Patent Application
20050234937
1. Field of the Invention
This invention relates to arts for dynamic management of networked computing resources, and especially to technologies for grid computing.
2. Description of the Related Art
In the 1990's, the communications standardization between wide ranges of systems propelled the Internet explosion. Based upon the concept of resource sharing, the latest evolutionary technology is grid computing.
Grid computing is an emerging technology that utilizes a collection of systems and resources to deliver qualities of services. It is distributed computing at its best, by creating a virtual self-managing computer, the processing for which is handled by a collection of interconnected heterogeneous systems sharing different combinations of resources. In simple terms, grid computing is about getting computers to work together, and allowing businesses, or grid participants, to optimize available resources.
The framework to grid computing is large scale resource sharing, which exist within multiple management domains, typically involving highly parrallelized applications connected together through a communications medium, and organized to perform one or more requested jobs simultaneously. Each grid resource's characteristics can include, but are not limited, to processing speed, storage capability, licensing rights, and types of applications available.
Grid computing's architecture is defined in the Open Grid Services Architecture (“OGSA”), which includes a basic specification Open Grid Services Infrastructure (“OGSI”).
Using grid computing to handle computing jobs of all sizes, and especially larger jobs such as enterprise processes, has several advantages. First, it exploits underutilized resources on the grid. For example, if a financial services company suddenly encounters a 50% increase in stock trade transactions during a 30-minute time period, using a traditional systems process, the company would face an increase in network traffic, latent response and completion time, bottleneck in processing and even overload on its resources due to its limited or fixed computational and communications resources.
In a similar situation, however, grid computing can adjust dynamically to meet the changing business needs, and respond instantly to stock transaction increase using its network of unused resources. For example, a grid computing system could run an existing stock trading application on four underutilized machines to process transactions, and deliver results four times faster than the traditional computing architecture. Thus, grid computing provides a better balance in resource utilization and enables the potential for massive parallel CPU capacity.
Second, because of its standards, grid computing enables and simplifies collaboration among many resources and organizations from a variety of vendors and operators. For instance, genome research companies can use grid computing to process, cleanse, cross-tabulate and compare massive amounts of data, with the jobs being handled by a variety of computer types, operating systems, and programming languages. By allowing the files or databases to span across many systems, data transfer rates can be improved using striping techniques that lead to faster processing giving the companies a competitive edge in the marketplace.
Third, grid computing provides sharing capabilities that extends to additional equipment, software, services, licenses and others. These virtual resources provide uniform interoperability among heterogeneous grid participants. Each grid resource may have certain features, functionalities and limitations. For example, a particular data mining job may be able to run on a DB2 server, but may not compatible to be processed on an Oracle server. So, the grid computing architecture selects a resource which is capable of handling each specific job.
Fourth, the grid can offer more advanced resource load balancing. A relatively idle machine may receive an unexpected peak job, or if the grid is fully utilized, priorities may be assigned to better execute the number of requested jobs. By using a Grid Management System (“GMS”) scheduler, a grid can provides excellent infrastructure for brokering resources.
International Business Machines (“IBM”) has pioneered the definition and implementation of grid computing systems. According to the IBM architecture, Service Level Agreements (“SLAs”) are contracts which specify a set of client-driven criterion directing acceptable execution parameters for computational jobs handled by the grid. SLA parameters may consist of metrics such as execution and response time, results accuracy, job cost, and storage and network requirements. Typically, after job completion, an asynchronous process which is frequently manual is performed to compare actual completion. In other words, companies use SLAs to ensure all accounting specifics such as costs incurred and credits obtained conforms to the brokered agreements.
The relationship between a submitting client and grid service provider is that of a buyer (client) and a seller (grid vendor). Currently, there are some public domains for clients to manually rate vendors based on past performances. However, these ratings are more subjective than objective, and rating criteria differs from each vendor. Furthermore, rating systems that have no consistent guidelines often produce accidental or purposeful skewing of results. Therefore, ambiguity, overrating or underrating often occurs.
Because current grid computing resource selection and scheduling processes do not have access to the results of the SLA compliance analysis or manually-created rating results, automated processes to fully utilize compliant resources, and to avoid use of non-compliant resources or historically under-performing resources to improve resource allocation and utilization is not possible. In addition, improved compliance with client requirements is difficult to ensure, and the SLA compliance analysis process remains manual, requiring tedious repetitive verifications to ensure contracts are met and customer requirements fulfilled.
