Abstract
The performance of the existing non-contiguous processor allocation strategies has been traditionally carried out by means of simulation based on synthetic workload models to generate streams of incoming jobs. To validate the performance of the existing algorithms, there is need to evaluate the algorithms' performance based on real workload traces. In this paper, we evaluate the performance of several well-known processor allocation strategies based on real workload traces and compare the results against those obtained using synthetic workload models. Our results reveal that the Greedy Available Busy List allocation strategy (GABL) performs better than all other non-contiguous allocation strategies in terms of job turnaround time for synthetic workload models, whereas the performance of Multiple Buddy Strategy (MBS) for real workload traces is superior to that of the other allocation strategies. This is because MBS performs well for power of two job sizes and contiguous allocation is explicitly sought in MBS for requests with sizes of the power of two. Moreover, the results indicate that the relative performance merits of the non-contiguous GABL strategy over the remaining non-contiguous allocation strategies become more noticeable as the message length increases.
Original language | English |
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Title of host publication | International Conference on Scalable Computing and Communications - The 8th International Conference on Embedded Computing, ScalCom-EmbeddedCom 2009 |
Pages | 633-639 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2009 |
Event | International Conference on Scalable Computing and Communications- 8th International Conference on Embedded Computing, ScalCom-EmbeddedCom 2009 - Dalian, China Duration: Sep 25 2009 → Sep 27 2009 |
Other
Other | International Conference on Scalable Computing and Communications- 8th International Conference on Embedded Computing, ScalCom-EmbeddedCom 2009 |
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Country | China |
City | Dalian |
Period | 9/25/09 → 9/27/09 |
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Software