Abstract:
A shared resource system, method of optimizing resource allocation in real time and computer program products therefor. At least one client device includes an optimization agent monitoring resource usage and selectively suggesting changes to resource configuration for the client device. A management system, e.g., in a cloud environment selectively makes resource capacity available to client devices and adjusts resource capacity available to client devices in response to the optimization agent. Client devices and provider computers connect over a network. The client devices and provider computer pass messages to each other over the network.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention is related to shared resource allocation and more particularly to reconfiguring virtual machines for optimized resource allocation and minimized energy waste. 
     2. Background Description 
     For any modern organization acquiring and managing Information Technology (IT) is a major budgetary concern. Moreover, the local IT hardware is seldom used at full capacity. So to reduce IT infrastructure costs and waste, instead of acquiring physical hardware, organizations increasingly are sharing resources by replacing some local computers with virtual machines (VMs). Each VM provides a local virtual desktop and runs on a remote physical server. Each desktop has allocated capacity (e.g. disk space, processing resources and memory) and is configured (software stack and licenses) for its intended purpose and expected needs. A key problem to managing these VM desktops is determining optimal capacity and configuration to allocate to each VM. 
     A typical state of the art service provider allocates/places physical resources for each VM based primarily on provider system optimization, on workload predictions and on results from continuously monitoring VM resource usage. Over-allocation, wastes resources and energy and reduces the capacity available to other users. Under-allocation impairs the users Quality-of-Service (QoS). Preferably, adequate IT resources are allocated without waste, and while also maintaining the desktop user&#39;s QoS. 
     System designers have investigated user/usage profiling and feedback in an effort to further optimize and improve service provider efficiency. User/usage profiles have been generated and used, for example, to deliver targeted content such as user targeted advertisements. Those user profiles have been categorized, for example, through analysis of web usage or mobile browser activity to infer demographic data. User feedback can include reporting software failures and performance degradation; expressing satisfaction with, and improve the quality of provided web content and advertisements; and involve them in the process of classifying emails for spam prevention. 
     Users can assist administrators in better defining initial desktop configurations and optimizing initial VM placement. For example, a resource management system may provide users with options that change system demands, e.g., to optimize energy consumption and systems energy efficiency. Once placed, however, the provider does not consider user feedback, even for subsequent attempts to consolidate system workload or optimize system resource allocation. 
     Thus, there is a need for allowing users to provide feedback with respect to a current desktop configuration and capacity, and for allowing users to indicate willingness to update the current desktop configuration for more efficient use of resource, by reducing the desktop capacity; and more particularly, there is a need for reconfiguring virtual desktops in response to such feedback, for example, consolidating the desktops onto fewer servers, thereby reducing IT costs, and further, understanding whether the current desktop configuration is appropriate for each user according to different respective usage profiles. 
     SUMMARY OF THE INVENTION 
     A feature of the invention is reduced shared resource energy consumption; 
     Another feature of the invention is optimized allocation of shared resources in a cloud environment; 
     Yet another feature of the invention is that cloud environment users are allowed to adjust allocated resources on the fly, whenever the user&#39;s client device identifies resource excess that has been allocated for a particular user and/or when the user is unsatisfied with a current resource allocation. 
     The present invention relates to a shared resource system, method of optimizing resource allocation in real time and computer program products therefor. At least one client device includes an optimization agent monitoring resource usage and selectively suggesting changes to resource configuration for the client device. A management system, e.g., in a cloud environment selectively makes resource capacity available to client devices and adjusts resource capacity available to client devices in response to the optimization agent. Client devices and provider computers connect over a network. The client devices and provider computer pass messages to each other over the network. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The foregoing and other objects, aspects and advantages will be better understood from the following detailed description of a preferred embodiment of the invention with reference to the drawings, in which: 
         FIG. 1  depicts a cloud computing node according to an embodiment of the present invention; 
         FIG. 2  depicts a cloud computing environment according to an embodiment of the present invention; 
         FIG. 3  depicts abstraction model layers according to an embodiment of the present invention; 
         FIG. 4  shows an example of the target computing environment  70  for application to a preferred embodiment of the present invention; 
         FIG. 5  shows an example of a group profile table of user profiles maintained by the management system for the entire group of an organization of server users; 
         FIGS. 6A-B  show an example of client devices configured initially using the latest profile table defined by the management system; 
         FIG. 7  shows an example of how the management system optimizes VM desktop placement on the physical servers, implemented using existing dynamic resource placement and suitable data mining solutions; 
         FIG. 8A  shows a user interface or Graphical User Interface (GUI) on device desktop example during reconfiguration; 
         FIG. 8B  shows an example of the user using the desktop on device to requesting another profile. 
