Patent Application
20130024573
The present invention relates to the electrical, electronic and computer arts, and, more particularly, to cloud computing and the like.
Cloud computing is poised to become a disruptive technology and potentially change the way information technology (IT) services are provided and managed. While several models are emerging and quite a few definitions are being used to describe this landscape, the most typical usage scenario involves a user requesting a computing resource with a set of software and/or applications without requiring the user to invest in the infrastructure. An Infrastructure as a Service (IaaS) cloud with certain level of service supports such a model, wherein a virtual server is provided to the user as per the user's request. This approach also typically allows users to request applications; for example, DB2® database software and WebSphere® Application Server (WAS) software (registered marks of International Business Machines Corporation, Armonk, N.Y. USA) in addition to a central processing unit (CPU) with appropriate memory and disk sizing. It should be noted that DB2 database software and WAS software are non-limiting examples of database and application server software. A provider may offer a service catalog wherein a set, including an operating system (OS), middleware, and applications, may be made available to the users to choose from. A user may choose a set of software while requesting the virtual resource. In this scenario, the cloud provider pre-builds a set of images called virtual appliances that can be used to automatically provision a virtual server with the desired software image.
Principles of the invention provide techniques for scalable and efficient management of virtual appliance(s) in a cloud. In one aspect, an exemplary method includes the step of obtaining data representative of a set of requests for cloud computing services. The services are to be provided by a cloud having a plurality of base images. The requests specify requested subsets of the base images. Further steps include obtaining data representative of provisioning and de-provisioning costs associated with the plurality of base images; and pre-provisioning k composite virtual appliances including virtual appliance subsets of the base images, based on cost minimization, in accordance with the data representative of the set of requests and the data representative of the provisioning and de-provisioning costs.
As used herein, “facilitating” an action includes performing the action, making the action easier, helping to carry the action out, or causing the action to be performed. Thus, by way of example and not limitation, instructions executing on one processor might facilitate an action carried out by instructions executing on a remote processor, by sending appropriate data or commands to cause or aid the action to be performed. For the avoidance of doubt, where an actor facilitates an action by other than performing the action, the action is nevertheless performed by some entity or combination of entities.
One or more embodiments of the invention or elements thereof can be implemented in the form of a computer program product including a computer readable storage medium with computer usable program code for performing the method steps indicated. Furthermore, one or more embodiments of the invention or elements thereof can be implemented in the form of a system (or apparatus) including a memory, and at least one processor that is coupled to the memory and operative to perform exemplary method steps. Yet further, in another aspect, one or more embodiments of the invention or elements thereof can be implemented in the form of means for carrying out one or more of the method steps described herein; the means can include (i) hardware module(s), (ii) software module(s) stored in a computer readable storage medium (or multiple such media) and implemented on a hardware processor, or (iii) a combination of (i) and (ii); any of (i)-(iii) implement the specific techniques set forth herein.
Techniques of the present invention can provide substantial beneficial technical effects. For example, one or more embodiments may provide one or more of the following advantages:
less storage
less time to achieve the right configuration
less time to provision
These and other features and advantages of the present invention will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings.
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'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'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.
Service Models are as follows:
Software as a Service (SaaS): the capability provided to the consumer is to use the provider'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 email). 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 where the consumer is able to deploy and run arbitrary software, which can include operating system is 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
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, handheld 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
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
Referring now to
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.
As noted, cloud computing is poised to become a disruptive technology and potentially change the way IT services are provided and managed. While several models are emerging and quite a few definitions are being used to describe this landscape, the most typical usage scenario involves a user requesting a computing resource with a set of software and/or applications without requiring the user to invest in the infrastructure. An Infrastructure as a Service (IaaS) cloud with a certain level of service supports such a model, wherein a virtual server is provided to the user as per the user's request. This approach also typically allows users to request applications; for example, DB2® database software and WebSphere® Application Server (WAS) software (registered marks of International Business Machines Corporation, Armonk, N.Y., USA) in addition to a central processing unit (CPU) with appropriate memory and disk sizing. It should be noted that DB2 database software and WAS software are non-limiting examples of database and application server software. A provider may offer a service catalog wherein a set, including an operating system (OS), middleware, and applications, may be made available to the users to choose from. A user may choose a set of software while requesting the virtual resource. In this scenario, the cloud provider pre-builds a set of images called virtual appliances that can be used to automatically provision a virtual server with the desired software image. In one or more embodiments, the virtual appliances reside in virtualization layer 62.
