Method and apparatus for online sample interval determination

Abstract

In one embodiment, functional system elements are added to an autonomic manager to enable automatic online sample interval selection. In another embodiment, a method for determining the sample interval by continually characterizing the system workload behavior includes monitoring the system data and analyzing the degree to which the workload is stationary. This makes the online optimization method less sensitive to system noise and capable of being adapted to handle different workloads. The effectiveness of the autonomic optimizer is thereby improved, making it easier to manage a wide range of systems.

1 . A method for determining sample intervals for resource allocations in a dynamic computing system, the method comprising the steps of: 
 collecting measured output data indicative of system characteristics and variable workloads;    determining whether to start interval tuning of the system; and    analyzing the collected measured output data to determine a sample interval for the system.    
     
     
         2 . The method of  claim 1 , wherein said determining step comprises: 
 determining whether sufficient measured output data has been collected for interval tuning, prior to the start of measured output data analysis.    
     
     
         3 . The method of  claim 2 , wherein additional measured output data is collected if the collected measured output data is not sufficient.  
     
     
         4 . The method of  claim 1 , wherein the measured output data is benefit information indicative of system response time as a function of system resource allocations.  
     
     
         5 . The method of  claim 1 , wherein the measured output data is collected for a fixed number of intervals.  
     
     
         6 . The method of  claim 1 , wherein resource allocation is halted during the collection of the measured output data.  
     
     
         7 . The method of  claim 1 , wherein the step of determining when to start interval tuning of the system comprises the step of: 
 determining if a system is receiving a workload.    
     
     
         8 . The method of  claim 7 , wherein the system is not ready to start interval tuning if the system is not receiving a workload.  
     
     
         9 . The method of  claim 7 , further comprising the step of: 
 determining if the system is attempting to perform interval tuning for the first time, if the system is receiving a workload.    
     
     
         10 . The method of  claim 9 , further comprising the step of: 
 determining if the system has reached a steady state, if the system is attempting to perform interval tuning for the first time.    
     
     
         11 . The method of  claim 9 , further comprising the step of: 
 waiting for a next-scheduled tuning interval, if the system is not attempting to perform interval tuning for the first time.    
     
     
         12 . The method of  claim 10 , wherein the system is ready for interval tuning only if the system has reached a steady state.  
     
     
         13 . The method of  claim 1   1 , wherein the system is ready for interval tuning during the next-scheduled tuning interval.  
     
     
         14 . The method of  claim 9 , wherein the system is presumed to be receiving a workload if at least one data point of the collected measured output data is not zero.  
     
     
         15 . The method of  claim 10 , wherein the system has reached a steady state if data collected at the state is representative of system characteristics.  
     
     
         16 . The method of  claim 2 , wherein the system is ready for analyzing the collected measured output data to determine a sample interval for the system if sufficient measured output data has been collected.  
     
     
         17 . The method of  claim 2 , wherein the method further comprises the following steps if sufficient measured output data has not been collected: 
 overriding a current system resource allocation;    setting a small sample interval; and    collecting additional measured output data.    
     
     
         18 . The method of  claim 1 , wherein the step of analyzing the collected measured output data to determine a sample interval for the system comprises the steps of: 
 separating the collected measured output data into two groups, wherein a group having a smaller standard deviation is selected for analysis;    selecting a measured output data point with the largest standard deviation; and    determining the sample interval based on measured and desired statistical properties.    
     
     
         19 . The method of  claim 18 , wherein the sample interval is determined by considering a confidence of the collected measured output data.  
     
     
         20 . The method of  claim 19 , wherein a desired confidence range is indicative of a desired maximum difference between a measured sample benefit and an actual mean benefit.  
     
     
         21 . A computer readable medium containing an executable program determining sample intervals for resource allocations in a dynamic computing system, wherein the program performs the steps of: 
 collecting measured output data indicative of system characteristics and variable workloads;    determining whether to start interval tuning of the system; and    analyzing the collected measured output data to determine a sample interval for the system.    
     
     
         22 . The computer readable medium of  claim 21 , wherein said determining step comprises: 
 determining whether sufficient measured output data has been collected for interval tuning, prior to the start of measured output data analysis.    
     
     
         23 . The computer readable medium of  claim 21 , wherein the measured output data is benefit information indicative of system response time as a function of system resource allocations.  
     
     
         24 . The computer readable medium of  claim 21 , wherein the measured output data is collected for a fixed number of intervals.  
     
     
         25 . The computer readable medium of  claim 21 , wherein resource allocation is halted during the collection of the measured output data.  
     
     
         26 . The computer readable medium of  claim 21 , wherein the step of determining when to start interval tuning of the system comprises the step of: 
 determining if a system is receiving a workload.    
     
     
         27 . The computer readable medium of  claim 26 , wherein the system is not ready to start interval tuning if the system is not receiving a workload.  
     
