Xen and the Art of Virtualization
Paul Barham∗, Boris Dragovic, Keir Fraser, Steven Hand, Tim Harris,Alex Ho, Rolf Neugebauer†, Ian Pratt, Andrew Warfield
University of Cambridge Computer Laboratory
15 JJ Thomson Avenue, Cambridge, UK, CB3 0FD{firstname.lastname}@cl.cam.ac.uk

ABSTRACT

1.

Numerous systems have been designed which use virtualization to
subdivide the ample resources of a modern computer. Some require
specialized hardware, or cannot support commodity operating systems. Some target 100% binary compatibility at the expense of
performance. Others sacrifice security or functionality for speed.
Few offer resource isolation or performance guarantees; most provide only best-effort provisioning, risking denial of service.
This paper presents Xen, an x86 virtual machine monitor whichallows multiple commodity operating systems to share conventional
hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality. This is achieved byproviding an idealized virtual machine abstraction to which operating systems such as Linux, BSD and Windows XP, can be portedwith minimal effort.
Our design is targeted at hosting up to 100 virtual machine instances simultaneously on a modern server. The virtualization approach taken by Xen is extremely efficient: we allow operating systems such as Linux and Windows XP to be hosted simultaneously
for a negligible performance overhead — at most a few percent
compared with the unvirtualized case. We considerably outperform
competing commercial and freely available solutions in a range of
microbenchmarks and system-wide tests.

Modern computers are sufficiently powerful to use virtualization
to present the illusion of many smaller virtual machines (VMs),
each running a separate operating system instance. This has led toa resurgence of interest in VM technology. In this paper we present
Xen, a high performance resource-managed virtual machine monitor (VMM) which enables applications such as server consolidation [42, 8], co-located hosting facilities [14], distributed web services [43], secure computing platforms [12, 16] and application
mobility [26, 37].
Successful partitioning of a machine to support the concurrent
execution of multiple operating systems poses several challenges.
Firstly, virtual machines must be isolated from one another: it is not
acceptable for the execution of one to adversely affect the performance of another. This is particularly true when virtual machines
are owned by mutually untrusting users. Secondly, it is necessary
to support a variety of different operating systems to accommodate
the heterogeneity of popular applications. Thirdly, the performance
overhead introduced by virtualization should be small.
Xen hosts commodity operating systems, albeit with some source
modifications. The prototype described and evaluated in this paper
can support multiple concurrent instances of our XenoLinux guest
operating system; each instance exports an application binary interface identical to a non-virtualized Linux 2.4. Our port of Windows
XP to Xen is not yet complete but is capable of running simple
user-space processes. Work is also progressing in porting NetBSD.
Xen enables users to dynamically instantiate an operating system to execute whatever they desire. In the XenoServer project [15,35] we are deploying Xen on standard server hardware at economically strategic locations within ISPs or at Internet exchanges. We
perform admission control when starting new virtual machines andexpect each VM to pay in some fashion for the resources it requires.
We discuss our ideas and approach in this direction elsewhere [21];this paper focuses on the VMM.
There are a number of ways to build a system to host multiple
applications and servers on a shared machine. Perhaps the simplest
is to deploy one or more hosts running a standard operating system such as Linux or Windows, and then to allow users to install
files and start processes — protection between applications being
provided by conventional OS techniques. Experience shows thatsystem administration can quickly become a time-consuming task
due to complex configuration interactions between supposedly disjoint applications.
More importantly, such systems do not adequately support performance isolation; the scheduling priority, memory demand, network traffic and disk accesses of one process impact the performance of others. This may be acceptable when there is adequate
provisioning and a closed user group (such as in the case of com-

Categories and Subject Descriptors
D.4.1 [Operating Systems]: Process Management; D.4.2 [Operating Systems]: Storage Management; D.4.8 [Operating Systems]:
Performance

General Terms
Design, Measurement, Performance

Keywords
Virtual Machine Monitors, Hypervisors, Paravirtualization∗†

Microsoft Research Cambridge, UKIntel Research Cambridge, UK

Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. To copy otherwise, torepublish, to post on servers or to redistribute to lists, requires prior specificpermission and/or a fee.
SOSP’03, October 19–22, 2003, Bolton Landing, New York, USA.
Copyright 2003 ACM 1-58113-757-5/03/0010 ...$5.00.

INTRODUCTION

putational grids, or the experimental PlanetLab platform [33]), but
not when resources are oversubscribed, or users uncooperative.
One way to address this problem is to retrofit support for performance isolation to the operating system. This has been demonstrated to a greater or lesser degree with resource containers [3],Linux/RK [32], QLinux [40] and SILK [4]. One difficulty withsuch approaches is ensuring that all resource usage is accounted tothe correct process — consider, for example, the complex interactions between applications due to buffer cache or page replacement
algorithms. This is effectively the problem of “QoS crosstalk” [41]within the operating system. Performing multiplexing at a low levelcan mitigate this problem, as demonstrated by the Exokernel [23]and Nemesis [27] operating systems. Unintentional or undesiredinteractions between tasks are minimized.
We use this same basic approach to build Xen, which multiplexes
physical resources at the granularity of an entire operating system
and is able to provide performance isolation between them. In contrast to process-level multiplexing this also allows a range of guest
operating systems to gracefully coexist rather than mandating a
specific application binary interface. There is a price to pay for thisflexibility — running a full OS is more heavyweight than runninga process, both in terms of initialization (e.g. booting or resuming
versus fork and exec), and in terms of resource consumption.
For our target of up to 100 hosted OS instances, we believe thisprice is worth paying; it allows individual users to run unmodified
binaries, or collections of binaries, in a resource controlled fashion(for instance an Apache server along with a PostgreSQL backend).
Furthermore it provides an extremely high level of flexibility since
the user can dynamically create the precise execution environment
their software requires. Unfortunate configuration interactions between various services and applications are avoided (for example,
each Windows instance maintains its own registry).
The remainder of this paper is structured as follows: in Section 2
we explain our approach towards virtualization and outline how
Xen works. Section 3 describes key aspects of our design and implementation. Section 4 uses industry standard benchmarks to evaluate the performance of XenoLinux running above Xen in comparison with stand-alone Linux, VMware Workstation and User-mode
Linux (UML). Section 5 reviews related work, and finally Section 6
discusses future work and concludes.

2. XEN: APPROACH & OVERVIEW
In a traditional VMM the virtual hardware exposed is functionally identical to the underlying machine [38]. Although full virtualization has the obvious benefit of allowing unmodified operating
systems to be hosted, it also has a number of drawbacks. This isparticularly true for the prevalent IA-32, or x86, architecture.
Support for full virtualization was never part of the x86 architectural design. Certain supervisor instructions must be handled by
the VMM for correct virtualization, but executing these with insufficient privilege fails silently rather than causing a convenient
trap [36]. Efficiently virtualizing the x86 MMU is also difficult.
These problems can be solved, but only at the cost of increased
complexity and reduced performance. VMware’s ESX Server [10]dynamically rewrites portions of the hosted machine code to insert
traps wherever VMM intervention might be required. This translation is applied to the entire guest OS kernel (with associated translation, execution, and caching costs) since all non-trapping privileged instructions must be caught and handled. ESX Server implements shadow versions of system structures such as page tables andmaintains consistency with the virtual tables by trapping every update attempt — this approach has a high cost for update-intensive
operations such as creating a new application process.

Notwithstanding the intricacies of the x86, there are other arguments against full virtualization. In particular, there are situations
in which it is desirable for the hosted operating systems to see real
as well as virtual resources: providing both real and virtual timeallows a guest OS to better support time-sensitive tasks, and to correctly handle TCP timeouts and RTT estimates, while exposing realmachine addresses allows a guest OS to improve performance byusing superpages [30] or page coloring [24].
We avoid the drawbacks of full virtualization by presenting a virtual machine abstraction that is similar but not identical to the underlying hardware — an approach which has been dubbed paravirtualization [43]. This promises improved performance, although
it does require modifications to the guest operating system. It is
important to note, however, that we do not require changes to theapplication binary interface (ABI), and hence no modifications are
required to guest applications.
We distill the discussion so far into a set of design principles:
1. Support for unmodified application binaries is essential, or
users will not transition to Xen. Hence we must virtualize allarchitectural features required by existing standard ABIs.
2. Supporting full multi-application operating systems is important, as this allows complex server configurations to be
virtualized within a single guest OS instance.
3. Paravirtualization is necessary to obtain high performanceand strong resource isolation on uncooperative machine architectures such as x86.
4. Even on cooperative machine architectures, completely hiding the effects of resource virtualization from guest OSesrisks both correctness and performance.
Note that our paravirtualized x86 abstraction is quite different
from that proposed by the recent Denali project [44]. Denali is designed to support thousands of virtual machines running network
services, the vast majority of which are small-scale and unpopular. In contrast, Xen is intended to scale to approximately 100 virtual machines running industry standard applications and services.
Given these very different goals, it is instructive to contrast Denali’s
design choices with our own principles.
Firstly, Denali does not target existing ABIs, and so can elidecertain architectural features from their VM interface. For example, Denali does not fully support x86 segmentation although it isexported (and widely used1 ) in the ABIs of NetBSD, Linux, andWindows XP.
Secondly, the Denali implementation does not address the problem of supporting application multiplexing, nor multiple address
spaces, within a single guest OS. Rather, applications are linked
explicitly against an instance of the Ilwaco guest OS in a manner
rather reminiscent of a libOS in the Exokernel [23]. Hence each virtual machine essentially hosts a single-user single-application unprotected “operating system”. In Xen, by contrast, a single virtual
machine hosts a real operating system which may itself securely
multiplex thousands of unmodified user-level processes. Althougha prototype virtual MMU has been developed which may help Denali in this area [44], we are unaware of any published technicaldetails or evaluation.
Thirdly, in the Denali architecture the VMM performs all paging
to and from disk. This is perhaps related to the lack of memorymanagement support at the virtualization layer. Paging within the1
For example, segments are frequently used by thread libraries to address
thread-local data.

