Abstract:
A system and method for evaluating workload units in a computer system whereby each workload unit is assigned an impact number representing the number of days that the expiration date of a computer system would be changed if the workload unit were to be added or removed from the system with all other workload units remaining the same. Each workload unit may be assigned a different number for each system in the environment. The inventive system and method simplify the task of combining multidimensional workload measures and incorporate the interaction with other workload units in the system by assessing the impact on both a donor and a recipient computer systems&#39; expiration dates. Thus, the invention provides a more robust way to measure the effect of moving workload units between systems to result in a better allocation of work amongst computer systems in a processing environment.

Description:
FIELD OF THE INVENTION 
     The invention relates generally to the field of computer systems and more particularly to a system and method for optimizing computer resource usage across a plurality of computer systems. 
     BACKGROUND OF THE INVENTION 
     In the capacity planning process, system parameters, desired service levels, and workload predictions are used to determine when the resources of a computer system will be exceeded and are used to assist in identifying cost-effective remedies to resource shortfalls. “Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems”, by Daniel A. Menasce, Virgilio A. Almeida, and Larry W. Dowdy (Prentice Hall, Englewood Cliffs, N.J., 1994) discloses approaches to both the predicting and rectifying of computer resource challenges. 
     Capacity planning for a set of heterogeneous computer systems presents several problems, as set forth below. As a first challenge, it must be recognized that workloads use multiple resources. Therefore, the effect of workload assignment is not readily predicted or quantified. Second, workload typically grows, and the rate of growth may differ between resources. Third, different computer systems may have different resources, and different resource capacities. These problems can make it difficult to determine how long available resources will last, which computer systems are most at risk for exceeding their resources, how to reallocate resources to alleviate shortages, and how the computer systems will be affected by such reallocations. 
     Dan Asit and Dinkar Sitaram, in U.S. Pat. No. 5,530,557, entitled “Online Placement of Video Files Determined by a Function of the Bandwidth to Space Ratio of each of the Storage Devices in a Server Environment”, (Jun. 25, 1996) teach one solution for maximizing storage utilization for the placement of videos on storage devices taking into account the expected demand for the video. Asit, et al use the bandwidth space ratio (BSR) to place videos on disks. The BSR of a disk is its bandwidth divided by space. The BSR of a video is the expected demand for the video divided by the space required to store it. Demand may be forecast based on historical usage data and, in their invention, a Video Placement Manager places the videos on the disks to match the BSR of the videos with the BSR of the disk. 
     Additional references which have sought to predict and manage storage capacity include an article and related patent application of W. G. Pope and Lily Mummert. The article entitled “The Use of Life Expectancy to Manage Notes Domino E-Mail Storage”, Proceedings of the Computer Measurement Group, CMG &#39;99, December 1999, and the patent application Ser. No. 09/457,467 entitled “System and Method for Providing Property Histories of Objects and Collections For Determining Device Capacity Based Thereon”, which was filed on Dec. 8, 1999, propose a method for projecting device capacity by past history of access to and usage of the relevant information for a single computer system. 
     In general, the amount of workload on a computing system grows over time. Eventually, workload exceeds the system&#39;s capacity causing either unscheduled outages or severe performance degradation which results in increased administrative costs and reduced customer satisfaction. When the server is a member of a group of servers where workload can be moved to some other server in the group, it is desirable to avoid these problems with planned action, as will be addressed by the present invention. 
     The date when a server&#39;s workload exceeds its capacity is called its expiration date. An expiration date is established using the aforementioned methods like life expectancy or capacity space. To provide a quality service, it is necessary to upgrade or offload the server before its expiration date. Usually, there are certain key dates when major changes can be made to a server with minor impact to service. These dates are conventionally associated with holidays, whereby service impact is reduced if servers are upgraded on a key date that precedes the expiration date. 
     Other resources, such as administrative personnel, are normally in limited supply. This constraint bounds the number of server upgrades that can be performed on any given key date. Thus, it is necessary to distribute the expiration dates of servers to fit within the bounds dictated by these other resources. A system&#39;s expiration date can be adjusted by adding or removing workload. 
     What is needed is a system and method which analyzes the combined expiration dates of a group of systems and adjusts the location of workload to align the expiration dates of systems in the group with key dates in order to fit within the bounds dictated by external resources. 
     What is additionally needed is to provide a system and method for analyzing the impact of a single workload unit on the capacity of a system. 
     Another objective of the present invention is to utilize workload unit impact measurements to improve the life expectancies of as many of the processing systems in a processing environment as possible. 
