Patent Publication Number: US-11663028-B2

Title: Computer system providing virtual computing sessions through virtual delivery agent leasing with enhanced power savings and connectivity and related methods

Description:
RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 16/241,047 filed Jan. 7, 2019, which is hereby incorporated herein in its entirety by reference. 
    
    
     BACKGROUND 
     Traditionally, personal computers include combinations of operating systems, applications, and user settings, which are each managed individually by owners or administrators on an ongoing basis. However, many organizations are now using desktop virtualization to provide a more flexible option to address the varying needs of their users. In desktop virtualization, a user&#39;s computing environment (e.g., operating system, applications, and/or user settings) may be separated from the user&#39;s physical computing device (e.g., smartphone, laptop, desktop computer). Using client-server technology, a “virtualized desktop” may be stored in and administered by a remote server, rather than in the local storage of the client computing device. 
     There are several different types of desktop virtualization systems. As an example, Virtual Desktop Infrastructure (VDI) refers to the process of running a user desktop inside a virtual machine that resides on a server. VDI and other server-based desktop virtualization systems may provide personalized desktops for each user, while allowing for centralized management and security. Servers in such systems may include storage for virtual desktop images and system configuration information, as well as software components to provide the virtual desktops and allow users to interconnect to them. For example, a VDI server may include one or more hypervisors (virtual machine managers) to create and maintain multiple virtual machines, software to manage the hypervisor(s), a connection broker, and software to provision and manage the virtual desktops. 
     Desktop virtualization systems may be implemented using a single virtualization server or a combination of servers interconnected as a server grid. For example, a cloud computing environment, or cloud system, may include a pool of computing resources (e.g., desktop virtualization servers), storage disks, networking hardware, and other physical resources that may be used to provision virtual desktop or application sessions, along with additional computing devices to provide management and customer portals for the cloud system. 
     SUMMARY 
     A computing device may include a memory and a processor cooperating with the memory to generate connection leases for a plurality of client devices. The client devices may be configured to request virtual computing sessions from virtual delivery appliances in accordance with respective connection leases. Virtual delivery appliances within a first group may be configured to operate during off-peak hours, and virtual delivery appliances within a second group different than the first group may be configured not to operate during the off-peak hours. The processor may generate each connection lease to include at least one of the virtual delivery appliances from the first group. 
     In an example embodiment, each of the connection leases may comprise an ordered list of virtual delivery appliances, and each client computing device may be configured to sequentially request virtual computing sessions from the virtual delivery appliances in its respective ordered list from a highest order to a lowest order until a virtual computing session is established. More particularly, the lowest order virtual delivery appliance in the ordered list may be from the first group of virtual delivery appliances. In accordance with another example, each client computing device may have a respective user account associated therewith, and the processor may generate connection leases for client computing devices having a same user account associated therewith that share a same ordered list of virtual delivery appliances. 
