# A COMPARISON OF LOAD SHARING AND JOB SCHEDULING IN A NETWORK OF WORKSTATIONS

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5 2.4 Performance Metrics Parameters used in simulation computations (presented later) are shown in Table 1. RT represents overall performance, while MW Ratio expresses fairness in individual job service. When load sharing is examined, case X is Pr, while case Y is one of the remaining load sharing methods. When job scheduling is examined, case X is FCFS, while case Y is one of the other job scheduling methods. Load sharing and job scheduling use the same measure for comparisons in this paper because FCFS is actually the Pr method. 3. SIMULATION RESULTS AND DISCUSSION 3.1 Model Implementation and Input Parameters The queuing network model described above is implemented with discrete event simulation ([Law and Kelton, 1991]) using the independent replication method. For every mean value, a 95% confidence interval is evaluated. All confidence intervals are less than 5% of the mean values. We have chosen mean processor service time 1/ = 1, which means mean service rate per processor =1. Since there are 16 workstations, we chose < 16, and consequently 1/ >.625. For this reason we examined the following mean inter-arrival times: 1/ =.7,.8,.9, which corresponds to the following arrival rates: = , 12.5, Epoch sizes are 2, 4, 6, and 8. We chose epoch length 2 as a starting point because the mean processor service time is equal to 1, and because with this epoch size NSA is much smaller than in the SQ case. We expect that larger epoch sizes would result in even smaller NSA. Also, with this epoch size, NQR is smaller than in the SJF case. Therefore, it is expected that larger epoch sizes would result in even smaller NQR. Co =.1 is considered for mean migration cost. In all cases, service time estimation errors of ±1% and ±3% are considered. 3.2 Performance Analysis The following results represent performance of the different policies. In each of these cases, system load (mean workstation utilization) is:.88 for 1/ =.7,.77 for 1/ =.8,.69 for 1/ = Load Sharing Performance Figures 2, 3, 4, 5 present the performance metrics versus 1/ (mean inter-arrival time) in the load sharing case. In all cases, the overall performance in terms of mean response time is superior with the SQ method. The superiority of SQ is intuitive. However, the intent of this study is to determine how superior it is to other methods, and whether the extent of its superiority justifies overhead required to maintaining knowledge of processor queue lengths. Pr is worst method. The difference in RT between Pr and each of the other methods decreases with decreasing arrival rate. The migration of jobs when using PrM significantly improves overall performance as compared with Pr. This is because when Pr is used, there are cases where processors have unbalanced queues and therefore may benefit from job migration. For all, the difference in performance between PrM and Pr varies between 51% and 75%. For all epoch sizes, epoch load sharing performs significantly better than Pr. Mean response time performance improves with decreasing epoch size. However, the PrM algorithm performs better than ELS. For all, the difference between ELS and each of PrM, and SQ increases with increasing epoch size. Generally, the superiority of SQ over PrM and ELS increases with increasing mean inter-arrival time. For all, the relative decrease in the number of scheduler activations (D NSA ) is very high for all epoch sizes (i.e., in the range of 96-99%). For any, D NSA increases slightly with increasing epoch size. D NSA is lower in the PrM case (in the range 7% 76%). The difference in the number of scheduler activations between PrM and ELS slightly decreases with decreasing. Figure 5 shows that the MW Ratio decreases with decreasing with each method. MW Ratio > 1. holds in 8 ISSN x online, print

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