Advanced Resource Sharing
in the Cloud
Eiji Kawai
NICT

Cloud computing• Goal– Cost effectiveness– Scale‐out– Elasticity• Methodology– Virtualization of every computing resource• System elements (IaaS: Infrastructure as a Service)– Ex: processor
processor, memory,
memory storage
storage, network
network, …

• Middleware services (PaaS: Platform as a Service)– Ex: database, overlay communication, security, …

• Application services (SaaS: Software as a Service)– Ex: e‐mail, wordprocessor, accounting information system, …

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Sharing everythingService C
Service B
Service A– SharingSh i computing
ti resources amongusers, applications, and computing
systems– Flexible resource sharing tomaximize the statistical multiplexingis the key• Storage sharing (virtualization) is a
hot topic in data center networks– FC, iSCSI, FCoE, etc• Next step: memory sharing in cloud– Memory price is dropping sharply

Usaage (%)

100• Benefit of cloud computing isderived from statistical multiplexing

80
60
40
200036912 15 18 21 24Time

CPU

Bound tohosts

MemoryStorage
Virtualized

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3Three approaches
to large scale memory sharing• Virtual machine migration– Move a guest VM to a host with more free memory– Pro: Easy deployment– Con: High migration cost

• Explicit Shared memory– Programming with memory sharing API– Pro: High flexibility (programmability)– Con: High implementation cost and low manageability• Remote memory mapping– Import memory of a remote host into the local virtual memory space– Pro: High manageability– Con: High deployment cost (no de facto implementation)

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Virtualization of virtual memory• Our approach: mount remote memory as swap device– Physical memory is already virtualized in OS (VM: virtual memory)– Pro: High performance– Con: (straightforward) implementation in kernel VM layer is highly
difficultProcess

Process
ATA/SCSI

VM

Physicalmemory

Swap

PhysicalMemory

deviceNormal system

TCP
P/IP

TCP
P/IP

VM/FS

VM
PhysicalMemory

Extended system

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Leveraging LVM and iSCSI• System configuration is highly flexible, thanks to modern
LVM (logical volume management) mechanism– Dynamic attachment/detachment of remote memory linked tothe memory usage• iSCSI performance in high latency networks is well‐studied– Distributed cloud environment
Process
VM/FS

LVM

iSCSI

VM/FS

TCP/IP

Physical
MemoryiSCSI
Physical
Memory2009/12/16

TCP/IPAFICT20096Performance: sequential access (read)thhroughput (MB/s)

1000

seq. read (local)
seq. readd (remote)()seq. read (10G remote)100

102.3X‐3.3X faster
1010002009/12/16

2000

3000

Data size (MB)

4000

5000

AFICT20097

Performance: random access (read)thhroughput (MB/s)

1000

rand. read (local)
rand. read (remote)rand. read (10G remote)100

17.0x‐28.0x faster

1010.10

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1000

2000

3000

Data size (MB)AFICT2009

4000

5000

8

Summary• Memory sharing is a forthcoming technology tobe deployed in the cloud• We proposed a low‐cost memory sharing
mechanism with LVM and iSCSI• Future work
– Engineering iSCSI performance over long distantnetworks (including JP‐TH JGN2plus network!!)– Memory cluster management mechanisms
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Thank you

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