     
    
    
     DESCRIPTION OF PREFERRED EMBODIMENTS 
     It is understood in advance that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed and as further indicated hereinbelow. 
     Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. 
     Characteristics are as follows: 
     On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service&#39;s provider. 
     Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs). 
     Resource pooling: the provider&#39;s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter). 
     Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time. 
     Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service. Moreover, the present invention provides for client self-monitoring for adjusting individual resource allocation and configuration on-the-fly for optimized resource allocation in real time and with operating costs and energy use minimized. 
     Service Models are as follows: 
     Software as a Service (SaaS): the capability provided to the consumer is to use the provider&#39;s applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. 
     Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 
     Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources, sometimes referred to as a hypervisor, where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls). 
     Deployment Models are as follows: 
     Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises. 
     Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. 
     Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. 
     Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds). 
     A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes. 
     Referring now to  FIG. 1 , a schematic of an example of a cloud computing node is shown. Cloud computing node  10  is only one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, cloud computing node  10  is capable of being implemented and/or performing any of the functionality set forth hereinabove. 
     In cloud computing node  10  there is a computer system/server  12 , which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server  12  include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like. 
     Computer system/server  12  may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server  12  may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices. 
     As shown in  FIG. 1 , computer system/server  12  in cloud computing node  10  is shown in the form of a general-purpose computing device. The components of computer system/server  12  may include, but are not limited to, one or more processors or processing units  16 , a system memory  28 , and a bus  18  that couples various system components including system memory  28  to processor  16 . 
     Bus  18  represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnects (PCI) bus. 
     Computer system/server  12  typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server  12 , and it includes both volatile and non-volatile media, removable and non-removable media. 
     System memory  28  can include computer system readable media in the form of volatile memory, such as random access memory (RAM)  30  and/or cache memory  32 . Computer system/server  12  may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system  34  can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus  18  by one or more data media interfaces. As will be further depicted and described below, memory  28  may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention. 
     Program/utility  40 , having a set (at least one) of program modules  42 , may be stored in memory  28  by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules  42  generally carry out the functions and/or methodologies of embodiments of the invention as described herein. 
     Computer system/server  12  may also communicate with one or more external devices  14  such as a keyboard, a pointing device, a display  24 , etc.; one or more devices that enable a user to interact with computer system/server  12 ; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server  12  to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces  22 . Still yet, computer system/server  12  can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter  20 . As depicted, network adapter  20  communicates with the other components of computer system/server  12  via bus  18 . It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server  12 . Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc. 
     Referring now to  FIG. 2 , illustrative cloud computing environment  50  is depicted. As shown, cloud computing environment  50  comprises one or more cloud computing nodes  10  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  54 A, desktop computer  54 B, laptop computer  54 C, and/or automobile computer system  54 N may communicate. Nodes  10  may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment  50  to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices  54 A-N shown in  FIG. 2  are intended to be illustrative only and that computing nodes  10  and cloud computing environment  50  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
     Referring now to  FIG. 3 , a set of functional abstraction layers provided by cloud computing environment  50  ( FIG. 2 ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG. 3  are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: 
     Hardware and software layer  60  includes hardware and software components. Examples of hardware components include mainframes, in one example IBM® zSeries® systems; RISC (Reduced Instruction Set Computer) architecture based servers, in one example IBM pSeries® systems; IBM xSeries® systems; IBM BladeCenter® systems; storage devices; networks and networking components. 
     Examples of software components include network application server software, in one example IBM WebSphere® application server software; and database software, in one example IBM DB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter, WebSphere, and DB2 are trademarks of International Business Machines Corporation registered in many jurisdictions worldwide). 
     Virtualization layer  62  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients. 