     In one embodiment, each of the connection leases may further include at least one virtual delivery appliance from the second group. Furthermore, the virtual delivery appliances within the first group may be further configured to operate in an always-on mode. By way of example, 20% or less of the virtual delivery appliances may be assigned to the first group. 
     The virtual computing sessions may comprise virtual machine sessions, and the virtual delivery appliances may be configured to connect multiple client computing devices to each virtual machine session, for example. In other example implementations, the virtual computing sessions may comprise at least one of virtual desktop sessions and virtual application sessions. 
     A related method may include generating connection leases for a plurality of client devices at a computing device, with the client devices being configured to request virtual computing sessions from virtual delivery appliances in accordance with respective connection leases. Virtual delivery appliances within a first group may be configured to operate during off-peak hours, and virtual delivery appliances within a second group different than the first group may be configured not to operate during the off-peak hours. Furthermore, generating may comprise generating each connection lease to include at least one of the virtual delivery appliances from the first group. 
     A related non-transitory computer-readable medium may have computer-executable instructions for causing a processor to perform steps including generating connection leases for a plurality of client devices at a computing device, with the client devices being configured to request virtual computing sessions from virtual delivery appliances in accordance with respective connection leases. Virtual delivery appliances within a first group may be configured to operate during off-peak hours, and virtual delivery appliances within a second group different than the first group may be configured not to operate during the off-peak hours. Furthermore, generating may comprise generating each connection lease to include at least one of the virtual delivery appliances from the first group. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a network environment of computing devices in which various aspects of the disclosure may be implemented. 
         FIG.  2    is a block diagram of a computing device useful for practicing an embodiment of the client machines or the remote machines illustrated in  FIG.  1   . 
         FIG.  3    is a schematic block diagram of a computer system providing connections to virtual computing sessions using virtual delivery agent (VDA) leases having at least one VDA operating during off-peak hours. 
         FIG.  4    is a schematic block diagram of an example implementation of the system of  FIG.  3   . 
         FIG.  5 A  is a schematic block diagram illustrating a conventional approach to VDA assignment for connecting client computing devices to virtual computing sessions. 
         FIG.  5 B  is a chart of example lease assignments for respective user accounts for the VDAs of  FIG.  5 A , along with connection probabilities resulting from the given lease assignments. 
         FIG.  6 A  is a schematic block diagram illustrating an example grouping of available VDAs for an embodiment of the system of  FIG.  3   . 
         FIG.  6 B  is a chart of example lease assignments for respective user accounts for the VDAs of  FIG.  6 A , along with connection probabilities resulting from the given lease assignments. 
         FIG.  7    is a table comparing connection probabilities for example lease configurations with and without VDAs designated for operating during off-peak hours. 
         FIG.  8    is a flow diagram illustrating method aspects associated with the system of  FIG.  3   . 
     