A consideration in this case is how to support user requests without supporting a very large number of virtual appliances. Consider the case where there are N base images. If it is desired to support any possible combinations of images, it may be necessary to keep an exponential number of images, which is expensive from both the storage and the maintenance viewpoints. That is, if it is desired to support any possible combinations of N base images, 2N−1 virtual appliances would theoretically be required.
One or more embodiments provide an efficient approach towards a cost effective solution for automating users' requests for software provisioning with a significantly smaller number of virtual appliances than in current techniques (the catalog in current public clouds typically includes only monolithic appliances; i.e., “all or nothing” with no possibility of composition). One or more embodiments account for practical system constraints and requirements. A non-limiting exemplary model and solutions are described below.
One significant aspect of one or more embodiments is the dynamic tracking of user requests to identify a set of composite virtual appliances that should be kept, such that the overall cost for supporting provisioning is minimized while respecting the system's constraints and requirements. A formal description of one non-limiting exemplary model, according to one embodiment, follows.
Denote the base images (i.e., DB2, WAS, CentOS enterprise-class LINUX® operating system distribution, etc.) by a set {Ik}, k=1, . . . , N. LINUX is a registered mark of Linus Torvalds, Portland, OR 97219 USA. In this regard, as noted above, DB2 software and WAS software are non-limiting examples of database and application server software. Furthermore, CentOS is a non-limiting example of an operating system. Even further, database software, application server software, and operating systems are non-limiting examples of images.
In one or more embodiments, users request a subset from these base images. Request Ri includes a set of images from the base images. If a composite image that matches this subset is available a priori, then the cost to provision is minimized due to full automation as well as reduced latency. Whenever there is no exact match, the provider typically needs to customize (modify) the configuration of a chosen a priori composite image or to create a new composite image from several base images to support the requested subset.
In the example, every base image Ik has a provision (time and/or labor) cost Ai, meaning that if a provider has to install this image instead of booting from a virtual appliance, the provider will incur this provision cost; and a de-provision (time and/or labor) cost D1, meaning that if the provider has to uninstall this image from a composite install, this de-provision cost will be incurred. The skilled artisan can determine the provision and de-provision costs, for example, via benchmarking based on skill levels, typical required times, and associated hourly rates. Such benchmarking can in turn be based on prior experience and/or statistics (in some cases, the estimates may well be stochastic rather than deterministic). Furthermore, every piece of base software and the composite images have an associated disk size requirement, say, Si. In addition, every piece of base software has an update frequency Ui, meaning the number of updates that arrive every unit time (in general, a value greater than or equal to zero). When an update arrives, the image as well as any composite image containing that virtual image is invalidated, meaning it cannot be installed before patching. There a patching cost associated with the composite image.
An exemplary, non-limiting objective of one or more embodiments can be stated as follows: Given that the system has a finite amount of storage, and hence can only keep a handful of virtual appliances, and given also the aforementioned invalidation rate for the images, which set(s) should be built a priori such that the cost for provisioning can be minimized?
One or more embodiments account for the invalidation rate and the cost for provisioning and de-provisioning, to determine the dynamic set of images that should be kept to efficiently support user requests for composite software requests.
In a non-limiting example, a method, according to an aspect of the invention, includes two distinct phases.
Provision phase: In this phase, the provider examines the catalog of pre-built images and chooses the composite image that minimizes the provision cost, given the two operations (i.e., the install and uninstall costs in the case of customization) to satisfy the requested set. That is to say, the provider has received an individual request and is now picking which one of the virtual appliances is best suited (possibly with modification) to meeting the request. An exemplary detailed flow diagram will be presented below.
Catalog phase: In this phase, a decision is made as to which set of images should be pre-built so as to minimize the provision cost given the past history and prediction about the request workload. This is a dynamic process. In some instances, the catalog contents may initially be based on an estimate by a human expert. Then, as the system is used, the catalog is updated periodically based on the requests that have been processed.