Memory Management
Segmentation
PagingCPU
Protection
Exceptions
System Calls
Interrupts
Time
Device I/O
Network, Disk, etc.

Cannot install fully-privileged segment descriptors and cannot overlap with the top end of the linear
address space.
Guest OS has direct read access to hardware page tables, but updates are batched and validated by
the hypervisor. A domain may be allocated discontiguous machine pages.
Guest OS must run at a lower privilege level than Xen.
Guest OS must register a descriptor table for exception handlers with Xen. Aside from page faults,
the handlers remain the same.
Guest OS may install a ‘fast’ handler for system calls, allowing direct calls from an application into
its guest OS and avoiding indirecting through Xen on every call.
Hardware interrupts are replaced with a lightweight event system.
Each guest OS has a timer interface and is aware of both ‘real’ and ‘virtual’ time.
Virtual devices are elegant and simple to access. Data is transferred using asynchronous I/O rings.
An event mechanism replaces hardware interrupts for notifications.
Table 1: The paravirtualized x86 interface.

Table 1 presents an overview of the paravirtualized x86 interface,factored into three broad aspects of the system: memory management, the CPU, and device I/O. In the following we address eachmachine subsystem in turn, and discuss how each is presented in
our paravirtualized architecture. Note that although certain partsof our implementation, such as memory management, are specificto the x86, many aspects (such as our virtual CPU and I/O devices)can be readily applied to other machine architectures. Furthermore,
x86 represents a worst case in the areas where it differs significantly
from RISC-style processors — for example, efficiently virtualizing
hardware page tables is more difficult than virtualizing a softwaremanaged TLB.

guest OS. The task is easier if the architecture provides a softwaremanaged TLB as these can be efficiently virtualized in a simple
manner [13]. A tagged TLB is another useful feature supported
by most server-class RISC architectures, including Alpha, MIPS
and SPARC. Associating an address-space identifier tag with each
TLB entry allows the hypervisor and each guest OS to efficiently
coexist in separate address spaces because there is no need to flush
the entire TLB when transferring execution.
Unfortunately, x86 does not have a software-managed TLB; instead TLB misses are serviced automatically by the processor bywalking the page table structure in hardware. Thus to achieve thebest possible performance, all valid page translations for the current
address space should be present in the hardware-accessible pagetable. Moreover, because the TLB is not tagged, address spaceswitches typically require a complete TLB flush. Given these limitations, we made two decisions: (i) guest OSes are responsible forallocating and managing the hardware page tables, with minimal
involvement from Xen to ensure safety and isolation; and (ii) Xen
exists in a 64MB section at the top of every address space, thus
avoiding a TLB flush when entering and leaving the hypervisor.
Each time a guest OS requires a new page table, perhaps because a new process is being created, it allocates and initializes apage from its own memory reservation and registers it with Xen.
At this point the OS must relinquish direct write privileges to thepage-table memory: all subsequent updates must be validated by
Xen. This restricts updates in a number of ways, including only
allowing an OS to map pages that it owns, and disallowing writable
mappings of page tables. Guest OSes may batch update requests toamortize the overhead of entering the hypervisor. The top 64MB
region of each address space, which is reserved for Xen, is not accessible or remappable by guest OSes. This address region is not
used by any of the common x86 ABIs however, so this restriction
does not break application compatibility.
Segmentation is virtualized in a similar way, by validating updates to hardware segment descriptor tables. The only restrictions
on x86 segment descriptors are: (i) they must have lower privilege than Xen, and (ii) they may not allow any access to the Xenreserved portion of the address space.

2.1.1

2.1.2

VMM is contrary to our goal of performance isolation: malicious
virtual machines can encourage thrashing behaviour, unfairly depriving others of CPU time and disk bandwidth. In Xen we expect
each guest OS to perform its own paging using its own guaranteed memory reservation and disk allocation (an idea previously
exploited by self-paging [20]).
Finally, Denali virtualizes the ‘namespaces’ of all machine resources, taking the view that no VM can access the resource allocations of another VM if it cannot name them (for example, VMs haveno knowledge of hardware addresses, only the virtual addresses
created for them by Denali). In contrast, we believe that secure access control within the hypervisor is sufficient to ensure protection;
furthermore, as discussed previously, there are strong correctness
and performance arguments for making physical resources directly
visible to guest OSes.
In the following section we describe the virtual machine abstraction exported by Xen and discuss how a guest OS must be modified
to conform to this. Note that in this paper we reserve the term guest
operating system to refer to one of the OSes that Xen can host and
we use the term domain to refer to a running virtual machine within
which a guest OS executes; the distinction is analogous to that between a program and a process in a conventional system. We call
Xen itself the hypervisor since it operates at a higher privilege level
than the supervisor code of the guest operating systems that it hosts.

2.1 The Virtual Machine Interface

Memory management

Virtualizing memory is undoubtedly the most difficult part ofparavirtualizing an architecture, both in terms of the mechanisms
required in the hypervisor and modifications required to port each

CPU

Virtualizing the CPU has several implications for guest OSes.
Principally, the insertion of a hypervisor below the operating system violates the usual assumption that the OS is the most privilegedentity in the system. In order to protect the hypervisor from OS
misbehavior (and domains from one another) guest OSes must be
modified to run at a lower privilege level.
Many processor architectures only provide two privilege levels.
In these cases the guest OS would share the lower privilege levelwith applications. The guest OS would then protect itself by running in a separate address space from its applications, and indirectly
pass control to and from applications via the hypervisor to set thevirtual privilege level and change the current address space. Again,
if the processor’s TLB supports address-space tags then expensive
TLB flushes can be avoided.
Efficient virtualizion of privilege levels is possible on x86 because it supports four distinct privilege levels in hardware. The x86
privilege levels are generally described as rings, and are numberedfrom zero (most privileged) to three (least privileged). OS code
typically executes in ring 0 because no other ring can execute privileged instructions, while ring 3 is generally used for application
code. To our knowledge, rings 1 and 2 have not been used by any
well-known x86 OS since OS/2. Any OS which follows this common arrangement can be ported to Xen by modifying it to executein ring 1. This prevents the guest OS from directly executing privileged instructions, yet it remains safely isolated from applications
running in ring 3.
Privileged instructions are paravirtualized by requiring them to
be validated and executed within Xen— this applies to operations
such as installing a new page table, or yielding the processor whenidle (rather than attempting to hlt it). Any guest OS attempt todirectly execute a privileged instruction is failed by the processor,
either silently or by taking a fault, since only Xen executes at a
sufficiently privileged level.
Exceptions, including memory faults and software traps, are virtualized on x86 very straightforwardly. A table describing the handler for each type of exception is registered with Xen for validation. The handlers specified in this table are generally identicalto those for real x86 hardware; this is possible because the exception stack frames are unmodified in our paravirtualized architecture. The sole modification is to the page fault handler, which
would normally read the faulting address from a privileged processor register (CR2); since this is not possible, we write it into an
extended stack frame2 . When an exception occurs while executing
outside ring 0, Xen’s handler creates a copy of the exception stack
frame on the guest OS stack and returns control to the appropriate
registered handler.
Typically only two types of exception occur frequently enough toaffect system performance: system calls (which are usually implemented via a software exception), and page faults. We improve theperformance of system calls by allowing each guest OS to registera ‘fast’ exception handler which is accessed directly by the processor without indirecting via ring 0; this handler is validated before
installing it in the hardware exception table. Unfortunately it is notpossible to apply the same technique to the page fault handler because only code executing in ring 0 can read the faulting addressfrom register CR2; page faults must therefore always be delivered
via Xen so that this register value can be saved for access in ring 1.
Safety is ensured by validating exception handlers when they arepresented to Xen. The only required check is that the handler’s code
segment does not specify execution in ring 0. Since no guest OS
can create such a segment, it suffices to compare the specified segment selector to a small number of static values which are reserved
by Xen. Apart from this, any other handler problems are fixed up
during exception propagation — for example, if the handler’s code2
In hindsight, writing the value into a pre-agreed shared memory location
rather than modifying the stack frame would have simplified the XP port.

OS subsection
Architecture-independent
Virtual network driver
Virtual block-device driver
Xen-specific (non-driver)
Total(Portion of total x86 code base# lines
Linux
XP
78
1299
484
–
1070
–
1363
3321
2995
4620
1.36% 0.04%)

Table 2: The simplicity of porting commodity OSes to Xen. The
cost metric is the number of lines of reasonably commented andformatted code which are modified or added compared with theoriginal x86 code base (excluding device drivers).

segment is not present or if the handler is not paged into memory then an appropriate fault will be taken when Xen executes theiret instruction which returns to the handler. Xen detects these“double faults” by checking the faulting program counter value: if
the address resides within the exception-virtualizing code then theoffending guest OS is terminated.
Note that this “lazy” checking is safe even for the direct systemcall handler: access faults will occur when the CPU attempts todirectly jump to the guest OS handler. In this case the faulting
address will be outside Xen (since Xen will never execute a guest
OS system call) and so the fault is virtualized in the normal way.
If propagation of the fault causes a further “double fault” then theguest OS is terminated as described above.

2.1.3

Device I/O

Rather than emulating existing hardware devices, as is typicallydone in fully-virtualized environments, Xen exposes a set of cleanand simple device abstractions. This allows us to design an interface that is both efficient and satisfies our requirements for protection and isolation. To this end, I/O data is transferred to and fromeach domain via Xen, using shared-memory, asynchronous bufferdescriptor rings. These provide a high-performance communication mechanism for passing buffer information vertically throughthe system, while allowing Xen to efficiently perform validation
checks (for example, checking that buffers are contained within adomain’s memory reservation).
Similar to hardware interrupts, Xen supports a lightweight eventdelivery mechanism which is used for sending asynchronous notifications to a domain. These notifications are made by updating abitmap of pending event types and, optionally, by calling an event
handler specified by the guest OS. These callbacks can be ‘held off’at the discretion of the guest OS — to avoid extra costs incurred byfrequent wake-up notifications, for example.