    
    
     DETAILED DESCRIPTION 
     The present description is made with reference to the accompanying drawings, in which example embodiments are shown. However, many different embodiments may be used, and thus the description should not be construed as limited to the particular embodiments set forth herein. Like numbers refer to like elements throughout, and prime notation may be used to indicate similar elements in different embodiments. 
     As will be appreciated by one of skill in the art upon reading the following disclosure, various aspects described herein may be embodied as a device, a method or a computer program product (e.g., a non-transitory computer-readable medium having computer executable instruction for performing the noted operations or steps). Accordingly, those aspects may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. 
     Furthermore, such aspects may take the form of a computer program product stored by one or more computer-readable storage media having computer-readable program code, or instructions, embodied in or on the storage media. Any suitable computer readable storage media may be utilized, including hard disks, CD-ROMs, optical storage devices, magnetic storage devices, and/or any combination thereof. 
     Referring initially to  FIG.  1   , a non-limiting network environment  101  in which various aspects of the disclosure may be implemented includes one or more client machines  102 A- 102 N, one or more remote machines  106 A- 106 N, one or more networks  104 ,  104 ′, and one or more appliances  108  installed within the computing environment  101 . The client machines  102 A- 102 N communicate with the remote machines  106 A- 106 N via the networks  104 ,  104 ′. 
     In some embodiments, the client machines  102 A- 102 N communicate with the remote machines  106 A- 106 N via an intermediary appliance  108 . The illustrated appliance  108  is positioned between the networks  104 ,  104 ′ and may also be referred to as a network interface or gateway. In some embodiments, the appliance  108  may operate as an application delivery controller (ADC) to provide clients with access to business applications and other data deployed in a datacenter, the cloud, or delivered as Software as a Service (SaaS) across a range of client devices, and/or provide other functionality such as load balancing, etc. In some embodiments, multiple appliances  108  may be used, and the appliance(s)  108  may be deployed as part of the network  104  and/or  104 ′. 
     The client machines  102 A- 102 N may be generally referred to as client machines  102 , local machines  102 , clients  102 , client nodes  102 , client computers  102 , client devices  102 , computing devices  102 , endpoints  102 , or endpoint nodes  102 . The remote machines  106 A- 106 N may be generally referred to as servers  106  or a server farm  106 . In some embodiments, a client device  102  may have the capacity to function as both a client node seeking access to resources provided by a server  106  and as a server  106  providing access to hosted resources for other client devices  102 A- 102 N. The networks  104 ,  104 ′ may be generally referred to as a network  104 . The networks  104  may be configured in any combination of wired and wireless networks. 
     A server  106  may be any server type such as, for example: a file server; an application server; a web server; a proxy server; an appliance; a network appliance; a gateway; an application gateway; a gateway server; a virtualization server; a deployment server; a Secure Sockets Layer or Transport Layer Security (TLS) Virtual Private Network (SSL VPN) server; a firewall; a web server; a server executing an active directory; a cloud server; or a server executing an application acceleration program that provides firewall functionality, application functionality, or load balancing functionality. 
     A server  106  may execute, operate or otherwise provide an application that may be any one of the following: software; a program; executable instructions; a virtual machine; a hypervisor; a web browser; a web-based client; a client-server application; a thin-client computing client; an ActiveX control; a Java applet; software related to voice over internet protocol (VoIP) communications like a soft IP telephone; an application for streaming video and/or audio; an application for facilitating real-time-data communications; a HTTP client; a FTP client; an Oscar client; a Telnet client; or any other set of executable instructions. 
     In some embodiments, a server  106  may execute a remote presentation services program or other program that uses a thin-client or a remote-display protocol to capture display output generated by an application executing on a server  106  and transmit the application display output to a client device  102 . 
     In yet other embodiments, a server  106  may execute a virtual machine providing, to a user of a client device  102 , access to a computing environment. The client device  102  may be a virtual machine. The virtual machine may be managed by, for example, a hypervisor, a virtual machine manager (VMM), or any other hardware virtualization technique within the server  106 . 