     
         28 . The computer readable medium of  claim 26 , further comprising the step of: 
 determining if the system is attempting to perform interval tuning for the first time, if the system is receiving a workload.    
     
     
         29 . The computer readable medium of  claim 28 , further comprising the step of: 
 determining if the system has reached a steady state, if the system is attempting to perform interval tuning for the first time.    
     
     
         30 . The computer readable medium of  claim 28 , further comprising the step of: 
 waiting for a next-scheduled tuning interval, if the system is not attempting to perform interval tuning for the first time.    
     
     
         31 . The computer readable medium of  claim 29 , wherein the system is ready for interval tuning only if the system has reached a steady state.  
     
     
         32 . The computer readable medium of  claim 30 , wherein the system is ready for interval tuning during the next-scheduled tuning interval.  
     
     
         33 . The computer readable medium of  claim 28 , wherein the system is presumed to be receiving a workload if at least one data point of the collected measured output data is not zero.  
     
     
         34 . The computer readable medium of  claim 29 , wherein the system has reached a steady state if data collected at the state is representative of system characteristics and suitable for use in interval tuning.  
     
     
         35 . The computer readable medium of  claim 22 , wherein the system is ready for analyzing the collected measured output data to determine a sample interval for the system if sufficient measured output data has been collected.  
     
     
         36 . The computer readable medium of  claim 22 , wherein the method further comprises the following steps if sufficient measured output data has not been collected: 
 overriding a current system resource allocation;    setting a small sample interval; and    collecting additional measured output data.    
     
     
         37 . The computer readable medium of  claim 21 , wherein the step of analyzing the collected measured output data to determine a sample interval for the system comprises the steps of: 
 separating the collected measured output data into two groups, wherein a group having a smaller standard deviation is selected for analysis;    selecting a measured output data point with the largest standard deviation; and    determining the sample interval based on measured and desired statistical properties.    
     
     
         38 . The computer readable medium of  claim 37 , wherein the sample interval is determined by considering a confidence of the collected measured output data.  
     
     
         39 . The computer readable medium of  claim 38 , wherein a desired confidence range is indicative of a desired maximum difference between a measured sample benefit and an actual mean benefit.  
     
     
         40 . A method for providing an optimization service to a client for a data processing system receiving a variable workload, the method comprising the steps of: 
 collecting measured output data indicative of system characteristics and workloads;    determining whether to start interval tuning of the system; and    analyzing the collected measured output data to determine a sample interval for the system to evaluate resource allocations to said client.    
     
     
         41 . The method of  claim 40 , wherein said determining step comprises: 
 determining whether sufficient measured output data has been collected for interval tuning, prior to the start of measured output data analysis.    
     
     
         42 . The method of  claim 40 , wherein the measured output data is benefit information indicative of system response time as a function of system resource allocations.  
     
     
         43 . The method of  claim 40 , wherein the step of determining when to start interval tuning of the system comprises the step of: 
 determining if a system is receiving a workload.    
     
     
         44 . The method of  claim 43 , further comprising the step of: 
 determining if the system is attempting to perform interval tuning for the first time, if the system is receiving a workload.    
     
     
         45 . The method of  claim 44 , further comprising the step of: 
 determining if the system has reached a steady state, if the system is attempting to perform interval tuning for the first time.    
     
     
         46 . The method of  claim 44 , further comprising the step of: 
 waiting for a next-scheduled tuning interval, if the system is not attempting to perform interval tuning for the first time.    
     
     
         47 . The method of  claim 45 , wherein the system is ready for interval tuning only if the system has reached a steady state.  
     
     
         48 . The method of  claim 45 , wherein the system has reached a steady state if data collected at the state is representative of system characteristics and suitable for use in interval tuning.  
     
     
         49 . The method of  claim 41 , wherein the system is ready for analyzing the collected measured output data to determine a sample interval for the system if sufficient measured output data has been collected.  
     
     
         50 . The method of  claim 41 , wherein the method further comprises the following steps if sufficient measured output data has not been collected: 
 overriding a current system resource allocation;    setting a small sample interval; and    collecting additional measured output data.    
     
     
         51 . The method of  claim 40 , wherein the step of analyzing the collected measured output data to determine a sample interval for the system comprises the steps of: 
 separating the collected measured output data into two groups, wherein a group having a smaller standard deviation is selected for analysis;    selecting a measured output data point with the largest standard deviation; and    determining the sample interval based on measured and desired statistical properties.    
     
     
         52 . A computing system, comprising: 
 a data processing system adapted to receive and process a variable workload, wherein the data processing system is further adapted to generate measured output data indicative of data processing system characteristics and workloads;    a plurality of resources available to the data processing system for processing the workload;    a resource optimizer coupled to the data processing system and adapted for evaluating resource allocations in pre-defined intervals; and    an interval tuner coupled to the data processing system and to the resource optimizer, the interval tuner being adapted for evaluating the measured output data in order to determine the pre-defined intervals in which the resource optimizer evaluates resource allocations.