2.2

The Cost of Porting an OS to Xen

Table 2 demonstrates the cost, in lines of code, of porting commodity operating systems to Xen’s paravirtualized x86 environment. Note that our NetBSD port is at a very early stage, and hence
we report no figures here. The XP port is more advanced, but still inprogress; it can execute a number of user-space applications froma RAM disk, but it currently lacks any virtual I/O drivers. For thisreason, figures for XP’s virtual device drivers are not presented.
However, as with Linux, we expect these drivers to be small andsimple due to the idealized hardware abstraction presented by Xen.
Windows XP required a surprising number of modifications to
its architecture independent OS code because it uses a variety ofstructures and unions for accessing page-table entries (PTEs). Eachpage-table access had to be separately modified, although some ofControl
Plane
SoftwareUser
SoftwareUser
SoftwareUser
SoftwareGuestOS

GuestOS

GuestOS

GuestOS(XenoLinux)(XenoLinux)(XenoBSD)(XenoXP)Xeno-Aware
Device Drivers

Xeno-Aware
Device Drivers

Xeno-Aware
Device Drivers

Xeno-Aware
Device Drivers

Domain0
controlinterfacevirtualx86 CPUvirtualphy mem

virtualnetworkvirtualblockdev

X
E
N

read-only VBD may be created, or a VIF may filter IP packets toprevent source-address spoofing).
This control interface, together with profiling statistics on thecurrent state of the system, is exported to a suite of applicationlevel management software running in Domain0. This complementof administrative tools allows convenient management of the entire
server: current tools can create and destroy domains, set network
filters and routing rules, monitor per-domain network activity atpacket and flow granularity, and create and delete virtual network
interfaces and virtual block devices. We anticipate the developmentof higher-level tools to further automate the application of administrative policy.

H/W (SMP x86, phy mem, enet, SCSI/IDE)

3.
Figure 1: The structure of a machine running the Xen hypervisor, hosting a number of different guest operating systems,
including Domain0 running control software in a XenoLinux
environment.

this process was automated with scripts. In contrast, Linux needed
far fewer modifications to its generic memory system as it uses preprocessor macros to access PTEs — the macro definitions provide
a convenient place to add the translation and hypervisor calls required by paravirtualization.
In both OSes, the architecture-specific sections are effectively
a port of the x86 code to our paravirtualized architecture. This
involved rewriting routines which used privileged instructions, andremoving a large amount of low-level system initialization code.
Again, more changes were required in Windows XP, mainly due
to the presence of legacy 16-bit emulation code and the need fora somewhat different boot-loading mechanism. Note that the x86specific code base in XP is substantially larger than in Linux andhence a larger porting effort should be expected.

2.3 Control and Management
Throughout the design and implementation of Xen, a goal has
been to separate policy from mechanism wherever possible. Although the hypervisor must be involved in data-path aspects (forexample, scheduling the CPU between domains, filtering network
packets before transmission, or enforcing access control when reading data blocks), there is no need for it to be involved in, or evenaware of, higher level issues such as how the CPU is to be shared,or which kinds of packet each domain may transmit.
The resulting architecture is one in which the hypervisor itself
provides only basic control operations. These are exported throughan interface accessible from authorized domains; potentially complex policy decisions, such as admission control, are best performedby management software running over a guest OS rather than inprivileged hypervisor code.
The overall system structure is illustrated in Figure 1. Note thata domain is created at boot time which is permitted to use the control interface. This initial domain, termed Domain0, is responsible
for hosting the application-level management software. The control interface provides the ability to create and terminate other domains and to control their associated scheduling parameters, physical memory allocations and the access they are given to the machine’s physical disks and network devices.
In addition to processor and memory resources, the control interface supports the creation and deletion of virtual network interfaces(VIFs) and block devices (VBDs). These virtual I/O devices haveassociated access-control information which determines which domains can access them, and with what restrictions (for example, a

DETAILED DESIGNIn this section we introduce the design of the major subsystems
that make up a Xen-based server. In each case we present both
Xen and guest OS functionality for clarity of exposition. The current discussion of guest OSes focuses on XenoLinux as this is themost mature; nonetheless our ongoing porting of Windows XP and
NetBSD gives us confidence that Xen is guest OS agnostic.

3.1

Control Transfer: Hypercalls and Events

Two mechanisms exist for control interactions between Xen andan overlying domain: synchronous calls from a domain to Xen may
be made using a hypercall, while notifications are delivered to domains from Xen using an asynchronous event mechanism.
The hypercall interface allows domains to perform a synchronous
software trap into the hypervisor to perform a privileged operation,
analogous to the use of system calls in conventional operating systems. An example use of a hypercall is to request a set of pagetable updates, in which Xen validates and applies a list of updates,
returning control to the calling domain when this is completed.
Communication from Xen to a domain is provided through anasynchronous event mechanism, which replaces the usual delivery
mechanisms for device interrupts and allows lightweight notification of important events such as domain-termination requests. Akinto traditional Unix signals, there are only a small number of events,
each acting to flag a particular type of occurrence. For instance,
events are used to indicate that new data has been received over the
network, or that a virtual disk request has completed.
Pending events are stored in a per-domain bitmask which is updated by Xen before invoking an event-callback handler specified
by the guest OS. The callback handler is responsible for resetting
the set of pending events, and responding to the notifications in an
appropriate manner. A domain may explicitly defer event handlingby setting a Xen-readable software flag: this is analogous to disabling interrupts on a real processor.

3.2

Data Transfer: I/O Rings

The presence of a hypervisor means there is an additional protection domain between guest OSes and I/O devices, so it is crucial
that a data transfer mechanism be provided that allows data to movevertically through the system with as little overhead as possible.
Two main factors have shaped the design of our I/O-transfer
mechanism: resource management and event notification. For resource accountability, we attempt to minimize the work required todemultiplex data to a specific domain when an interrupt is received
from a device — the overhead of managing buffers is carried out
later where computation may be accounted to the appropriate domain. Similarly, memory committed to device I/O is provided by
the relevant domains wherever possible to prevent the crosstalk inherent in shared buffer pools; I/O buffers are protected during datatransfer by pinning the underlying page frames within Xen.

Request Consumer
Private pointerin XenResponse Producer
Shared pointerupdated by
Xen

Request Producer
Shared pointerupdated by guest OS

Response Consumer
Private pointerin guest OS

Request queue - Descriptors queued by the VM but not yet accepted by Xen
Outstanding descriptors - Descriptor slots awaiting a response from Xen
Response queue - Descriptors returned by Xen in response to serviced requests
Unused descriptors

Figure 2: The structure of asynchronous I/O rings, which areused for data transfer between Xen and guest OSes.

Figure 2 shows the structure of our I/O descriptor rings. A ringis a circular queue of descriptors allocated by a domain but accessible from within Xen. Descriptors do not directly contain I/O data;
instead, I/O data buffers are allocated out-of-band by the guest OS
and indirectly referenced by I/O descriptors. Access to each ringis based around two pairs of producer-consumer pointers: domains
place requests on a ring, advancing a request producer pointer, andXen removes these requests for handling, advancing an associatedrequest consumer pointer. Responses are placed back on the ringsimilarly, save with Xen as the producer and the guest OS as theconsumer. There is no requirement that requests be processed inorder: the guest OS associates a unique identifier with each request
which is reproduced in the associated response. This allows Xen to
unambiguously reorder I/O operations due to scheduling or priority
considerations.
This structure is sufficiently generic to support a number of different device paradigms. For example, a set of ‘requests’ can provide buffers for network packet reception; subsequent ‘responses’
then signal the arrival of packets into these buffers. Reordering
is useful when dealing with disk requests as it allows them to bescheduled within Xen for efficiency, and the use of descriptors with
out-of-band buffers makes implementing zero-copy transfer easy.
We decouple the production of requests or responses from thenotification of the other party: in the case of requests, a domain
may enqueue multiple entries before invoking a hypercall to alert
Xen; in the case of responses, a domain can defer delivery of a
notification event by specifying a threshold number of responses.
This allows each domain to trade-off latency and throughput requirements, similarly to the flow-aware interrupt dispatch in the
ArseNIC Gigabit Ethernet interface [34].

3.3 Subsystem Virtualization
The control and data transfer mechanisms described are used in
our virtualization of the various subsystems. In the following, we
discuss how this virtualization is achieved for CPU, timers, memory, network and disk.

3.3.1

CPU scheduling

Xen currently schedules domains according to the Borrowed Virtual Time (BVT) scheduling algorithm [11]. We chose this particular algorithms since it is both work-conserving and has a special mechanism for low-latency wake-up (or dispatch) of a domain
when it receives an event. Fast dispatch is particularly importantto minimize the effect of virtualization on OS subsystems that aredesigned to run in a timely fashion; for example, TCP relies on

the timely delivery of acknowledgments to correctly estimate network round-trip times. BVT provides low-latency dispatch by using virtual-time warping, a mechanism which temporarily violates‘ideal’ fair sharing to favor recently-woken domains. However,other scheduling algorithms could be trivially implemented over
our generic scheduler abstraction. Per-domain scheduling parameters can be adjusted by management software running in Domain0.

3.3.2

Time and timers

Xen provides guest OSes with notions of real time, virtual time
and wall-clock time. Real time is expressed in nanoseconds passed
since machine boot and is maintained to the accuracy of the processor’s cycle counter and can be frequency-locked to an external timesource (for example, via NTP). A domain’s virtual time only advances while it is executing: this is typically used by the guest OS
scheduler to ensure correct sharing of its timeslice between application processes. Finally, wall-clock time is specified as an offset
to be added to the current real time. This allows the wall-clock time
to be adjusted without affecting the forward progress of real time.
Each guest OS can program a pair of alarm timers, one for realtime and the other for virtual time. Guest OSes are expected tomaintain internal timer queues and use the Xen-provided alarm
timers to trigger the earliest timeout. Timeouts are delivered using Xen’s event mechanism.