     In one example, management layer  64  may provide the functions described below. Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal provides access to the cloud computing environment for consumers and system administrators. Service level management provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
     Workloads layer  66  provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and Mobile Desktop. 
       FIG. 4  shows an example of the target computing environment  70  for application to a preferred embodiment of the present invention with reference to the cloud environment of  FIGS. 1-3  with like features labeled identically. In the preferred computing environment  70  users at devices  54 A,  54 B interface through network messages with virtual machines  68  on networked servers  10 A- 10 N. Each virtual machine  68  includes an optimization agent  72  providing environment feedback for adjusting the virtual environment  74 ,  76 ,  78  for each virtual machine  68  to improve overall system  70  efficiency. Each virtual machine  68  includes an optimization agent  72  collecting resource usage information on virtualized hardware  74 , operating system(s)  76  and applications  78 , which the optimization agent  72  passes to the respective server,  10 A in this example. One software component  78  is a user interface for showing the user possible desktop reconfiguration options. The management system  64  in middleware cooperates with servers  10 A- 10 N allocating resources, modifying allocations in response to reconfigurations, and informing each VM of improved desktop reconfigurations. 
     Thus, the present invention allows users at networked devices  54 A,  54 B to receive and accept virtual desktop reconfiguration, and provide feedback during use for determining a more optimized resource placement. Each User may be informed of possible virtual desktop reconfigurations on-the-fly according to feedback and respective usage profiles. Accepting a reconfiguration optimizes desktop placement and VM configuration in real time to reduce over-allocated and/or underused/unused resources. Minimizing configuration inefficiency allows data center hardware consolidation and processing capacity reduction for reduced energy use; or, increasing the number of users supported by each server. Thus, the present invention reduces the per user average power consumption in a particular data center, thereby reducing Information Technology (IT) administration costs. Moreover, administrators can better understand resource usage profiles for improved capacity planning quality. 
       FIG. 5  shows an example of a user profile table  80  that the management system  64  maintains for the entire group of an organization of server users. In this example, the user profile table  80  includes a menu of profiles  82  and a list of users  84  indicating profile assignment. The profile menu  82  includes a set of selectable VM profiles  82 A- 82 M, that may be created initially by a system administrator, for example, and augmented or modified with use as described in more detail hereinbelow. Profiles in the profile menu  82  may also be updated using any suitable data mining technique, such as taught by Geng et al. “Interestingness measures for data mining: A survey”  ACM Computing Surveys  2006. The user list  84  includes an entry for each VM and the profile assigned to the respective VM, either the initially assigned profile or the profile assigned as a result of subsequent reconfiguration. It should be noted that although the profile menu  82  and the user list  84  are shown and treated as a unified table  80 , this is for simplicity of description only. It is understood that these two units may be, for example, separately and independently maintained. 
     In this example, each selectable VM profile  82 A- 82 M, which may be assigned to one or more VMs for requesting users, contains hardware  86 , software  88  and Quality-of-Service (QoS)  90  information. Typical hardware information  86  may indicate CPU, memory, disk, network, among other hardware requirements. Typical software information  88  may include a software systems stack and respective licenses. Typical QoS information  90  may include time to boot the desktop, or time to resume the desktop from standby mode. Each optimization agent  72  also maintains a local copy of the user profile table  80 . 
     As shown in  FIGS. 6A and 6B  and with reference to  FIGS. 4 and 5 , first the management system  64  configures  100  a VM  68  for each device  54 A,  54 B,  54 C, . . . ,  54 N requesting resources. In particular, the management system  64  assigns a profile  82 A- 82 M from profile menu  82  to the respective device  54 A,  54 B,  54 C, . . . ,  54 N in the user list  84 . Once the device  54 A,  54 B,  54 C, . . . ,  54 N is configured each respective optimization agent  72  manages two processes, a reconfiguration process  110  and a monitoring process  120 , reflected in the data flow of  FIG. 6A . In the reconfiguration process  110 , the optimization agent  72  waits  112  for updates to the profile table  80  from the management system  64 . If the management system  64  has provided an update  114 , the optimization agent  72  applies the update  116 . 