     In some embodiments, the network  104  may be: a local-area network (LAN); a metropolitan area network (MAN); a wide area network (WAN); a primary public network  104 ; and a primary private network  104 . Additional embodiments may include a network  104  of mobile telephone networks that use various protocols to communicate among mobile devices. For short range communications within a wireless local-area network (WLAN), the protocols may include 802.11, Bluetooth, and Near Field Communication (NFC). 
       FIG.  2    depicts a block diagram of a computing device  100  useful for practicing an embodiment of client devices  102 , appliances  108  and/or servers  106 . The computing device  100  includes one or more processors  103 , volatile memory  122  (e.g., random access memory (RAM)), non-volatile memory  128 , user interface (UI)  123 , one or more communications interfaces  118 , and a communications bus  150 . 
     The non-volatile memory  128  may include: one or more hard disk drives (HDDs) or other magnetic or optical storage media; one or more solid state drives (SSDs), such as a flash drive or other solid-state storage media; one or more hybrid magnetic and solid-state drives; and/or one or more virtual storage volumes, such as a cloud storage, or a combination of such physical storage volumes and virtual storage volumes or arrays thereof. 
     The user interface  123  may include a graphical user interface (GUI)  124  (e.g., a touchscreen, a display, etc.) and one or more input/output (I/O) devices  126  (e.g., a mouse, a keyboard, a microphone, one or more speakers, one or more cameras, one or more biometric scanners, one or more environmental sensors, and one or more accelerometers, etc.). 
     The non-volatile memory  128  stores an operating system  115 , one or more applications  116 , and data  117  such that, for example, computer instructions of the operating system  115  and/or the applications  116  are executed by processor(s)  103  out of the volatile memory  122 . In some embodiments, the volatile memory  122  may include one or more types of RAM and/or a cache memory that may offer a faster response time than a main memory. Data may be entered using an input device of the GUI  124  or received from the I/O device(s)  126 . Various elements of the computer  100  may communicate via the communications bus  150 . 
     The illustrated computing device  100  is shown merely as an example client device or server, and may be implemented by any computing or processing environment with any type of machine or set of machines that may have suitable hardware and/or software capable of operating as described herein. 
     The processor(s)  103  may be implemented by one or more programmable processors to execute one or more executable instructions, such as a computer program, to perform the functions of the system. As used herein, the term “processor” describes circuitry that performs a function, an operation, or a sequence of operations. The function, operation, or sequence of operations may be hard coded into the circuitry or soft coded by way of instructions held in a memory device and executed by the circuitry. A processor may perform the function, operation, or sequence of operations using digital values and/or using analog signals. 
     In some embodiments, the processor can be embodied in one or more application specific integrated circuits (ASICs), microprocessors, digital signal processors (DSPs), graphics processing units (GPUs), microcontrollers, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), multi-core processors, or general-purpose computers with associated memory. 
     The processor  103  may be analog, digital or mixed-signal. In some embodiments, the processor  103  may be one or more physical processors, or one or more virtual (e.g., remotely located or cloud) processors. A processor including multiple processor cores and/or multiple processors may provide functionality for parallel, simultaneous execution of instructions or for parallel, simultaneous execution of one instruction on more than one piece of data. 
     The communications interfaces  118  may include one or more interfaces to enable the computing device  100  to access a computer network such as a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or the Internet through a variety of wired and/or wireless connections, including cellular connections. 
     In described embodiments, the computing device  100  may execute an application on behalf of a user of a client device. For example, the computing device  100  may execute one or more virtual machines managed by a hypervisor. Each virtual machine may provide an execution session within which applications execute on behalf of a user or a client device, such as a hosted desktop session. The computing device  100  may also execute a terminal services session to provide a hosted desktop environment. The computing device  100  may provide access to a remote computing environment including one or more applications, one or more desktop applications, and one or more desktop sessions in which one or more applications may execute. 
     Additional descriptions of a computing device  100  configured as a client device  102  or as a server  106 , or as an appliance intermediary to a client device  102  and a server  106 , and operations thereof, may be found in U.S. Pat. Nos. 9,176,744 and 9,538,345, which are incorporated herein by reference in their entirety. The &#39;744 and &#39;345 patents are both assigned to the current assignee of the present disclosure. 