3.3.3

Virtual address translation

As with other subsystems, Xen attempts to virtualize memory
access with as little overhead as possible. As discussed in Section 2.1.1, this goal is made somewhat more difficult by the x86
architecture’s use of hardware page tables. The approach taken by
VMware is to provide each guest OS with a virtual page table, notvisible to the memory-management unit (MMU) [10]. The hypervisor is then responsible for trapping accesses to the virtual pagetable, validating updates, and propagating changes back and forth
between it and the MMU-visible ‘shadow’ page table. This greatly
increases the cost of certain guest OS operations, such as creating new virtual address spaces, and requires explicit propagation of
hardware updates to ‘accessed’ and ‘dirty’ bits.
Although full virtualization forces the use of shadow page tables,
to give the illusion of contiguous physical memory, Xen is not soconstrained. Indeed, Xen need only be involved in page table updates, to prevent guest OSes from making unacceptable changes.
Thus we avoid the overhead and additional complexity associatedwith the use of shadow page tables — the approach in Xen is toregister guest OS page tables directly with the MMU, and restrict
guest OSes to read-only access. Page table updates are passed to
Xen via a hypercall; to ensure safety, requests are validated before
being applied.
To aid validation, we associate a type and reference count witheach machine page frame. A frame may have any one of the following mutually-exclusive types at any point in time: page directory (PD), page table (PT), local descriptor table (LDT), global descriptor table (GDT), or writable (RW). Note that a guest OS may
always create readable mappings to its own page frames, regardlessof their current types. A frame may only safely be retasked when
its reference count is zero. This mechanism is used to maintain theinvariants required for safety; for example, a domain cannot have awritable mapping to any part of a page table as this would require
the frame concerned to simultaneously be of types PT and RW.
The type system is also used to track which frames have alreadybeen validated for use in page tables. To this end, guest OSes indicate when a frame is allocated for page-table use — this requires aone-off validation of every entry in the frame by Xen, after whichits type is pinned to PD or PT as appropriate, until a subsequent
unpin request from the guest OS. This is particularly useful whenchanging the page table base pointer, as it obviates the need to validate the new page table on every context switch. Note that a frame
cannot be retasked until it is both unpinned and its reference counthas reduced to zero – this prevents guest OSes from using unpin
requests to circumvent the reference-counting mechanism.
To minimize the number of hypercalls required, guest OSes canlocally queue updates before applying an entire batch with a single
hypercall — this is particularly beneficial when creating new address spaces. However we must ensure that updates are committed
early enough to guarantee correctness. Fortunately, a guest OS will
typically execute a TLB flush before the first use of a new mapping:
this ensures that any cached translation is invalidated. Hence, committing pending updates immediately before a TLB flush usually
suffices for correctness. However, some guest OSes elide the flush
when it is certain that no stale entry exists in the TLB. In this case
it is possible that the first attempted use of the new mapping willcause a page-not-present fault. Hence the guest OS fault handler
must check for outstanding updates; if any are found then they areflushed and the faulting instruction is retried.

3.3.4

Physical memory

The initial memory allocation, or reservation, for each domain is
specified at the time of its creation; memory is thus statically partitioned between domains, providing strong isolation. A maximumallowable reservation may also be specified: if memory pressure
within a domain increases, it may then attempt to claim additional
memory pages from Xen, up to this reservation limit. Conversely,
if a domain wishes to save resources, perhaps to avoid incurring unnecessary costs, it can reduce its memory reservation by releasing
memory pages back to Xen.
XenoLinux implements a balloon driver [42], which adjusts a
domain’s memory usage by passing memory pages back and forth
between Xen and XenoLinux’s page allocator. Although we could
modify Linux’s memory-management routines directly, the balloon
driver makes adjustments by using existing OS functions, thus simplifying the Linux porting effort. However, paravirtualization canbe used to extend the capabilities of the balloon driver; for example, the out-of-memory handling mechanism in the guest OS can be
modified to automatically alleviate memory pressure by requesting
more memory from Xen.
Most operating systems assume that memory comprises at mosta few large contiguous extents. Because Xen does not guarantee toallocate contiguous regions of memory, guest OSes will typicallycreate for themselves the illusion of contiguous physical memory,even though their underlying allocation of hardware memory issparse. Mapping from physical to hardware addresses is entirely
the responsibility of the guest OS, which can simply maintain anarray indexed by physical page frame number. Xen supports efficient hardware-to-physical mapping by providing a shared translation array that is directly readable by all domains – updates to thisarray are validated by Xen to ensure that the OS concerned owns
the relevant hardware page frames.
Note that even if a guest OS chooses to ignore hardware addresses in most cases, it must use the translation tables when accessing its page tables (which necessarily use hardware addresses).
Hardware addresses may also be exposed to limited parts of theOS’s memory-management system to optimize memory access. For
example, a guest OS might allocate particular hardware pages so
as to optimize placement within a physically indexed cache [24],or map naturally aligned contiguous portions of hardware memory
using superpages [30].

3.3.5

Network

Xen provides the abstraction of a virtual firewall-router (VFR),
where each domain has one or more network interfaces (VIFs) logically attached to the VFR. A VIF looks somewhat like a modern
network interface card: there are two I/O rings of buffer descriptors, one for transmit and one for receive. Each direction also has
a list of associated rules of the form (<pattern>, <action>) — if
the pattern matches then the associated action is applied.
Domain0 is responsible for inserting and removing rules. In typical cases, rules will be installed to prevent IP source address spoofing, and to ensure correct demultiplexing based on destination IP
address and port. Rules may also be associated with hardware interfaces on the VFR. In particular, we may install rules to perform
traditional firewalling functions such as preventing incoming connection attempts on insecure ports.
To transmit a packet, the guest OS simply enqueues a buffer
descriptor onto the transmit ring. Xen copies the descriptor and,to ensure safety, then copies the packet header and executes any
matching filter rules. The packet payload is not copied since we use
scatter-gather DMA; however note that the relevant page frames
must be pinned until transmission is complete. To ensure fairness,
Xen implements a simple round-robin packet scheduler.
To efficiently implement packet reception, we require the guest
OS to exchange an unused page frame for each packet it receives;
this avoids the need to copy the packet between Xen and the guest
OS, although it requires that page-aligned receive buffers be queued
at the network interface. When a packet is received, Xen immediately checks the set of receive rules to determine the destination
VIF, and exchanges the packet buffer for a page frame on the relevant receive ring. If no frame is available, the packet is dropped.

3.3.6

Disk

Only Domain0 has direct unchecked access to physical (IDE and
SCSI) disks. All other domains access persistent storage throughthe abstraction of virtual block devices (VBDs), which are createdand configured by management software running within Domain0.
Allowing Domain0 to manage the VBDs keeps the mechanisms
within Xen very simple and avoids more intricate solutions such as
the UDFs used by the Exokernel [23].
A VBD comprises a list of extents with associated ownershipand access control information, and is accessed via the I/O ringmechanism. A typical guest OS disk scheduling algorithm will reorder requests prior to enqueuing them on the ring in an attempt toreduce response time, and to apply differentiated service (for example, it may choose to aggressively schedule synchronous metadata
requests at the expense of speculative readahead requests). However, because Xen has more complete knowledge of the actual disklayout, we also support reordering within Xen, and so responses
may be returned out of order. A VBD thus appears to the guest OS
somewhat like a SCSI disk.
A translation table is maintained within the hypervisor for each
VBD; the entries within this table are installed and managed by
Domain0 via a privileged control interface. On receiving a disk
request, Xen inspects the VBD identifier and offset and produces
the corresponding sector address and physical device. Permission
checks also take place at this time. Zero-copy data transfer takes
place using DMA between the disk and pinned memory pages in
the requesting domain.
Xen services batches of requests from competing domains in a
simple round-robin fashion; these are then passed to a standard elevator scheduler before reaching the disk hardware. Domains may
explicitly pass down reorder barriers to prevent reordering when
this is necessary to maintain higher level semantics (e.g. when us-

ing a write-ahead log). The low-level scheduling gives us good
throughput, while the batching of requests provides reasonably fair
access. Future work will investigate providing more predictable
isolation and differentiated service, perhaps using existing techniques and schedulers [39].

3.4 Building a New Domain
The task of building the initial guest OS structures for a new
domain is mostly delegated to Domain0 which uses its privileged
control interfaces (Section 2.3) to access the new domain’s memory
and inform Xen of initial register state. This approach has a number of advantages compared with building a domain entirely within
Xen, including reduced hypervisor complexity and improved robustness (accesses to the privileged interface are sanity checkedwhich allowed us to catch many bugs during initial development).
Most important, however, is the ease with which the building
process can be extended and specialized to cope with new guest
OSes. For example, the boot-time address space assumed by theLinux kernel is considerably simpler than that expected by Windows XP. It would be possible to specify a fixed initial memory
layout for all guest OSes, but this would require additional bootstrap code within every guest OS to lay things out as required by
the rest of the OS. Unfortunately this type of code is tricky to implement correctly; for simplicity and robustness it is therefore betterto implement it within Domain0 which can provide much richer
diagnostics and debugging support than a bootstrap environment.