With regard to a technique for determining the catalog, refer to the flow chart 400 of
Reference is made to the article “Fundamental Effects of Clustering on the Euclidean Embedding of Internet Hosts,” by Sanghwan Lee et al., presented at NETWORKING '07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, 2007, the complete contents of which are expressly incorporated herein by reference in their entirety for all purposes.
For illustrative convenience, reference to the two-dimensional case will continue, with attributes represented by X and Y Cartesian coordinates. Thus, in this example, draw k circles, based on an initial value of k, and find the corresponding k clusters. In one or more embodiments, the given parameters include k, as well as the radius of the circles. A least squares technique is used to assign each request to one of the clusters; effectively identifying k loci. In this regard, the distance between a request and the locus of a given cluster is proportional to error or cost. As is well known, in the least squares technique, the sum of the squares of the distances is minimized.
Thus, in step 404, determine the center for each cluster such that the distance from the chosen center to each request is minimized. In essence, what is being determined is which composite virtual appliances should be pre-provisioned to minimize overall cost. Here, in one or more embodiments, the distance is denoted by the total cost function. In at least some instances, this total cost function may include a weighted cost function including a weighted average of the provisioning cost, Ai, the de-provision cost, D1, and the cost associated with the update frequency U1. In some instances, human experts in the field can be used to select the weights.
In step 406, choose an appropriate size for k based on the storage Si and permissible catalog size. Recall that an initial value of k was selected prior to step 402. It will be appreciated that if k is too large, an excessive number of composite virtual appliances will be pre-provisioned and that if k is too small, excessive provisioning time will be required to meet requests. In step 406, k can be selected to comply with pertinent constraints such as the available storage capacity, taking into account the required time and cost to maintain multiple golden images.
In one or more embodiments, pertinent attributes, represented by distances, include the install cost, uninstall cost, and update cost. In a preferred embodiment, the distance vector represents the weighted average labor and time for installation, update, and un-installation. For example, a particular case might involve availability of 1 terabyte of total storage. A very small value of k might easily satisfy the storage constraint but the cost to provision in response to requests might be too great. Another pertinent factor is the degree of variation in requests. Higher variation implies larger values of k and conversely, more uniform requests imply lower values of k.
In step 408, update this computation of the catalog every periodic interval, where the periodicity can be chosen, for example, based on request frequency, among other factors. Decision block 408 depicts logical flow returning back to step 402 if the periodic interval has elapsed, as per the “YES” branch; otherwise, continue to check whether the periodic interval has elapsed, as per the “NO” branch. Steps 406 and 408 thus can include, for example, periodically selecting a new value of k in an iterative manner.
In one or more embodiments, while carrying out the logic of flow chart 400, include invalidation cost as a metric in determining the above-discussed weighting factor(s).
With regard to an on-line technique (a technique for dynamically updating the catalog based on data collected over time as well as projections of future requests) refer to the flow chart 500 of
Thus, in one or more embodiments, given that only a set of past requests are known, use the technique for determining the catalog, illustrated in the logic of flow chart 400 of
Attention should now be given to the exemplary system block diagram 600 of
For the avoidance of doubt, the system diagram 600 is typically only part of the entire cloud operations—only the specifics to provisioning a new compute node is discussed in the non-limiting example.
Given the discussion thus far, it will be appreciated that, in general terms, an exemplary method, according to an aspect of the invention, includes the step of obtaining data representative of a set of requests for cloud computing services. The services are to be provided by a cloud having a plurality of base images. The requests specify requested subsets of the base images. An additional step includes obtaining data representative of provisioning and de-provisioning costs associated with the plurality of base images. A further step includes pre-provisioning k composite virtual appliances including virtual appliance subsets of the base images, based on cost minimization, in accordance with the data representative of the set of requests and the data representative of the provisioning and de-provisioning costs. The subsets of the base images that are included in the virtual appliances arc designated as “virtual appliance subsets” to distinguish them from the subsets of the base images specified in the requests, designates as requested subsets.