Therefore, there exists a need in the art for a means to automatically and consistently rate the performance of grid computing resources, to facilitate better selection and scheduling of grid resources and jobs assigned to those resources, and to ensure compliance with client-driven performance requirements such as Service Level Agreements.
The following detailed description when taken in conjunction with the figures presented herein present a complete description of the present invention.
This invention entails a grid service provider vendor rating system. This grid resource rating system will collect and display empirical data reflecting each vendor's actual performance against SLA, as nominally negotiated in an automated proposal process. The statistical data will be compiled into a data repository such as a database and allow organizations such as vendors, clients and new customers to access and improve internal process as needed based on the comparative figures.
Our grid service provider vendor rating system is both systematic and automated. Collected performance data is used to automatically generate ratings relative to Service Level Agreement (“SLA”) criteria, which enables clients, vendors, or the grid management processes to select resources and delegate jobs to those resources for improved compliance to SLA requirements and objectives. Furthermore, the new rating system applies a standard format to each grid vendor, and tracks SLA compliance, in our preferred embodiment. With the performance data collected and consistently and fairly analyzed, powerful reports can be produced for clients, vendors, and grid management administrators, as well.
The following definitions will be employed throughout this disclosure:
As previously discussed, IBM has pioneered the development of systems, architectures, interfaces, and standards for open grid computing. As grid computing is relatively new in the field of computing, we will first provide an overview of grid computing concepts and logical processes. Additional information regarding grid computing in general is publicly available from IBM, several other grid computing suppliers and developers, a growing number of universities, as well as from appropriate standards organizations such as the Open Grids Computing Environment (“OGCE”) consortium. The following description of grid computing uses a generalized model and generalized terminology which can be used equally well to implement the invention not only in an IBM-based grid environment, but in grid environments comprised of systems and components from other vendors, as well.
Turning to
Once the GMS determines a specific vendor(s) (38, 39, 300) to which the job will be assigned (or among which the job will be divided), requests are sent to the selected grid resources, such as Server 1 (38). Server 1 (38) would then process the job as required, and would return job results, such as a terrorist name list, back to the requesting client (53), such as the FBI analyst, via the communications network (51).
A Job/Grid Scheduler (“JGS”) (34) retrieves each pending job from the inbound job-queue (33), verifies handling requirements against one or more SLA (305) to determine processing requirements for the job, and then selects which server or servers (28, 29, 300) to assign to process the job (32). In this illustration, Server 2 (39) has been selected, so the job (32) is transferred to Server 2′ job queue (36) to be processed when the server becomes available (immediately if adequate processing bandwidth is already available). Some servers may handle their job queues in an intelligent manner, allowing jobs to have priority designation which allows them to be processed quicker or sooner than earlier-received, lower priority jobs.
Eventually, the assigned server completes the job and returns the results (301) to a Job Results Manager (“JRM”) (302). The JRM can verify job completion and results delivery (303) to the client application (31), and can generate job completion records (304) as necessary to achieve billing and invoice functions.
Turning now to
Through consideration of these factors regarding the grid resources, and in combination with the SLA client requirements, the JGS can select one or more appropriate grid resources to which to assign each job. For example, for high-priority jobs which require immediate processing, the JGS may select a resource which is immediately available, and which provides the greatest memory and processing bandwidth. For another job which is cost-sensitive but not time critical, the JGS may select a resource which is least expensive without great concern about the current depth of the queue for handling at that resource.
Grid Computing Environment Enhanced with Our Grid Vendor Rating System
As previously discussed, the present invention may be alternately realized in conjunction with a wide variety of grid computing products, resources, and clients, and is especially well suited for implementation with the IBM grid environment.
When a client (53) submits a job to the grid, the client may optionally access the Grid Vendor Rating Table (63) to review comparative and historical performance data based on client preferences such as cost, completion time, response time, availability and level of security. Thus, a client may enhance its job request to specify or request handling by a specific resource or set of resources. As the Grid Vendor Rating Table is dynamically generated and updated, the client's request become a time-relevant factor in the client's job requirements. Vendors who are aware of the availability of this table to the clients will be motivated to provide systems and resources which consistently perform to specification to increase job flow to their servers, thereby enhancing the overall performance of the grid.
According to another aspect of the present invention, the Job/Grid Scheduler is provided access to the Grid Vendor Rating Table (63) to enhance its ability to select resources which not only appear to be capable of handling the job according to the resources characteristics and the client SLA, but also according to each resource's historical performance.
In a further enhanced embodiment of the present invention, the Grid Vendor Rating Table(s) are available to both the client and the JGS such that both entities can select and screen resources which may or may not perform as desired or expected. Separate tables (not shown) may be maintained for each client, each resource, and for the JGS, allowing a variety of prioritization and factor weighting schemes to be employed to further enhance the selection process.