     SUMMARY OF THE INVENTION 
     The foregoing and other objectives are realized by the present system and method which utilizes a single measure for the workload unit. This measure is called the impact which is measured in time (usually days) and represents the effect of the workload unit on the expiration date of the system. The method is more robust in that the measure of a workload unit is calculated in relation to a specific processing system and the other workload assigned to the system, other than the workload unit in question. This measurement technique is effective and relevant for an iterative planning process that examines the movement of workload units to achieve a desired configuration of expiration dates within a processing environment. 
     The system and method of the present invention provide for evaluating workload units in a computer system whereby each workload unit is assigned an impact number representing the number of days that the expiration date of a computer system would be changed if the workload unit were to be added or removed from the system with all other workload units remaining the same. The impact number for a given workload unit may differ depending upon the system to which it is assigned. The inventive system and method simplify the task of combining multidimensional workload measures and incorporate the interaction with other workload units in the system by assessing the impact on both a donor and a recipient computer systems&#39; expiration dates. Thus, the invention provides a more robust way to measure the effect of moving workload units between systems to result in a better allocation of work amongst computer systems in a processing environment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will now be described in greater detail with specific reference to the appended drawings wherein: 
         FIG. 1  illustrates a processing environment for implementing the present invention; 
         FIG. 2  provides a timeline and server placement example; 
         FIG. 3  illustrate a graph associating computer servers with key planning dates; 
         FIG. 4  provides a process flow diagram depicting the highest level of the methods of this invention; 
         FIG. 5  provides a process flow diagram depicting the assignment of targets to list L; 
         FIG. 6  provides a process flow diagram depicting the processing of the From list; 
         FIG. 7  provides a process flow diagram depicting the process flow for extending the expiration date of a computing system; 
         FIG. 8  provides a process flow diagram for calculating the impact of each workload unit on a computing system&#39;s expiration date; 
         FIG. 9  provides a process flow diagram for selecting the best server in the To list; 
         FIG. 10  provides a process flow diagram for moving the workload unit from the From to the To computing system; and 
         FIG. 11  provides a process flow diagram depicting the recalculation of the expiration date for systems s and b in accordance with the foregoing. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     For the ensuing description of the invention, the following terms will be used: 
     An administrative processor is a computer system with the capability to execute computer software and programs. Here the term administrative processor refers to hardware including at least a central processing unit along with the memory and input/output interfaces for transferring digital data between the inside of the system and the outside world and the operating and support software, i.e. operating system and support subsystems that allow the hardware devices to be used. The term administrative processor is not meant to include any devices for the permanent storage of data. The administrative processor may be part of a separate processing system (as shown in  FIG. 1 ) or may be a component of one of the processing systems in the processing environment for which the workload analysis is to be conducted. More than one administrative processor can serve a single processing environment. 
     A repository is a means for storing structured data external to the administrative processor. Data in the repository is saved and accessed in a storage subsystem but is also supported by software, such as relational database software, that provides access to the structure of the data. Database software is not essential for a repository as the content of the repository can be stored in simpler storage objects, such as a flat file. 
     A processing system is a computing system that includes all the hardware and software needed to execute computer programs. This includes the central processing unit (CPU) or multiple CPUs, memory, storage and network connectivity as well as the operating system, application software and procedures for managing work on the system. 
     Workload is the set of identifiable tasks that execute in the processing system and utilize or consume the resources of the system. 
     A workload unit is a subset of the workload that can be associated with some external identifier (e.g., the collection of all tasks executed by an employee user.) Workload units are a collection point for keeping historical records about resource consumption and act as a means to allocate workload to a specific processing system. Workload units may execute anywhere in the processing environment, subject only to resource constraints. 
     A container is a generalized term that represents an identifiable and limited part of a resource that has a limit, or capacity. A storage container might be a disk partition or an entire physical device, limited by its size. A processing container might be a CPU, a set of CPUs, or a specific type of server. The limit might be some number of instructions or transactions per unit time. A network container could be an interface, or the network itself, and the limit could be the bandwidth. In any case, the resource has a limit (capacity) which cannot be exceeded without external intervention. Attempts to exceed the capacity of a container will result in degraded performance or failure. 
     A processing environment is a collection of processing systems that are capable of executing the workload for any of the workload units executing within the environment. The administrative processor has access to the storage subsystems) in its storage environment. Through the storage subsystems, it can identify all of the containers in each subsystem, the limits of those containers, the identity of all of the objects in each container, and the resource usage of each object. 