4. EVALUATIONIn this section we present a thorough performance evaluationof Xen. We begin by benchmarking Xen against a number of alternative virtualization techniques, then compare the total systemthroughput executing multiple applications concurrently on a single native operating system against running each application in its
own virtual machine. We then evaluate the performance isolation
Xen provides between guest OSes, and assess the total overhead of
running large numbers of operating systems on the same hardware.
For these measurements, we have used our XenoLinux port (basedon Linux 2.4.21) as this is our most mature guest OS. We expect
the relative overheads for our Windows XP and NetBSD ports tobe similar but have yet to conduct a full evaluation.
There are a number of preexisting solutions for running multiple copies of Linux on the same machine. VMware offers several
commercial products that provide virtual x86 machines on whichunmodified copies of Linux may be booted. The most commonlyused version is VMware Workstation, which consists of a set ofprivileged kernel extensions to a ‘host’ operating system. BothWindows and Linux hosts are supported. VMware also offer anenhanced product called ESX Server which replaces the host OS
with a dedicated kernel. By doing so, it gains some performance
benefit over the workstation product. ESX Server also supports aparavirtualized interface to the network that can be accessed by installing a special device driver (vmxnet) into the guest OS, where
deployment circumstances permit.
We have subjected ESX Server to the benchmark suites described
below, but sadly are prevented from reporting quantitative results
due to the terms of the product’s End User License Agreement. We
are authorized simply to say that “Xen significantly outperforms
ESX Server” on all benchmarks in the suite. We present resultsfor VMware Workstation 3.2, the most recent VMware product released without the benchmarking restriction, running over a Linux
host OS.
We also present results for User-mode Linux (UML), an increasingly popular platform for virtual hosting. UML is a port of Linuxto run as a user-space process on a Linux host. Like XenoLinux, thechanges required are restricted to the architecture dependent codebase. However, the UML code bears little similarity to the native
x86 port due to the very different nature of the execution environments. Although UML can run on an unmodified Linux host, we
present results for the ‘Single Kernel Address Space’ (skas3) variant that exploits patches to the host OS to improve performance.
We also investigated three other virtualization techniques for running ported versions of Linux on the same x86 machine. Connectix’s Virtual PC and forthcoming Virtual Server products (now acquired by Microsoft) are similar in design to VMware’s, providing
full x86 virtualization. Since all versions of Virtual PC have benchmarking restrictions in their license agreements we did not subject
them to closer analysis. UMLinux is similar in concept to UML
but is a different code base and has yet to achieve the same level of
performance, so we omit the results. Work to improve the performance of UMLinux through host OS modifications is ongoing [25].
Although Plex86 was originally a general purpose x86 VMM, it has
now been retargeted to support just Linux guest OSes. The guest
OS must be specially compiled to run on Plex86, but the sourcechanges from native x86 are trivial. The performance of Plex86 iscurrently well below the other techniques.
All the experiments were performed on a Dell 2650 dual processor 2.4GHz Xeon server with 2GB RAM, a Broadcom Tigon 3 Gigabit Ethernet NIC, and a single Hitachi DK32EJ 146GB 10k RPM
SCSI disk. Linux version 2.4.21 was used throughout, compiled
for architecture i686 for the native and VMware guest OS experiments, for xeno-i686 when running on Xen, and architecture um
when running on UML. The Xeon processors in the machine support SMT (“hyperthreading”), but this was disabled because noneof the kernels currently have SMT-aware schedulers. We ensured
that the total amount of memory available to all guest OSes plus
their VMM was equal to the total amount available to native Linux.
The RedHat 7.2 distribution was used throughout, installed on
ext3 file systems. The VMs were configured to use the same disk
partitions in ‘persistent raw mode’, which yielded the best performance. Using the same file system image also eliminated potential
differences in disk seek times and transfer rates.

4.1

Relative Performance

We have performed a battery of experiments in order to evaluate
the overhead of the various virtualization techniques relative to running on the ‘bare metal’. Complex application-level benchmarksthat exercise the whole system have been employed to characterize
performance under a range of server-type workloads. Since neither Xen nor any of the VMware products currently support multiprocessor guest OSes (although they are themselves both SMP
capable), the test machine was configured with one CPU for theseexperiments; we examine performance with concurrent guest OSes
later. The results presented are the median of seven trials.
The first cluster of bars in Figure 3 represents a relatively easy
scenario for the VMMs. The SPEC CPU suite contains a seriesof long-running computationally-intensive applications intended tomeasure the performance of a system’s processor, memory system,
and compiler quality. The suite performs little I/O and has little
interaction with the OS. With almost all CPU time spent executing
in user-space code, all three VMMs exhibit low overhead.
The next set of bars show the total elapsed time taken to builda default configuration of the Linux 2.4.21 kernel on a local ext3
file system with gcc 2.96. Native Linux spends about 7% of the
CPU time in the OS, mainly performing file I/O, scheduling andmemory management. In the case of the VMMs, this ‘system time’is expanded to a greater or lesser degree: whereas Xen incurs a

518

514

400

418

1714
158

1633

172

U

271

V

263

X

554

567

L

1.0

550

567

1.1

L

X

310

0.8
0.7
0.6

111

0.4

150

65

0.5

199

0.2

306

0.3

172

80

535

Relative score to Linux

334

0.9

0.1
0.0
SPEC INT2000 (score)

L

X

V

U

Linux build time (s)

L

X

V

U

OSDB-IR (tup/s)

L

X

V

U

OSDB-OLTP (tup/s)

L

X

V

U

dbench (score)

V

U

SPEC WEB99 (score)

Figure 3: Relative performance of native Linux (L), XenoLinux (X), VMware workstation 3.2 (V) and User-Mode Linux (U).
mere 3% overhead, the other VMMs experience a more significant
slowdown.
Two experiments were performed using the PostgreSQL 7.1.3
database, exercised by the Open Source Database Benchmark suite(OSDB) in its default configuration. We present results for themulti-user Information Retrieval (IR) and On-Line Transaction Processing (OLTP) workloads, both measured in tuples per second. A
small modification to the suite’s test harness was required to produce correct results, due to a UML bug which loses virtual-timer
interrupts under high load. The benchmark drives the database
via PostgreSQL’s native API (callable SQL) over a Unix domain
socket. PostgreSQL places considerable load on the operating system, and this is reflected in the substantial virtualization overheads
experienced by VMware and UML. In particular, the OLTP benchmark requires many synchronous disk operations, resulting in many
protection domain transitions.
The dbench program is a file system benchmark derived fromthe industry-standard ‘NetBench’. It emulates the load placed on afile server by Windows 95 clients. Here, we examine the throughput experienced by a single client performing around 90,000 filesystem operations.
SPEC WEB99 is a complex application-level benchmark for evaluating web servers and the systems that host them. The workload is
a complex mix of page requests: 30% require dynamic content generation, 16% are HTTP POST operations and 0.5% execute a CGI
script. As the server runs it generates access and POST logs, so
the disk workload is not solely read-only. Measurements therefore
reflect general OS performance, including file system and network,in addition to the web server itself.
A number of client machines are used to generate load for theserver under test, with each machine simulating a collection ofusers concurrently accessing the web site. The benchmark is run
repeatedly with different numbers of simulated users to determine
the maximum number that can be supported. SPEC WEB99 defines
a minimum Quality of Service that simulated users must receive inorder to be ‘conformant’ and hence count toward the score: users
must receive an aggregate bandwidth in excess of 320Kb/s over aseries of requests. A warm-up phase is allowed in which the num-

ber of simultaneous clients is slowly increased, allowing servers topreload their buffer caches.
For our experimental setup we used the Apache HTTP server
version 1.3.27, installing the modspecweb99 plug-in to perform
most but not all of the dynamic content generation — SPEC rules
require 0.5% of requests to use full CGI, forking a separate process. Better absolute performance numbers can be achieved withthe assistance of “TUX”, the Linux in-kernel static content web
server, but we chose not to use this as we felt it was less likely to be
representative of our real-world target applications. Furthermore,
although Xen’s performance improves when using TUX, VMware
suffers badly due to the increased proportion of time spent emulating ring 0 while executing the guest OS kernel.
SPEC WEB99 exercises the whole system. During the measurement period there is up to 180Mb/s of TCP network traffic andconsiderable disk read-write activity on a 2GB dataset. The benchmark is CPU-bound, and a significant proportion of the time isspent within the guest OS kernel, performing network stack processing, file system operations, and scheduling between the many
httpd processes that Apache needs to handle the offered load.
XenoLinux fares well, achieving within 1% of native Linux performance. VMware and UML both struggle, supporting less than athird of the number of clients of the native Linux system.

4.2

Operating System Benchmarks

To more precisely measure the areas of overhead within Xen andthe other VMMs, we performed a number of smaller experiments
targeting particular subsystems. We examined the overhead of virtualization as measured by McVoy’s lmbench program [29]. We
used version 3.0-a3 as this addresses many of the issues regarding the fidelity of the tool raised by Seltzer’s hbench [6]. The OS
performance subset of the lmbench suite consist of 37 microbenchmarks. In the native Linux case, we present figures for both uniprocessor (L-UP) and SMP (L-SMP) kernels as we were somewhat
surprised by the performance overhead incurred by the extra locking in the SMP system in many cases.
In 24 of the 37 microbenchmarks, XenoLinux performs similarly to native Linux, tracking the uniprocessor Linux kernel per-null nullopen slct sig sig fork exec sh
Config call I/O stat closeTCP inst hndl proc proc proc
L-SMP 0.53 0.81 2.10 3.51 23.2 0.83 2.94 143 601 4k2
L-UP 0.45 0.50 1.28 1.92 5.70 0.68 2.49 110 530 4k0
0.46 0.50 1.22 1.88 5.69 0.69 1.75 198 768 4k8
Xen
VMW 0.73 0.83 1.88 2.99 11.1 1.02 4.63 874 2k3 10k
24.7 25.1 36.1 62.8 39.9 26.0 46.0 21k 33k 58k
UML

TCP MTU 1500
TX
RX
Linux 897
897
Xen 897 (-0%)
897 (-0%)
VMW 291 (-68%) 615 (-31%)
UML 165 (-82%) 203 (-77%)

Table 6: ttcp: Bandwidth in Mb/s

Table 3: lmbench: Processes - times in µs
2p
Config 0K
L-SMP 1.69
L-UP 0.77
1.97
Xen
VMW 18.1
15.5
UML

2p
16K
1.88
0.91
2.22
17.6
14.6

2p
64K
2.03
1.06
2.67
21.3
14.4

8p
16K
2.36
1.03
3.07
22.4
16.3

8p
64K
26.8
24.3
28.7
51.6
36.8

16p
16K
4.79
3.61
7.08
41.7
23.6

16p
64K
38.4
37.6
39.4
72.2
52.0

Table 4: lmbench: Context switching times in µs
0K File10K File
Mmap Prot
create delete create delete lat
fault
L-SMP 44.9 24.2 123 45.2 99.0 1.33
L-UP 32.1 6.08 66.0 12.5 68.0 1.06
32.5 5.86 68.2 13.6 139 1.40
Xen
85.6 21.4 620 7.53
VMW 35.3 9.3
130 65.7 250 113 1k4 21.8
UML