Grid Vendor Rating Table Generation
Our rating tables are generated by our Grid Resource Rating Logic (“GRRL”) (62) based upon data gathered from a number of potential sources. Ideally, all sources are used to generate the table, but in alternate embodiments, some sources may be eliminated or estimated.
The rating logic (62) obtains real-time data from grid resources (54) in self-reported job statistics (61), as well as statistics (45) reported from the Results Manager. Preferably, accounting information (34) may also be received by the rating logic (62) to allow it to include cost-to-performance considerations in the rating process.
The GRRL (62) automatically compares job processing data for each job and each resource against related SLA criterion to determine if contractual agreements were met. A Grid Vendor Rating Table (43) is created containing the results of the analysis (or updated to contain the results of the most recent analysis), such as the example table shown in
As shown in
Further, the overall vendor rating (27) is preferably determined either by an equal rating approach for all of the individual analysis results, or by applying a weighting scheme to the individual analysis results in order to prioritize certain performance characteristics as needed according to a client's requirements, or according to a grid performance objective. For example, a particular client may always prefer accuracy over cost and timeliness, and as such, the overall ratings for that client's table(s) may place greater weight on the accuracy individual analysis results when determining an overall rating for a vendor. In another example, a particular grid may be advertised or touted as a high-speed grid designed especially for time-critical jobs, and as such, the rating table(s) for that grid may place greater weight on the on time performance individual analysis results.
Other analyses, table formats, and fields within the table may optionally include:
Turning now to
Initially, a client establishes (1) its own set of business requirements, such as desired completion time within 24 hours with high level of security. Then, an SLA is generated (2) based on client's business requirements. The SLA agreement is then negotiated (3), preferably via a virtual Request for Proposal process, which replaces the previous manual processes for RFP submission and response.
Following establishment of an SLA, the client's job is submitted (4) and SLA monitoring begins, which tracks vendor performance statistics as previously described. When a job completes, the SLA monitoring also stops (5). The job results are compared against SLA (6), including consideration of resource self-reported statistics as previously described, to check if it meets the SLA requirements (7).
Each field of the job results is considered individually, such as a bank account statement having ending balance, average daily balance, interest accrued, and fees charged fields. If a result field meets the SLA requirement, a high score such as 100% is assigned (9) to that field. If a discrepancy is detected in the result field (e.g. accuracy was low, format was incorrect, result was out of range, etc.), then a less-than-optimal score is assigned to that field. The individual field score(s) are then saved to an intermediate table (11), and remaining job fields are processed similarly (12) until all job results fields are considered and scored.
Then, overall ratings for all fields are considered, as well as other job-specific performance information (e.g. was job completed within allowed time limits, was the cost of the job met, etc.), and a Grid Vendor Rating Table is yielded.
Any number of statistical and/or logical methods may be applied to generate the individual field scores, as indicated by the type of information and data. Likewise, a wide variety of methods for generating overall ratings of various times, as previously outlined, may be employed to generate the detailed contents of the Grid Vendor Rating table.
Computing Platform Suitable for Realization of the Invention
The invention, in one available embodiment, is realized as a feature or addition to software products, such as IBM's grid computing products, for execution by well-known computing platforms such as personal computers, web servers, and web browsers.
As the computing power, memory and storage, and communications capabilities of even portable and handheld devices such as personal digital assistants (“PDA”), web-enabled wireless telephones, and other types of personal information management (“PIM”) devices, steadily increases over time, it is possible that the invention may be realized in software for some of these devices, as well.
Therefore, it is useful to review a generalized architecture of a computing platform which may span the range of implementation, from a high-end web or enterprise server platform, to a personal computer, to a portable PDA or web-enabled wireless phone.
Turning to
Many computing platforms are also provided with one or more storage drives (79), such as a hard-disk drives (“HDD”), floppy disk drives, compact disc drives (CD, CD-R, CD-RW, DVD, DVD-R, etc.), and proprietary disk and tape drives (e.g., Iomega Zip™ and Jaz™, Addonics SuperDisk™, etc.). Additionally, some storage drives may be accessible over a computer network.
Many computing platforms are provided with one or more communication interfaces (710), according to the function intended of the computing platform. For example, a personal computer is often provided with a high speed serial port (RS-232, RS-422, etc.), an enhanced parallel port (“EPP”), and one or more universal serial bus (“USB”) ports. The computing platform may also be provided with a local area network (“LAN”) interface, such as an Ethernet card, and other high-speed interfaces such as the High Performance Serial Bus IEEE-1394.