     A threshold is an artificial limit on utilization that is used by the capacity planning process to prioritize containers that need action. When the projected utilization of a container reaches the threshold, the container is selected to be managed, and action will be taken to prevent or alleviate the resource shortage in that container. 
     Capacity management is the process of projecting and managing the allocation of workload unit to processing systems within a processing environment so that capacity limits are not exceeded within a planning horizon. Capacity management is depicted by three high level steps: (1) collecting information about the processing environment, (2) projecting the state of the processing environment at some time in the future; and (3) defining actions to prevent the over commitment of any processing system. 
     The life expectancy of a processing system is the period of time from the last measurement of the system until the increase in resource consumption is expected to exceed the capacity of any one of the system&#39;s resources. If the change in resource consumption over time is non-positive and the system is operating below its capacity limit, then the life expectancy of the system is considered infinite. If the resource consumption exhibits positive growth for any system resource dimension, the life expectancy of the system is finite. 
     A system&#39;s expiration date is the date when the server workload is expected to exceed its capacity because of growth in workload. An expiration date is calculated using life expectancy as set forth in co-pending patent application Ser. No. 09/457,467 entitled “System and Method for Providing Property Histories of Objects and Collections For Determining Device Capacity Based Thereon”, which was filed on Dec. 8, 1999, or capacity space as set forth in co-pending patent application Ser. No. 09/690,872, entitled “System and Method for Analyzing Capacity in a Plurality of Processing Systems, which was filed on Oct. 17, 2000, or some comparable method (see also: Daniel A. Menasce, Virgilio A. Almeida, and Larry W. Dowdy, “Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems”, Prentice Hall, Englewood Cliffs, N.J., 1994 and Bucky Pope and Lily Mummer, “The Use of Life Expectancy to Manage Notes Domino E-Mail Storage”, Proceedings of the Computer Measurement Group, CMG &#39;99, December 1999). For the purposes of the present invention, the use of the terms “expiration date”, “life expectancy”, and “capacity space” will be understood to be mutually-interchangeable alternatives representing measurements of a processing system&#39;s capacity. 
     The impact of a workload unit is the effect on the system&#39;s expiration date that results from either adding the workload unit to the system or removing it. The impact is calculated by taking the difference between the expiration date before and after the workload change. 
     The system where this invention would apply is represented  FIG. 1  comprising a processing environment having an administrative processor  101  is adapted to implement the inventive process. The administrative processor  101  has access to a data repository  102 , such as a relational database, where the data can be saved and from which data can be retrieved. The administrative processor also has access to configuration data about properties of the processing environment  100 , comprising processing systems  104   a  and  104   b , and about workload needs and workload usage history data relating to the workload units  105   a  and  105   b  that are part of the processing environment. 
     The objects of interest for this invention are processing systems  104   a  and  104   b  that manage workload units. An example of work which is to be divided up into workload units to be managed by the respective processing systems is a sort program run on behalf of a computer user. Each workload unit has a unique identifier, within the processing environment. Workload units consume resources of the processing systems. The resources consumed by a workload unit are recorded by the processing system and the record of this consumption is transferred as the workload usage history to the administrative processor  101  and stored in the repository  102 . Each resource has its own unit of measure. These consumption records are identified by the name of the workload unit and the time period of the consumption. 
     The administrative processor makes use of three inputs: a table of key planning dates, the set of tables of workload units for each processing system and the table of processing systems in the installation. With the relevant information, the impact value component  111  of the administrative processor associates each processing system in the processing environment with a key planning date on the planning horizon. An objective of the invention is to ensure that each processing system&#39;s expiration date falls after a specified key planning date. If the processing component  121  of the administrative processor finds that a system will run out of capacity before its assigned key planning date, it will perform an analysis and select workload units to move to another system. Then, it will search the other systems in the environment to determine where to place the workload unit. In general, removing workload from a system results in a later expiration date while adding workload to a system typically results in an earlier expiration date. 
     The analysis of the system capacities and selection of workload units for transfer continue until the objective is met whereby all systems&#39; expiration dates are later than their key planning dates. The result of the analysis is a plan to move workload units between systems in the environment, If an assignment of workload that satisfies the planning dates is not possible, a partial plan can be created to improve the state of the system even though it fails to meet the ultimate planning objective. 
       FIG. 2  illustrates the inventive methodology. The expiration date for system s 1  places it before key planning date d 1 . By removing workload from s 1 , the system&#39;s expiration date is extended as represented by arrow  202 . The process continues to remove workload until the server&#39;s expiration date falls after the key planning date. Workload removed from one system must, of course, be moved to another system in the group, depicted in  FIG. 2  as arrow  201 . Moving workload onto a server shifts that server&#39;s expiration date to the left on a timeline.  FIG. 2  illustrates this with system s 2 . Adding workload to s 2  moves its expiration date to the left as indicated by arrow  203 . 
