Abstract | ||
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More computational power is offered by current real-time systems to cope with CPU intensive applications. However, this facility comes at the price of more energy consumption and eventually higher heat dissipation. As a remedy, these issues are being encountered by adjusting the system speed on the fly so that application deadlines are respected and also, the overall system energy consumption is reduced. In addition, the current state of the art of multi-core technology opens further research opportunities for energy reduction through power efficient scheduling. However, the multi-core front is relatively unexplored from the perspective of task scheduling. To the best of our knowledge, very little is known as of yet to integrate power efficiency component into real-time scheduling theory that is tailored for multi-core platforms. In this paper, we first propose a technique to find the lowest core speed to schedule individual tasks. The proposed technique is experimentally evaluated and the results show the supremacy of our test over the existing counterparts. Following that, the lightest task shifting policy is adapted for balancing core utilization, which is utilized to determine the uniform system speed for a given task set. The aforementioned guarantees that: (i) all the tasks fulfill their deadlines and (ii) the overall system energy consumption is reduced. |
Year | DOI | Venue |
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2012 | 10.1016/j.jpdc.2011.07.005 | J. Parallel Distrib. Comput. |
Keywords | Field | DocType |
multi-core system,system speed,energy reduction,energy consumption,uniform system speed,lowest core speed,power efficient rate monotonic,individual task,overall system energy consumption,lightest task,computational power,current real-time system,feasibility analysis,real time systems | Fixed-priority pre-emptive scheduling,Fair-share scheduling,Computer science,Parallel computing,Two-level scheduling,Rate-monotonic scheduling,Earliest deadline first scheduling,Dynamic priority scheduling,Energy consumption,Round-robin scheduling,Distributed computing | Journal |
Volume | Issue | ISSN |
72 | 1 | 0743-7315 |
Citations | PageRank | References |
16 | 0.62 | 23 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Nasro Min-Allah | 1 | 468 | 23.57 |
Hameed Hussain | 2 | 85 | 3.93 |
Samee Ullah Khan | 3 | 1605 | 81.01 |
Albert Y. Zomaya | 4 | 5709 | 454.84 |