     Turning to  FIG.  3    and the flow diagram  80  of  FIG.  8   , a system  30  providing client computing devices access to virtual computing sessions through connection leasing, yet with enhanced power saving capabilities and high connection probabilities, is now described. The system  30  illustratively includes a plurality of client computing devices  31   a ,  31   b  (e.g., smartphones, tablet computers, laptop computers, desktop computers, etc.), and a plurality of host computing devices  32   a - 32   c  each configured to provide virtual computing sessions  33   a - 33   c  for the client computing devices. Each host computing device  32   a - 32   c  illustratively includes a virtual delivery agent (VDA)  34   a - 34   c  associated therewith configured to connect the client computing devices with the virtual computing sessions. While only two client computing devices  31   a ,  31   b  and three hosting computing devices  32   a - 32   c  are shown in the illustrated example, it will be appreciated that any number of such computing devices may be used in different embodiments. Moreover, it will also be appreciated that the host computing devices  32   a - 32   c  and VDAs  34   a - 34   c  may be implemented in the cloud and/or on-premises in different embodiments. 
     By way of background, Citrix XenApp and XenDesktop are products which allow client computing devices to remotely access virtual computing sessions, such as virtual desktop sessions and virtual application sessions. In some embodiments, multiple virtual computing sessions may be hosted by a virtual machine. By way of example, the virtual application sessions may provide access to shared computing applications, including hosted applications, Web/Software as a Service (SaaS) applications, etc. Virtual desktop sessions may include both shared applications and hosted operating system components. In the case of XenApp and XenDesktop, a VDA enables connections to the applications and desktops, and is typically installed on the server/machine that runs the XenApp and/or XenDesktop virtual application/desktop sessions for the user (although it may be installed on a different machine in some implementations). The VDA enables the machines to register with delivery controllers and manage the connection to a user device. While the techniques described herein may be implemented using products such as XenApp and XenDesktop, for example, it will be appreciated that they may be implemented using other computing systems as well. 
     Connection leasing is a way to provide relatively high availability by authorizing client computing devices to connect to one of many VDAs via a signed lease document. However, one challenge is ensuring that the client computing devices can connect on nights and weekends and/or holidays (i.e., off-peak hours) when most VDAs are powered off to provide power savings. The present approach provides a technical solution to this problem of providing desired connection probabilities through VDA leases yet while still allowing for VDA power cycling during off-peak times to advantageously provide significant power savings to thereby improve the operation of a virtualized computing environment. 
     Beginning at Block  81 , the host computing devices  32   a - 32   c  provide virtual computing sessions  33   a - 33   c  for the client computing devices  31   a ,  31   b , at Block  82 . However, a first group of the VDAs (here including only the VDA  34   c ) is configured to operate during off-peak hours, while VDAs within a second group different than the first group (here the VDAs  34   a - 34   b ) are configured not to operate during the off-peak hours, at Block  83 . That is, the VDAs  34   a - 34   b  (and optionally the host computing devices  32   a ,  32   b  they run on) are configured to power off or run in a reduced power mode during off-peak hours, which may include weekdays outside of normal business hours (e.g., after 5 PM and before 9 AM), and all day on holidays and weekends, for example. Of course, off-peak hours may be selected differently for different entities or organizations in different embodiments. 
     Yet, the VDAs within the first group (i.e., the VDA  34   c  in the present example) are configured to run during some or all of the off-peak hours, and may optionally be run during some or all of the peak hours. That is, VDAs in the first group could be configured to operate (i.e., in a normal operational mode) only during off-peak hours, or they may be configured to also run during some or all of the peak hours. The VDAs  34   a - 34   c  connect the client computing devices  31   a ,  31   b  to the virtual computing sessions  33   a - 33   c  as requested in accordance with the VDA leases, and as the VDAs are available based upon whether they are in the first or second group and whether it is peak or off-peak hours, at Block  84 . The method of  FIG.  8    illustratively concludes at Block  85 . In an example embodiment, VDA leases may be assigned to the client computing devices  31   a ,  31   b  by brokers or other network administrator computers when the client computing device registers with the system  30 , for example. In one example configuration, the VDAs in the first group may be operated in an “always-on” fashion, providing full operational capabilities twenty-four hours a day. 