In some instances, the pre-provisioning step is further based on request frequency and update frequency for said plurality of base images. In some cases, further steps include clustering the data representative of the set of requests into k clusters having radii such that all of the requests are within at least one of the clusters, as at 402, and, for each of the k clusters, determining a center thereof such that a distance from each of the requests in a given one of the clusters to the center thereof is minimized, as at 404. The distance specifies, for each of the requests in the given one of the clusters, a weighted total cost. The centers correspond to the composite virtual appliances.
As shown, for example, in step 408, in some instances, periodically repeat the step of obtaining the data representative of the requests and the pre-provisioning step as additional data representative of additional sets of requests for cloud computing services is obtained. It will be appreciated that in such cases, the repeated step of obtaining the data representative of the requests includes obtaining the additional data. In the most general case, the additional data can include actual data, as more actual requests are obtained, and/or predicted data, as explained in connection with
An additional step in at least some instances includes actually fulfilling future requests for cloud computing services using the k pre-provisioned composite virtual appliances (in at least some instances, as such appliances may be updated from time-to-time).
It is worth noting that in some instances, excessive pre-provisioning may be harmful, especially with a “buggy” piece of software which needs to be frequently updated. This is due to the fact that significant amounts of time may be wasted maintaining the pre-provisioned composite images, since, as the “buggy” software gets updated, each pre-provisioned composite image must also be updated. On the other hand, items that do not need frequent updates are good candidates to build into composite images.
Furthermore, given the discussion thus far, it will be appreciated that, in general terms, an exemplary system, according to an aspect of the invention, includes a memory; and at least one processor, coupled to said memory, and operative to carry out or otherwise facilitate any one, some, or all of the method steps described herein. In some cases, the system includes a plurality of distinct software modules, each of which is embodied in a non-transitory manner on a non-transitory computer-readable storage medium. The distinct software modules can include, for example, any of the blocks or sub-blocks in
It is worth mentioning that in one or more embodiments, k-centers can also be used to determine which of the pre-provisioned composite virtual appliances should be sued to fulfill a given request, during the provisioning phase. Simply see which one of the k-centers in the catalog the request attaches itself to.
Exemplary System and Article of Manufacture Details
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.
One or more embodiments of the invention, or elements thereof, can be implemented in the form of an apparatus including a memory and at least one processor that is coupled to the memory and operative to perform exemplary method steps.
One or more embodiments can make use of software running on a general purpose computer or workstation. With reference to
Accordingly, computer software including instructions or code for performing the methodologies of the invention, as described herein, may be stored in one or more of the associated memory devices (for example, ROM, fixed or removable memory) and, when ready to be utilized, loaded in part or in whole (for example, into RAM) and implemented by a CPU. Such software could include, but is not limited to, firmware, resident software, microcode, and the like.
A data processing system suitable for storing and/or executing program code will include at least one processor 16 coupled directly or indirectly to memory elements 28 through a system bus 18. The memory elements can include local memory employed during actual implementation of the program code, bulk storage, and cache memories 32 which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during implementation.
Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, and the like) can be coupled to the system either directly or through intervening I/O controllers.
Network adapters 20 may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
As used herein, including the claims, a “server” includes a physical data processing system (for example, system 12 as shown in
As noted, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon. Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. In the most general case, the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). However, one or more embodiments are particularly significant in the context of a cloud or virtual machine environment employing a hypervisor or the like. Reference is made back to
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that any of the methods described herein can include an additional step of providing a system comprising distinct software modules embodied on a computer readable storage medium; the modules can include, for example, any or all of the appropriate elements depicted in the block diagrams and/or described herein; by way of example and not limitation, any one, some or all of the modules/blocks and or sub-modules/sub-blocks (handlers 608, 610, 612 are non-limiting examples of sub-blocks/sub-modules) in
In any case, it should be understood that the components illustrated herein may be implemented in various forms of hardware, software, or combinations thereof; for example, application specific integrated circuit(s) (ASICS), functional circuitry, one or more appropriately programmed general purpose digital computers with associated memory, and the like. Given the teachings of the invention provided herein, one of ordinary skill in the related art will be able to contemplate other implementations of the components of the invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