Config

TCP MTU 500
TX
RX
602
544
516 (-14%) 467 (-14%)
101 (-83%) 137 (-75%)
61.1(-90%) 91.4(-83%)

Page
fault
1.88
1.42
2.73
12.4
26.3

Table 5: lmbench: File & VM system latencies in µs

formance closely and outperforming the SMP kernel. In Tables 3
to 5 we show results which exhibit interesting performance variations among the test systems; particularly large penalties for Xen
are shown in bold face.
In the process microbenchmarks (Table 3), Xen exhibits slower
fork, exec and sh performance than native Linux. This is expected,
since these operations require large numbers of page table updates
which must all be verified by Xen. However, the paravirtualization
approach allows XenoLinux to batch update requests. Creating newpage tables presents an ideal case: because there is no reason tocommit pending updates sooner, XenoLinux can amortize each hypercall across 2048 updates (the maximum size of its batch buffer).
Hence each update hypercall constructs 8MB of address space.
Table 4 shows context switch times between different numbersof processes with different working set sizes. Xen incurs an extra overhead between 1µs and 3µs, as it executes a hypercall tochange the page table base. However, context switch results forlarger working set sizes (perhaps more representative of real applications) show that the overhead is small compared with cache effects. Unusually, VMware Workstation is inferior to UML on thesemicrobenchmarks; however, this is one area where enhancements
in ESX Server are able to reduce the overhead.
The mmap latency and page fault latency results shown in Table 5 are interesting since they require two transitions into Xen per
page: one to take the hardware fault and pass the details to the guest
OS, and a second to install the updated page table entry on the guest
OS’s behalf. Despite this, the overhead is relatively modest.
One small anomaly in Table 3 is that XenoLinux has lower signalhandling latency than native Linux. This benchmark does not require any calls into Xen at all, and the 0.75µs (30%) speedup is presumably due to a fortuitous cache alignment in XenoLinux, hence
underlining the dangers of taking microbenchmarks too seriously.

4.2.1

Network performance

In order to evaluate the overhead of virtualizing the network, we
examine TCP performance over a Gigabit Ethernet LAN. In all experiments we use a similarly-configured SMP box running native
Linux as one of the endpoints. This enables us to measure receive
and transmit performance independently. The ttcp benchmark wasused to perform these measurements. Both sender and receiver applications were configured with a socket buffer size of 128kB, as
we found this gave best performance for all tested systems. The results presented are a median of 9 experiments transferring 400MB.
Table 6 presents two sets of results, one using the default Ethernet MTU of 1500 bytes, the other using a 500-byte MTU (chosen
as it is commonly used by dial-up PPP clients). The results demonstrate that the page-flipping technique employed by the XenoLinuxvirtual network driver avoids the overhead of data copying andhence achieves a very low per-byte overhead. With an MTU of 500
bytes, the per-packet overheads dominate. The extra complexity oftransmit firewalling and receive demultiplexing adversely impact
the throughput, but only by 14%.
VMware emulate a ‘pcnet32’ network card for communicatingwith the guest OS which provides a relatively clean DMA-based
interface. ESX Server also supports a special ‘vmxnet’ driver forcompatible guest OSes, which provides significant networking performance improvements.

4.3

Concurrent Virtual Machines

In this section, we compare the performance of running multiple applications in their own guest OS against running them on
the same native operating system. Our focus is on the results using Xen, but we comment on the performance of the other VMMs
where applicable.
Figure 4 shows the results of running 1, 2, 4, 8 and 16 copiesof the SPEC WEB99 benchmark in parallel on a two CPU machine. The native Linux was configured for SMP; on it we ran
multiple copies of Apache as concurrent processes. In Xen’s case,each instance of SPEC WEB99 was run in its own uniprocessor
Linux guest OS (along with an sshd and other management processes). Different TCP port numbers were used for each web server
to enable the copies to be run in parallel. Note that the size of theSPEC data set required for c simultaneous connections is (25 +(c × 0.66)) × 4.88 MBytes or approximately 3.3GB for 1000 connections. This is sufficiently large to thoroughly exercise the disk
and buffer cache subsystems.
Achieving good SPEC WEB99 scores requires both high throughput and bounded latency: for example, if a client request gets stalled
due to a badly delayed disk read, then the connection will be classed
as non conforming and won’t contribute to the score. Hence, it isimportant that the VMM schedules domains in a timely fashion. Bydefault, Xen uses a 5ms time slice.
In the case of a single Apache instance, the addition of a second CPU enables native Linux to improve on the score reported
in section 4.1 by 28%, to 662 conformant clients. However, the

200

0

2833

2685

3289
290

282

318
289

2104

1.5

1.0

1661

880

842

874

896

887

400

2.0

158

600

Aggregate score relative to single instance

662

800

906

1001
924
-16.3% (non-SMP guest)

Aggregate number of conforming clients

1000

0.5

0.0
L

X

1

L

X

2

L

X

4

L

X

8

L

X

1

16

best aggregate throughput is achieved when running two Apacheinstances, suggesting that Apache 1.3.27 may have some SMP scalability issues.
When running a single domain, Xen is hampered by a lack ofsupport for SMP guest OSes. However, Xen’s interrupt load balancer identifies the idle CPU and diverts all interrupt processing
to it, improving on the single CPU score by 9%. As the numberof domains increases, Xen’s performance improves to within a few
percent of the native case.
Next we performed a series of experiments running multiple instances of PostgreSQL exercised by the OSDB suite. Running multiple PostgreSQL instances on a single Linux OS proved difficult,as it is typical to run a single PostgreSQL instance supporting multiple databases. However, this would prevent different users having separate database configurations. We resorted to a combinationof chroot and software patches to avoid SysV IPC name-space
clashes between different PostgreSQL instances. In contrast, Xen
allows each instance to be started in its own domain allowing easy
configuration.
In Figure 5 we show the aggregate throughput Xen achieves
when running 1, 2, 4 and 8 instances of OSDB-IR and OSDBOLTP. When a second domain is added, full utilization of the second CPU almost doubles the total throughput. Increasing the number of domains further causes some reduction in aggregate throughput which can be attributed to increased context switching and disk
head movement. Aggregate scores running multiple PostgreSQL
instances on a single Linux OS are 25-35% lower than the equivalent scores using Xen. The cause is not fully understood, but it
appears that PostgreSQL has SMP scalability issues combined withpoor utilization of Linux’s block cache.
Figure 5 also demonstrates performance differentiation between
8 domains. Xen’s schedulers were configured to give each domain
an integer weight between 1 and 8. The resulting throughput scoresfor each domain are reflected in the different banding on the bar.
In the IR benchmark, the weighting has a precise influence overthroughput and each segment is within 4% of its expected size.
However, in the OLTP case, domains given a larger share of resources to not achieve proportionally higher scores: The high level4

8

8(diff)

OSDB-IR

Simultaneous SPEC WEB99 Instances on Linux (L) and Xen(X)Figure 4: SPEC WEB99 for 1, 2, 4, 8 and 16 concurrent Apache
servers: higher values are better.

2

1

2

4

8

8(diff)

OSDB-OLTP

Simultaneous OSDB-IR and OSDB-OLTP Instances on Xen

Figure 5: Performance of multiple instances of PostgreSQL
running OSDB in separate Xen domains. 8(diff) bars show performance variation with different scheduler weights.

of synchronous disk activity highlights a weakness in our current
disk scheduling algorithm causing them to under-perform.

4.4

Performance Isolation

In order to demonstrate the performance isolation provided by
Xen, we hoped to perform a “bakeoff” between Xen and other OSbased implementations of performance isolation techniques suchas resource containers. However, at the current time there appear
to be no implementations based on Linux 2.4 available for download. QLinux 2.4 has yet to be released and is targeted at providing
QoS for multimedia applications rather than providing full defensive isolation in a server environment. Ensim’s Linux-based Private
Virtual Server product appears to be the most complete implementation, reportedly encompassing control of CPU, disk, network andphysical memory resources [14]. We are in discussions with Ensimand hope to be able to report results of a comparative evaluation at
a later date.
In the absence of a side-by-side comparison, we present results
showing that Xen’s performance isolation works as expected, evenin the presence of a malicious workload. We ran 4 domains configured with equal resource allocations, with two domains runningpreviously-measured workloads (PostgreSQL/OSDB-IR and SPEC
WEB99), and two domains each running a pair of extremely antisocial processes. The third domain concurrently ran a disk bandwidthhog (sustained dd) together with a file system intensive workload
targeting huge numbers of small file creations within large directories. The fourth domain ran a ‘fork bomb’ at the same time asa virtual memory intensive application which attempted to allocate
and touch 3GB of virtual memory and, on failure, freed every page
and then restarted.
We found that both the OSDB-IR and SPEC WEB99 results were
only marginally affected by the behaviour of the two domains running disruptive processes — respectively achieving 4% and 2%
below the results reported earlier. We attribute this to the overhead of extra context switches and cache effects. We regard this as
somewhat fortuitous in light of our current relatively simple diskscheduling algorithm, but under this scenario it appeared to pro-Normalised Throughput

2.0
1.8
1.6
1.4
Linux
XenoLinux (50ms time slice)
XenoLinux (5ms time slice)

1.2
1.0
0

10

20

30

40

50

60

70

80

90 100 110 120 130

Concurrent Processes/Domains

Figure 6: Normalized aggregate performance of a subset ofSPEC CINT2000 running concurrently on 1-128 domains

on a single server is unlikely to be commonplace in our target application area, Xen copes relatively well: running 128 domains welose just 7.5% of total throughput relative to Linux.
Under this extreme load, we measured user-to-user UDP latency
to one of the domains running the SPEC CINT2000 subset. We
measured mean response times of 147ms (standard deviation 97ms).
Repeating the experiment against a 129th domain that was otherwise idle, we recorded a mean response time of 5.4ms (s.d. 16ms).
These figures are very encouraging — despite the substantial background load, interactive domains remain responsive.
To determine the cause of the 7.5% performance reduction, we
set Xen’s scheduling ‘slice’ to 50ms (the default value used by
ESX Server). The result was a throughput curve that tracked native
Linux’s closely, almost eliminating the performance gap. However, as might be expected, interactive performance at high load is
adversely impacted by these settings.