     Let Table D be a date table with i entries, one for each date in the planning horizon. Each date entry Di is a tuple of two values {di,ci} where di is the planning date and ci is a count representing the number of systems that must expire after that date. The administrative processor assumes that D has been created by some external means. Usually planning dates are chosen in such a way to minimize impact on service, such as holidays. Additionally, it must be noted that the number of systems that may be reconfigured on a given date may be affected by other resources, such as amount of available administrative personnel. 
     Let Table L be the table of j systems to be managed. Each entry Lj is a tuple of two values {sj,ej}, where sj is the name of the system j and ej is the expiration date for system j, calculated using life expectancy, capacity space, or some similar methodology. The number of servers j must equal the sum of the counts (ci) found in date table D. 
     Let Table W with k entries represent all of the workload units on the group of systems. Each entry Wk consists of a tuple of the following values {uk, sk} where uk is the identifier of the workload and sk is the name of the system that most recently served the workload. 
     The invention works with date deltas as depicted in  FIG. 3 .  FIG. 3  shows seven systems indicated by the circles  301 - 307  marked s 1  to s 7 . The planning horizon is indicated by a timeline marked t 1  to tn. Three key planning dates are indicated: d 1 , d 2 , and d 3 . The seven systems are divided into three subsets, one subset for each key planning date. The systems s 1 -s 7  have been ordered in expiration date sequence and positioned above the planning horizon in line by their expiration date. Each key planning date has a number of systems assigned to it as depicted by the number in parentheses following the date: two for d 1 , three for d 2 , and two for d 3 . Subset  1  consisting of systems s 1  and s 2  are assigned to d 1 . One system, s 1 , expires before d 1  and has a negative date delta as shown at  311  by Δ 1 . The second system, s 2 , has a positive delta date, Δ 2 , shown at  312 , because the expiration data of the system fall after the key planning date. 
     The invention creates an output referred to as the move table M. Let Table M have l entries. Each move entry Ml is composed of three entries {ul, fl, tl} where u 1  is the designator for workload unit l, fl is the current location of the workload (“From” system), and tl is the next location of the workload (“To” system). 
       FIGS. 4-11  depict one implementation of the invention, based on a greedy algorithm.  FIG. 4  provides a process flow diagram depicting the highest level of the methods of this invention. The first step  401  is to retrieve the list of systems L from the repository. The list is sorted in ascending date sequence by the expiration date (e) of each system in the list. Step  402  assigns each system to a key planning date as is explained in  FIG. 5 . Next, in step  403 , the From list F, the To list T and the Move list M are initialized with empty list structures. In step  404 , the first system in list L is assigned as server l. Step  405  calculates the Δ for system l by subtracting the key planning date from the system&#39;s expiration date. Step  406  next determines if the server needs to have workload removed. If the system will expire before the key planning date, that is the Δ is negative, then action must be taken to remove workload. If, in step  406 , the determination is made that the system will expire before its planning date, the system is added to the From list F in step  407 . If the system will not expire before its key planning date, it is a candidate to receive workload and is added to the To list T (in step  408 ). Step  409  determines if all systems in list L have been allotted to either the From list or the To list. If there are more systems to process, step  410  picks the next system in the list, otherwise processing continues in step  411  as described starting with  FIG. 6 . 
       FIG. 5  describes the procedure for assigning key planning dates to every system in list L. First, in step  501 , the date Table D is retrieved from the repository and the key planning dates are sorted in ascending date sequence. In step  502 , the date in the first tuple in Table D is assigned to d and the count value is set for c. The first system in List L is assigned as l in step  503 . In step  504 , planning date d is assigned to l. Step  505  tests to determine if all systems have been assigned a date and, if so, the process returns the completed list L. If there are more systems in List L, step  506  first decrements the count c to indicate that date d was assigned to l. If there are more systems to be assigned to the planning date d (i.e. c&gt;0 in step  507 ), then the processing proceeds to step  508  where the next system is assigned as l, otherwise step  509  picks the next date in Table D, and processing continues with step  508 . 