     Furthermore, the client computing devices  31   a ,  31   b  are configured to request virtual computing sessions from the VDAs  34   a - 34   c  in accordance with respective VDA leases, and each VDA lease includes at least one of the VDAs from the first group. In the illustrated example, the client computing device  31   a  is assigned a VDA lease including the VDAs  34   b  (second/peak group) and  34   c  (first/off-peak group), while the client computing device  31   b  is assigned a VDA lease including the VDAs  34   a  (second/peak group) and  34   c  (first/off-peak group). 
     Referring additionally to  FIG.  4   , in some implementations each of the VDA leases may include an ordered list of VDAs, with each client computing device  31   a ,  31   b  being configured to sequentially request virtual computing sessions from the VDAs  34   a - 34   c  in its respective ordered list from a highest order to a lowest order until a virtual computing session is established. Furthermore, each of the client computing devices  31   a ,  31   b  has a respective user account associated therewith, and in the present example the client computing devices have a same user account (User Account A) associated therewith, and they share the same ordered list of VDAs. For example, the client computing device  31   a  could be User A&#39;s laptop computer, while the client computing device  31   b  is User A&#39;s smartphone, etc. 
     In the present case, the ordered list of VDAs within the VDA lease includes, in order from highest ranked to lowest ranked: (1) VDA  34   a  (peak only); (2) VDA  34   b  (peak only); and (3) VDA  34   c  (always-on). Thus, in this example, the client computing devices  31   a ,  31   b  attempt to establish virtual computing sessions with the VDA  34   a , and if that is unsuccessful then with VDA  34   b , and if that is unsuccessful then finally with VDA  34   c . This is the case shown in the illustrated example, in which the last VDA  34   c  in the ordered list connects the client computing device  31   a  with a virtual computing session  33   c . This is the scenario that would occur during off-peak hours (when the VDAs  34   a - 34   b  are powered down or in a low power state), or during peak hours when the VDAs  34   a - 34   b  are overloaded, a connection is down, etc. 
     Note that there is at least one peak only VDA (here the VDAs  34   a ,  34   b ) in the ordered list, and at least one always-on VDA (here the VDA  34   c ), which in this example is positioned at the end of the ordered list. Positioning the off-peak/always-on VDA at the end of the ordered list may be advantageous in that it provides a more even distribution of processing resources over time, as the peak only VDAs  34   a ,  34   b  will receive more traffic during peak hours, and the always-on VDA  34   c  will receive more traffic during off-peak hours. However, it will be appreciated that the off-peak/always-on VDAs need not be positioned at the end of the ordered list in all embodiments. Moreover, any number of VDAs from the peak/off-peak groups may be included in the VDA leases in different embodiments. It should also be noted that different VDA leases (with different ordered lists) may be assigned to different user accounts, which provides a passive load balancing approach since different client computing devices will initially look to different VDAs for a virtual computing session. 
     Further details on connecting client computing devices to virtual computing sessions through VDAs using an ordered list approach are set forth in application Ser. No. 16/194,823 filed Nov. 20, 2018, now U.S. Pat. No. 11,115,478 which is also assigned to the present Applicant and is hereby incorporated herein in its entirety by reference. 
     The foregoing will be further understood with reference to various implementation examples demonstrating the enhanced connection probabilities that may be obtained using the above-described VDA leasing approach. Before describing the examples, the following background on typical approaches for brokering virtual computing sessions is now provided. The brokering of a pooled desktop is typically achieved with a probabilistic approach to guarantee a certain level of availability (i.e., a successful connection to a published desktop), for instance three nines (99.999%), four nines (99.9999%), etc. In this context, this is why a Connection Lease (CL) contains multiple VDAs. 
     Upon request to connect to a pooled desktop, in the case of the Citrix Workspace App (CWA), it will try to connect to the VDAs from the CL list of VDAs, one-by-one until a VDA is available (meaning powered on and not in use). When the end-user launches a desktop (from a Delivery Group containing pooled machines), the CWA will attempt to connect to a VDA by doing a quick ICA/CGP ping to check if it is available. If not, the CWA will go to the next one in the list of VDAs and so on. For cost reasons, only a subset of the available VDAs are typically powered on (and idle) at a specific time—taking advantage of the XenApp/XenDesktop Smart Scale Feature. Typically, customers may power on only 10-20% of available VDAs on nights and weekends, when usage is low. 
     In such a scenario, if we distribute VDAs evenly in connection leases, we can calculate the probability of connecting successfully. Assuming the probability for the VDAs in the CL list to be available is P a , then the probability to connect successfully to a VDA (by trying successively) is defined by the following recurrence relation (where n is the number of VDAs to try to connect to):
 