5.
vide sufficient isolation from the page-swapping and disk-intensive
activities of the other domains for the benchmarks to make good
progress. VMware Workstation achieves similar levels of isolation,
but at reduced levels of absolute performance.
We repeated the same experiment under native Linux. Unsurprisingly, the disruptive processes rendered the machine completely
unusable for the two benchmark processes, causing almost all the
CPU time to be spent in the OS.

4.5 Scalability
In this section, we examine Xen’s ability to scale to its targetof 100 domains. We discuss the memory requirements of runningmany instances of a guest OS and associated applications, and measure the CPU performance overhead of their execution.
We evaluated the minimum physical memory requirements ofa domain booted with XenoLinux and running the default set of
RH7.2 daemons, along with an sshd and Apache web server. The
domain was given a reservation of 64MB on boot, limiting the maximum size to which it could grow. The guest OS was instructed tominimize its memory footprint by returning all pages possible to
Xen. Without any swap space configured, the domain was able toreduce its memory footprint to 6.2MB; allowing the use of a swap
device reduced this further to 4.2MB. A quiescent domain is able tostay in this reduced state until an incoming HTTP request or periodic service causes more memory to be required. In this event, theguest OS will request pages back from Xen, growing its footprint
as required up to its configured ceiling.
This demonstrates that memory usage overhead is unlikely to
be a problem for running 100 domains on a modern server classmachine — far more memory will typically be committed to application data and buffer cache usage than to OS or application text
pages. Xen itself maintains only a fixed 20kB of state per domain,
unlike other VMMs that must maintain shadow page tables etc.
Finally, we examine the overhead of context switching between
large numbers of domains rather than simply between processes.
Figure 6 shows the normalized aggregate throughput obtained whenrunning a small subset of the SPEC CINT2000 suite concurrently
on between 1 and 128 domains or processes on our dual CPU server.
The line representing native Linux is almost flat, indicating thatfor this benchmark there is no loss of aggregate performance whenscheduling between so many processes; Linux identifies them all as
compute bound, and schedules them with long time slices of 50ms
or more. In contrast, the lower line indicates Xen’s throughput
when configured with its default 5ms maximum scheduling ‘slice’.
Although operating 128 simultaneously compute bound processes

RELATED WORK

Virtualization has been applied to operating systems both commercially and in research for nearly thirty years. IBM VM/370 [19,38] first made use of virtualization to allow binary support for legacy
code. VMware [10] and Connectix [8] both virtualize commodity
PC hardware, allowing multiple operating systems to run on a single host. All of these examples implement a full virtualization of(at least a subset of) the underlying hardware, rather than paravirtualizing and presenting a modified interface to the guest OS. As
shown in our evaluation, the decision to present a full virtualization, although able to more easily support off-the-shelf operating
systems, has detremental consequences for performance.
The virtual machine monitor approach has also been used by
Disco to allow commodity operating systems to run efficiently on
ccNUMA machines [7, 18]. A small number of changes had to bemade to the hosted operating systems to enable virtualized execution on the MIPS architecture. In addition, certain other changes
were made for performance reasons.
At present, we are aware of two other systems which take theparavirtualization approach: IBM presently supports a paravirtualized version of Linux for their zSeries mainframes, allowing large
numbers of Linux instances to run simultaneously. Denali [44],discussed previously, is a contemporary isolation kernel which attempts to provide a system capable of hosting vast numbers of virtualized OS instances.
In addition to Denali, we are aware of two other efforts to use
low-level virtualization to build an infrastructure for distributed
systems. The vMatrix [1] project is based on VMware and aims
to build a platform for moving code between different machines.
As vMatrix is developed above VMware, they are more concernedwith higher-level issues of distribution that those of virtualization
itself. In addition, IBM provides a “Managed Hosting” service, inwhich virtual Linux instances may be rented on IBM mainframes.
The PlanetLab [33] project has constructed a distributed infrastructure which is intended to serve as a testbed for the research anddevelopment of geographically distributed network services. The
platform is targeted at researchers and attempts to divide individual
physical hosts into slivers, providing simultaneous low-level accessto users. The current deployment uses VServers [17] and SILK [4]to manage sharing within the operating system.
We share some motivation with the operating system extensibility and active networks communities. However, when runningover Xen there is no need to check for “safe” code, or for guaranteed termination — the only person hurt in either case is the clientin question. Consequently, Xen provides a more general solution:
there is no need for hosted code to be digitally signed by a trusted

compiler (as in SPIN [5]), to be accompanied by a safety proof (aswith PCC [31]), to be written in a particular language (as in SafetyNet [22] or any Java-based system), or to rely on a particular middleware (as with mobile-agent systems). These other techniquescan, of course, continue to be used within guest OSes running over
Xen. This may be particularly useful for workloads with more transient tasks which would not provide an opportunity to amortize thecost of starting a new domain.
A similar argument can be made with regard to language-levelvirtual machine approaches: while a resource-managed JVM [9]should certainly be able to host untrusted applications, these applications must necessarily be compiled to Java bytecode and followthat particular system’s security model. Meanwhile, Xen can readily support language-level virtual machines as applications runningover a guest OS.

6. DISCUSSION AND CONCLUSION
We have presented the Xen hypervisor which partitions the resources of a computer between domains running guest operating
systems. Our paravirtualizing design places a particular emphasison performance and resource management. We have also describedand evaluated XenoLinux, a fully-featured port of a Linux 2.4 kernel that runs over Xen.

6.1 Future Work
We believe that Xen and XenoLinux are sufficiently complete to
be useful to a wider audience, and so intend to make a public releaseof our software in the very near future. A beta version is alreadyunder evaluation by selected parties; once this phase is complete, ageneral 1.0 release will be announced on our project page3 .
After the initial release we plan a number of extensions and improvements to Xen. To increase the efficiency of virtual block devices, we intend to implement a shared universal buffer cache indexed on block contents. This will add controlled data sharing toour design without sacrificing isolation. Adding copy-on-write semantics to virtual block devices will allow them to be safely shared
among domains, while still allowing divergent file systems.
To provide better physical memory performance, we plan to implement a last-chance page cache (LPC) — effectively a systemwide list of free pages, of non-zero length only when machine
memory is undersubscribed. The LPC is used when the guest OS
virtual memory system chooses to evict a clean page; rather than
discarding this completely, it may be added to the tail of the freelist. A fault occurring for that page before it has been reallocatedby Xen can therefore satisfied without a disk access.
An important role for Xen is as the basis of the XenoServer
project which looks beyond individual machines and is building
the control systems necessary to support an Internet-scale computing infrastructure. Key to our design is the idea that resource usage
be accounted precisely and paid for by the sponsor of that job —if payments are made in real cash, we can use a congestion pricing
strategy [28] to handle excess demand, and use excess revenues topay for additional machines. This necessitates accurate and timely
I/O scheduling with greater resilience to hostile workloads. We alsoplan to incorporate accounting into our block storage architecture
by creating leases for virtual block devices.
In order to provide better support for the management and administration of XenoServers, we are incorporating more thoroughsupport for auditing and forensic logging. We are also developing
additional VFR rules which we hope will allow us to detect andprevent a wide range of antisocial network behaviour. Finally, we
3

http://www.cl.cam.ac.uk/netos/xen

are continuing our work on XenoXP, focusing in the first instanceon writing network and block device drivers, with the aim of fully
supporting enterprise servers such as IIS.

6.2

Conclusion

Xen provides an excellent platform for deploying a wide variety of network-centric services, such as local mirroring of dynamic
web content, media stream transcoding and distribution, multiplayer
game and virtual reality servers, and ‘smart proxies’ [2] to provide aless ephemeral network presence for transiently-connected devices.
Xen directly addresses the single largest barrier to the deployment of such services: the present inability to host transient servers
for short periods of time and with low instantiation costs. By allowing 100 operating systems to run on a single server, we reduce theassociated costs by two orders of magnitude. Furthermore, by turning the setup and configuration of each OS into a software concern,
we facilitate much smaller-granularity timescales of hosting.
As our experimental results show in Section 4, the performanceof XenoLinux over Xen is practically equivalent to the performanceof the baseline Linux system. This fact, which comes from the careful design of the interface between the two components, means that
there is no appreciable cost in having the resource management facilities available. Our ongoing work to port the BSD and Windows
XP kernels to operate over Xen is confirming the generality of theinterface that Xen exposes.

Acknowledgments
This work is supported by ESPRC Grant GR/S01894/01 and by
Microsoft. We would like to thank Evangelos Kotsovinos, AnilMadhavapeddy, Russ Ross and James Scott for their contributions.

7.

REFERENCES[1] A. Awadallah and M. Rosenblum. The vMatrix: A network of virtual
machine monitors for dynamic content distribution. In Proceedingsof the 7th International Workshop on Web Content Caching andDistribution (WCW 2002), Aug. 2002.
[2] A. Bakre and B. R. Badrinath. I-TCP: indirect TCP for mobile hosts.
In Proceedings of the 15th International Conference on Distributed
Computing Systems (ICDCS 1995), pages 136–143, June 1995.
[3] G. Banga, P. Druschel, and J. C. Mogul. Resource containers: A new
facility for resource management in server systems. In Proceedingsof the 3rd Symposium on Operating Systems Design and
Implementation (OSDI 1999), pages 45–58, Feb. 1999.
[4] A. Bavier, T. Voigt, M. Wawrzoniak, L. Peterson, and
P. Gunningberg. SILK: Scout paths in the Linux kernel. Technical
Report 2002-009, Uppsala University, Department of Information
Technology, Feb. 2002.
[5] B. N. Bershad, S. Savage, P. Pardyak, E. G. Sirer, M. Fiuczynski,
D. Becker, S. Eggers, and C. Chambers. Extensibility, safety andperformance in the SPIN operating system. In Proceedings of the
15th ACM SIGOPS Symposium on Operating Systems Principles,
volume 29(5) of ACM Operating Systems Review, pages 267–284,
Dec. 1995.
[6] A. Brown and M. Seltzer. Operating System Benchmarking in the
Wake of Lmbench: A Case Study of the Performance of NetBSD on
the Intel x86 Architecture. In Proceedings of the 1997 ACM
SIGMETRICS Conference on Measurement and Modeling ofComputer Systems, June 1997.
[7] E. Bugnion, S. Devine, K. Govil, and M. Rosenblum. Disco:
Running commodity operating systems on scalable multiprocessors.
In Proceedings of the 16th ACM SIGOPS Symposium on Operating
Systems Principles, volume 31(5) of ACM Operating Systems
Review, pages 143–156, Oct. 1997.
[8] Connectix. Product Overview: Connectix Virtual Server, 2003.
http://www.connectix.com/products/vs.html.