       FIG. 6  describes the procedure for processing of the From list F. The From list comprises a list of the systems that need workload removed. Step  601  prioritizes the list in ascending expiration date sequence since the systems that expire the soonest must be addressed first, as there is less time to make changes to the installation. Step  602  prioritizes the To list of systems in descending expiration date sequence so that workload is moved to the server that is the farthest to the right on the planning horizon time line. This procedure is complete when either the From list or the To list is empty, as indicated by the decision boxes of steps  603  and  604 . If the From list has entries, there are some systems that will expire before their target date and for which workload must be removed. When there are systems in the To list, there are potential candidates to receive the workload. Step  605  assigns the next system in the From list to s and step  606  performs the process of finding the right workload unit to remove and the right system to receive the workload unit, as further detailed with reference to  FIG. 7 . 
       FIG. 7  details the process for determining how to extend the expiration date of a system. Step  701  retrieves a table of the workload that currently uses system s. Step  702  is a procedure (further detailed in  FIG. 8 ) that determines the impact of removing each workload unit for the system. The workload list is sorted in descending order by impact in step  703  and the workload at the top of the list is selected in step  704 . Step  705  tests to determine if the workload list is empty and if it is, the procedure is complete because there is no more work that is available to move. Step  706  is a procedure that finds the best server to receive the workload unit u. It may be that no system is capable of receiving workload unit u (as tested in step  707 ) in which case the next workload unit is selected in step  708  and the procedure returns to the test in step  705 . If there is a system to receive unit u, the workload is moved in procedure  709  ( FIG. 10 ) and the expiration date for system s is recalculated in step  710 . Since the expiration dates of systems in the From and To list have been changed by the movement of workload unit u, the two lists are resequenced before the procedure exits. 
       FIG. 8  details the process for calculating the impact of each workload unit on a system. The unit of measure for impact is time, usually recorded in days. First, in step  801 , the list of workload units assigned to the system in question is retrieved from the repository. Next, in step  802 , the first workload unit is selected. It is here to be noted that there need be no particular order to the workload list for this procedure. The selected workload unit is temporarily removed from the list in step  804 , and a new expiration date is calculated using the remainder of the list. The difference between this new expiration date and the original expiration date is assigned to the selected workload unit at step  805  as its impact, and the workload unit is returned to the list. If all workload units have been processed, the procedure completes. If not all workload units have been processed, the system proceeds to the next workload unit to be processed at step  807 . When all iterations are completed, each workload unit will have been assigned an impact number that represents the change in expiration date if that workload unit, only, is removed. 
       FIG. 9  describes how the system is selected to receive a workload unit. First, the list of To systems must be ordered in priority sequence. Step  901  sorts the list of To systems in descending expiration date sequence. The use of expiration date is one way of prioritizing the list, although other prioritizing functions could be substituted at this point. The top system on the list is selected as the next candidate at step  902 , as long as there are candidate To systems on the To list, as determined at step  903 . In step  904 , the list of workload units for that system is retrieved from the repository. The additional workload unit is added to the list at step  905  and the expiration date is recomputed in step  906 . Step  907  compares the new expiration date with the selected systems key planning target date. If the expiration date still falls beyond the key planning data on the planning time line, the procedure is complete and the selected system is returned as the best candidate at step  910 . If the addition of this workload causes the system expiration date to fall short of the key planning date, as determined at step  907 , the method proceeds to step  908  where the next system on the list is selected as a candidate. The process continues until either an appropriate system is found (step  907 ) or until all systems have been examined and none have qualified to receive the workload, as determined at step  903 . 
     When the process successfully finds a workload unit that can be moved, is creates an entry in the move table and updates the workload lists for the From and To systems.  FIG. 10  illustrates the updating process. Step  1001  retrieves the workload unit list from the repository for the From system and step  1003  retrieves the workload unit list for the To system. The workload unit is removed from the From system workload list and the list is returned to the repository at step  1002 . The unit is added to the To systems workload unit list and that list is returned to the repository at  1004 . Finally, the tuple representing the name of the workload unit, the From and To system is added to the Move table in step  1005 . 
       FIG. 11  is the last process in this method as it recalculates the expiration dates for the From and To systems. At step  1101  the workload unit list is retrieved from the repository for the To system and the expiration date of the To system is recalculated. The updated tuple is saved with the system identifier and the expiration date to the To list at step  1103 . For the From server, the workload list is first retrieved from the repository (step  1104 ) and the expiration date is recalculated at  1105 . The procedure tests for the possibility that the expiration date now falls after the key planning target date as determined at step  1106 . If this is the case, the entry is moved to the To list at  1107 , otherwise it remains of the From list. 
     While the invention has been described with reference to an illustrated system and several preferred process flow embodiments it will be apparent to one having skill in the relevant art that modifications can be made without departing from the spirit and scope of the invention as set forth in the appended claims.