 P   n+1   =P   n +(1− P   n )× P   a ,
 
With P 1 =P a .
 
This can be changed to:
 
 P   n+1   =P   n ×(1− P   a )+ P   a ,
 
which resolves to:
 
 P   n =1−(1− P   a ) n .
 
A quick calculation shows how many VDAs (=n) are required in the CL list to guarantee two nines, three nines, etc. probability to connect successfully to a VDA. The following table assumes that only 20% of the available VDAs are powered on (and available/idle), which translates to P a =0.2
 
                                             Number of VDAs   Probability of finding a VDA to connect to                                                    1   0.2           11   0.914101           21   0.990777           31   0.999010           42   0.999915           52   0.999991                        
It will be appreciated that achieving even three 9&#39;s reliability requires a large number of VDAs in every lease (i.e., 30+). This could have a large impact on performance as leases would be large, and the CWA may have to try many connections before succeeding.
 
     An example of the typical approach to issuing leases in a system  50 A with twenty available VDAs, all having an equal probability of being powered on, and the VDAs being distributed evenly to the leases, is shown in  FIG.  5 A  and the associated chart  50 B of  FIG.  5 B . This results in a 20% probability for each VDA of being powered on at any given time. For the case of four users, each user will have approximately a 95% connection probability. 
     Instead of assuming that all VDAs have the same probability of being powered on, the present approach pre-selects those that will remain on during off-peak hours (or always-on). Continuing with the above example, the 20% of VDAs that stay powered on during nights and weekends may advantageously be selected ahead of time. Then, rather than distributing VDAs evenly in the leases, the leases are made up of a mix of VDAs powered on during peak periods (to ensure adequate load balancing during high-usage periods), and also VDAs from the preselected 20% (to ensure availability during low-usage periods), as noted above. Of course, different percentages of off-peak/always-on VDAs may be used in different embodiments. 
     Turning now to  FIGS.  6 A- 6 B , an example implementation of a system  60 A using the present approach where 10% of the available VDAs are pre-selected for operations during off-peak hours is now described. More particularly, in this example VDAs  1 - 18  are pre-selected for peak only operation, while the VDAs  19 - 20  (i.e., 2 of the available 20 VDAs, or 10%) are pre-selected for off-peak operation (here always-on operation). As described above, when issuing leases, one of the always-on VDAs is included in every user&#39;s lease, as shown in the chart  60 B of  FIG.  6 B . In the peak only group, there is &lt;1% probability of each VDA being powered on at a given time, but in the always-on group there is &gt;99% probability of these two VDAs (VDA  19  and  20 ) being powered on at any given time. As seen in  FIG.  6 B , the result is that for each user&#39;s VDA lease, there is a &gt;99% probability that the user will be connected to a virtual computing session by including one of the always-on VDAs in the lease, a 4%+ improvement over the approach noted above with the same number of VDAs and users but no pre-selection of the always-on VDAs. Of course, it will be appreciated that more always-on VDAs could be designated and assigned to user leases to increase the probability of connection even higher, but at the expense of some power savings, so the appropriate amount of VDAs to be pre-selected for a given application may be different. As a general guide, 20% or less of the available VDAs may be pre-selected for off-peak operation in a typical application, but a higher percentage may be chosen in some cases as desired. 
     The present approach to connection leasing plus power management also advantageously applies to pooled VDI (i.e., one user per VM) as well as RDS workloads (multiple users per VM). With RDS, configurations are more complicated as multiple users can share the same VM (up to a limit), so a simulation was performed to validate the effectiveness of the present approach. The results of the simulation are shown in the table  70  of  FIG.  7   . Assuming 20 VDAs capable of handling 10 users each (for a total of 200 users), a 10% idle pool, and 5 VDAs in a lease, the probability of connection with no pre-selected always-on VDAs is 95.5%, but with a single pre-selected always-on VDA in each lease the probability rises to 97.2%. Similarly, the average number of connection attempts changes from 1.27 to 1.41, and the load balancing unevenness changes from 7.26 users to 7.03 users. 
     It will therefore be appreciated that, without increasing the number of VDAs in a lease, the present approach provided for nearly half the connection failure rate, improved load balancing, and only caused a slight increase in connection time due to a higher number of connection attempts before finding an unloaded VDA. As noted above, in larger environments, it would also be possible to include more than one always-on VDA in leases to further increase connection probability. 
     Many modifications and other embodiments will come to the mind of one skilled in the art having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is understood that the foregoing is not to be limited to the example embodiments, and that modifications and other embodiments are intended to be included within the scope of the appended claims.