[9] G. Czajkowski and L. Daynés. Multitasking without compromise: avirtual machine evolution. ACM SIGPLAN Notices, 36(11):125–138,
Nov. 2001. Proceedings of the 2001 ACM SIGPLAN Conference on
Object Oriented Programming, Systems, Languages andApplications (OOPSLA 2001).
[10] S. Devine, E. Bugnion, and M. Rosenblum. Virtualization system
including a virtual machine monitor for a computer with a segmented
architecture. US Patent, 6397242, Oct. 1998.
[11] K. J. Duda and D. R. Cheriton. Borrowed-Virtual-Time (BVT)
scheduling: supporting latency-sensitive threads in a general-purpose
scheduler. In Proceedings of the 17th ACM SIGOPS Symposium on
Operating Systems Principles, volume 33(5) of ACM Operating
Systems Review, pages 261–276, Kiawah Island Resort, SC, USA,
Dec. 1999.
[12] G. W. Dunlap, S. T. King, S. Cinar, M. Basrai, and P. M. Chen.
ReVirt: Enabling Intrusion Analysis through Virtual-Machine
Logging and Replay. In Proceedings of the 5th Symposium on
Operating Systems Design and Implementation (OSDI 2002), ACM
Operating Systems Review, Winter 2002 Special Issue, pages
211–224, Boston, MA, USA, Dec. 2002.
[13] D. Engler, S. K. Gupta, and F. Kaashoek. AVM: Application-levelvirtual memory. In Proceedings of the 5th Workshop on Hot Topics inOperating Systems, pages 72–77, May 1995.
[14] Ensim. Ensim Virtual Private Servers, 2003.
http://www.ensim.com/products/materials/
datasheet_vps_051003.pdf.
[15] K. A. Fraser, S. M. Hand, T. L. Harris, I. M. Leslie, and I. A. Pratt.
The Xenoserver computing infrastructure. Technical Report
UCAM-CL-TR-552, University of Cambridge, Computer
Laboratory, Jan. 2003.
[16] T. Garfinkel, M. Rosenblum, and D. Boneh. Flexible OS Support andApplications for Trusted Computing. In Proceedings of the 9thWorkshop on Hot Topics in Operating Systems, Kauai, Hawaii, May
2003.
[17] J. Gelinas. Virtual Private Servers and Security Contexts, 2003.
http://www.solucorp.qc.ca/miscprj/
s_context.hc.
[18] K. Govil, D. Teodosiu, Y. Huang, and M. Rosenblum. Cellular Disco:
Resource management using virtual clusters on shared-memory
multiprocessors. In Proceedings of the 17th ACM SIGOPS
Symposium on Operating Systems Principles, volume 33(5) of ACM
Operating Systems Review, pages 154–169, Dec. 1999.
[19] P. H. Gum. System/370 extended architecture: facilities for virtual
machines. IBM Journal of Research and Development,27(6):530–544, Nov. 1983.
[20] S. Hand. Self-paging in the Nemesis operating system. In
Proceedings of the 3rd Symposium on Operating Systems Design and
Implementation (OSDI 1999), pages 73–86, Oct. 1999.
[21] S. Hand, T. L. Harris, E. Kotsovinos, and I. Pratt. Controlling the
XenoServer Open Platform, April 2003.
[22] A. Jeffrey and I. Wakeman. A Survey of Semantic Techniques for
Active Networks, Nov. 1997. http://www.cogs.susx.
ac.uk/projects/safetynet/.
[23] M. F. Kaashoek, D. R. Engler, G. R. Granger, H. M. Briceño,R. Hunt, D. Mazières, T. Pinckney, R. Grimm, J. Jannotti, andK. Mackenzie. Application performance and flexibility on Exokernel
systems. In Proceedings of the 16th ACM SIGOPS Symposium on
Operating Systems Principles, volume 31(5) of ACM Operating
Systems Review, pages 52–65, Oct. 1997.
[24] R. Kessler and M. Hill. Page placement algorithms for large
real-indexed caches. ACM Transaction on Computer Systems,
10(4):338–359, Nov. 1992.
[25] S. T. King, G. W. Dunlap, and P. M. Chen. Operating System Support
for Virtual Machines. In Proceedings of the 2003 Annual USENIX
Technical Conference, Jun 2003.
[26] M. Kozuch and M. Satyanarayanan. Internet Suspend/Resume. In
Proceedings of the 4th IEEE Workshop on Mobile Computing
Systems and Applications, Calicoon, NY, Jun 2002.
[27] I. M. Leslie, D. McAuley, R. Black, T. Roscoe, P. Barham, D. Evers,
R. Fairbairns, and E. Hyden. The design and implementation of an
operating system to support distributed multimedia applications.

IEEE Journal on Selected Areas In Communications,14(7):1280–1297, Sept. 1996.
[28] J. MacKie-Mason and H. Varian. Pricing congestible network
resources. IEEE Journal on Selected Areas In Communications,13(7):1141–1149, Sept. 1995.
[29] L. McVoy and C. Staelin. lmbench: Portable tools for performance
analysis. In Proceedings of the USENIX Annual TechnicalConference, pages 279–294, Berkeley, Jan. 1996. Usenix
Association.
[30] J. Navarro, S. Iyer, P. Druschel, and A. Cox. Practical, transparent
operating system support for superpages. In Proceedings of the 5th
Symposium on Operating Systems Design and Implementation (OSDI
2002), ACM Operating Systems Review, Winter 2002 Special Issue,
pages 89–104, Boston, MA, USA, Dec. 2002.
[31] G. C. Necula. Proof-carrying code. In Conference Record of
POPL 1997: The 24th ACM SIGPLAN-SIGACT Symposium on
Principles of Programming Languages, pages 106–119, Jan. 1997.
[32] S. Oikawa and R. Rajkumar. Portable RK: A portable resource kernel
for guaranteed and enforced timing behavior. In Proceedings of theIEEE Real Time Technology and Applications Symposium, pages
111–120, June 1999.
[33] L. Peterson, D. Culler, T. Anderson, and T. Roscoe. A blueprint for
introducing disruptive technology into the internet. In Proceedings ofthe 1st Workshop on Hot Topics in Networks (HotNets-I), Princeton,
NJ, USA, Oct. 2002.
[34] I. Pratt and K. Fraser. Arsenic: A user-accessible gigabit ethernet
interface. In Proceedings of the Twentieth Annual Joint Conference of
the IEEE Computer and Communications Societies (INFOCOM-01),
pages 67–76, Los Alamitos, CA, USA, Apr. 22–26 2001. IEEE
Computer Society.
[35] D. Reed, I. Pratt, P. Menage, S. Early, and N. Stratford. Xenoservers:
accounted execution of untrusted code. In Proceedings of the 7thWorkshop on Hot Topics in Operating Systems, 1999.
[36] J. S. Robin and C. E. Irvine. Analysis of the Intel Pentium’s ability tosupport a secure virtual machine monitor. In Proceedings of the 9th
USENIX Security Symposium, Denver, CO, USA, pages 129–144,
Aug. 2000.
[37] C. P. Sapuntzakis, R. Chandra, B. Pfaff, J. Chow, M. S. Lam, and
M. Rosenblum. Optimizing the Migration of Virtual Computers. In
Proceedings of the 5th Symposium on Operating Systems Design and
Implementation (OSDI 2002), ACM Operating Systems Review,
Winter 2002 Special Issue, pages 377–390, Boston, MA, USA, Dec.
2002.
[38] L. Seawright and R. MacKinnon. VM/370 – a study of multiplicity
and usefulness. IBM Systems Journal, pages 4–17, 1979.
[39] P. Shenoy and H. Vin. Cello: A Disk Scheduling Framework for
Next-generation Operating Systems. In Proceedings of ACM
SIGMETRICS’98, the International Conference on Measurement andModeling of Computer Systems, pages 44–55, June 1998.
[40] V. Sundaram, A. Chandra, P. Goyal, P. Shenoy, J. Sahni, and
H.M.Vin. Application Performance in the QLinux Multimedia
Operating System. In Proceedings of the 8th ACM Conference on
Multimedia, Nov. 2000.
[41] D. Tennenhouse. Layered Multiplexing Considered Harmful. In
Rudin and Williamson, editors, Protocols for High-Speed Networks,
pages 143–148. North Holland, 1989.
[42] C. A. Waldspurger. Memory resource management in VMware ESX
server. In Proceedings of the 5th Symposium on Operating Systems
Design and Implementation (OSDI 2002), ACM Operating Systems
Review, Winter 2002 Special Issue, pages 181–194, Boston, MA,
USA, Dec. 2002.
[43] A. Whitaker, M. Shaw, and S. D. Gribble. Denali: Lightweight
Virtual Machines for Distributed and Networked Applications.
Technical Report 02-02-01, University of Washington, 2002.
[44] A. Whitaker, M. Shaw, and S. D. Gribble. Scale and performance inthe Denali isolation kernel. In Proceedings of the 5th Symposium on
Operating Systems Design and Implementation (OSDI 2002), ACM
Operating Systems Review, Winter 2002 Special Issue, pages
195–210, Boston, MA, USA, Dec. 2002.