Computing platforms such as wireless telephones and wireless networked PDA's may also be provided with a radio frequency (“RF”) interface with antenna, as well. In some cases, the computing platform may be provided with an infrared data arrangement (“IrDA”) interface, too.
Computing platforms are often equipped with one or more internal expansion slots (811), such as Industry Standard Architecture (“ISA”), Enhanced Industry Standard Architecture (“EISA”), Peripheral Component Interconnect (“PCI”), or proprietary interface slots for the addition of other hardware, such as sound cards, memory boards, and graphics accelerators.
Additionally, many units, such as laptop computers and PDA's, are provided with one or more external expansion slots (712) allowing the user the ability to easily install and remove hardware expansion devices, such as PCMCIA cards, SmartMedia cards, and various proprietary modules such as removable hard drives, CD drives, and floppy drives.
Often, the storage drives (79), communication interfaces (810), internal expansion slots (711) and external expansion slots (712) are interconnected with the CPU (71) via a standard or industry open bus architecture (78), such as ISA, EISA, or PCI. In many cases, the bus (78) may be of a proprietary design.
A computing platform is usually provided with one or more user input devices, such as a keyboard or a keypad (716), and mouse or pointer device (717), and/or a touch-screen display (718). In the case of a personal computer, a full size keyboard is often provided along with a mouse or pointer device, such as a track ball or TrackPoint™. In the case of a web-enabled wireless telephone, a simple keypad may be provided with one or more function-specific keys. In the case of a PDA, a touch-screen (718) is usually provided, often with handwriting recognition capabilities.
Additionally, a microphone (719), such as the microphone of a web-enabled wireless telephone or the microphone of a personal computer, is supplied with the computing platform. This microphone may be used for simply reporting audio and voice signals, and it may also be used for entering user choices, such as voice navigation of web sites or auto-dialing telephone numbers, using voice recognition capabilities.
Many computing platforms are also equipped with a camera device (7100), such as a still digital camera or full motion video digital camera.
One or more user output devices, such as a display (713), are also provided with most computing platforms. The display (713) may take many forms, including a Cathode Ray Tube (“CRT”), a Thin Flat Transistor (“TFT”) array, or a simple set of light emitting diodes (“LED”) or liquid crystal display (“LCD”) indicators.
One or more speakers (714) and/or annunciators (715) are often associated with computing platforms, too. The speakers (714) may be used to reproduce audio and music, such as the speaker of a wireless telephone or the speakers of a personal computer. Annunciators (715) may take the form of simple beep emitters or buzzers, commonly found on certain devices such as PDAs and PIMs.
These user input and output devices may be directly interconnected (78′, 78″) to the CPU (71) via a proprietary bus structure and/or interfaces, or they may be interconnected through one or more industry open buses such as ISA, EISA, PCI, etc. The computing platform is also provided with one or more software and firmware (7101) programs to implement the desired functionality of the computing platforms.
Turning to now
Additionally, one or more “portable” or device-independent programs (824) may be provided, which must be interpreted by an OS-native platform-specific interpreter (825), such as Java™ scripts and programs.
Often, computing platforms are also provided with a form of web browser or micro-browser (826), which may also include one or more extensions to the browser such as browser plug-ins (827).
The computing device is often provided with an operating system (820), such as Microsoft Windows™, UNIX, IBM OS/2 ™, LINUX, MAC OS™ or other platform specific operating systems. Smaller devices such as PDA's and wireless telephones may be equipped with other forms of operating systems such as real-time operating systems (“RTOS”) or Palm Computing's PalmOS™.
A set of basic input and output functions (“BIOS”) and hardware device drivers (821) are often provided to allow the operating system (820) and programs to interface to and control the specific hardware functions provided with the computing platform.
Additionally, one or more embedded firmware programs (822) are commonly provided with many computing platforms, which are executed by onboard or “embedded” microprocessors as part of the peripheral device, such as a micro controller or a hard drive, a communication processor, network interface card, or sound or graphics card.
As such,
Conclusion
The present invention enhances the ability of clients to request specific grid vendors who have historically performed according to a client's preferences, and enhances a grid computing control system's ability to select-grid resources and vendors for job assignment who have historically performed according to performance requirements.
It will be recognized by those skilled in the art that the foregoing examples and embodiment details are provided for illustration of the present invention, and that certain variations in embodiment may be made without departing from the spirit and scope of the present invention. Therefore, the scope of the invention should be determined by the following claims.