     In the monitoring process  120  the optimization agent  72  monitors  122  user activity and VM  68  behavior. The optimization agent  72  analyzes  124  data from monitoring to determine whether a reconfiguration suggestion  126  should be passed  128  to the user interface. Alternately, the user can suggest reconfiguring the desktop profile, e.g., if the user is dissatisfied with the current configuration. After making the suggestion  128 , or if no suggestion is made, the optimization agent checks the data to determine  130  whether to store  132  the behavior data in the server  10 A. Either after sending the behavior data  132  or if storing the behavior data is unnecessary, the optimization agent  72  returns to continue monitor  122  user activity and VM behavior. 
       FIG. 7  shows an example of how the management system  64  optimizes  140  VM desktop placement on the physical servers  10 A- 10 N, implemented using existing dynamic resource placement, for example. An example of dynamic resource placement is provided by Ferreto et al. “Server consolidation with migration control for virtualized data centers”  Future Generation Computer Systems,  2011. 
     VM optimization  140  begins when either, the user changes  142  the profile in response to a suggestion from the optimization agent  72  as shown in  FIG. 8A  or, the user initiates  144  a profile change as shown in  FIG. 8B . The management system  64  assigns a different profile in user list  84  to recon figure 146  the respective VM, preferably immediately, or after a preselected interval. Then, the management system  64  passes a notification  148  of the user list  84  changes to the user&#39;s device  54 A,  54 B and optimizes data center resources  150 , consolidating where possible. Finally, the management system  64  assesses the impact  152  of the user list  84  changes on resource allocation, e.g., determining power savings and/or added resource availability. The management system  64  can also adjust the profile menu  82  as needed based on VM usage and desktop behavior. 
       FIG. 8A  shows an example of a user interface or Graphical User Interface (GUI) on desktop  160  of client device  54  during reconfiguration in steps  126  and  128  of  FIG. 6A . A token  162  displayed on the desktop  160  indicates the current desktop configuration “A,” e.g., textually in the task bar  164  in this example, or iconically. After analyzing user activity and VM behavior  124  with the current desktop “A”  160 , a preferred optimization agent optimizes the configuration, tentatively reconfiguring to a more efficient, optimized desktop “B.” The optimization agent changes the task bar token  162  from “A” to “A-&gt;B” and suggests a profile change  126  to optimized desktop “B,” e.g., in a pop-up window  166 . 
     In this example, pop-up window  166  offers the user the option of exploring the advantages of migrating to optimized desktop “B.” The user can select more detailed information, e.g., with a mouse click or using a voice command. If more detailed information is selected, the optimization agent presents the user with an explanation of why the reconfiguration was suggested and possible impact of reconfiguring. If the user accepts the reconfiguration suggestion  128 , e.g., clicking on the task bar token  162 , the optimization agent provides feedback  142  to management system. The management system changes the profile designation for device  54  from “A” to “B” in the user list  84 . 
       FIG. 8B  shows an example of the user requesting another profile using the desktop  160  GUI on device  54  in  FIG. 8A  with like features labeled identically and with further reference to  FIG. 7 . In this example, the user has become dissatisfied with the current configuration “A,” and clicks  144  on another desktop token  170 . In this example, the current profile tagged with a minus sign, “−A” to indicate a requested change. The desktop  160  responds through the GUI, e.g., providing a pop-up window  172  that offers an opportunity to view alternate profiles. If the user responds in the positive, the desktop  160  may provide a list of profiles  82 A- 82 M in the menu  82  through the GUI, that the user can select. The desktop  160  may also indicate the impact of using each, e.g., the cost and energy consumption associated with each menu profile  82 A- 82 M. When the user selects a different configuration, the optimization agent returns  144  the selection to the management system. The management system uses the profile selection to reallocate resources and, optionally, refine the profile menu  82  to better meet future user resource needs and demands. 
     Thus advantageously, the present invention provides for client self-monitoring for adjusting individual resource allocation and configuration on-the-fly for optimized resource allocation in real time and with operating costs and energy use minimized. 
     While the invention has been described in terms of preferred embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims. It is intended that all such variations and modifications fall within the scope of the appended claims. Examples and drawings are, accordingly, to be regarded as illustrative rather than restrictive.