Abstract
AbstractEnergy efficiency without performance degradation is a challenge in battery operated real-time systems. One way to achieve this is by optimizing scheduling parameters like preemptions and cache activities. In this work, we present an energy efficient variant of Least Laxity First scheduler – Least Laxity First with Reduced Preemptions – that reduces the number of preemptions in a schedule. We prove that our scheduler offers the same feasibility as LLF. We present extensive analysis through experimental results to show that our variant significantly reduces the number of preemptions. Our results also show that the number of preemptions in the schedule output by this algorithm is close to the minimum possible number. Our analysis addresses the following metrics: preemptions, cache impacts, decision points, response time, response time jitter, latency, time complexity and energy consumption. In this work the proposed algorithm is compared with dynamic priority scheduling algorithms like RM, EDF, nonstrict LLF and strict-LLF. The result shows that the proposed algorithm offers 4.25% of energy saving in comparison with EDF, RM and non-strict LLF and it offers 7% energy saving in comparison with strict-LLF. The result also shows that the proposed algorithm increases the scheduling utilization by 4% in comparison with EDF, RM and non-strict LLF and it increases scheduling utilization by 6% in comparison with strict-LLF.
Highlights
RATE Monotonic (RM) [1][2], Earliest Deadline First (EDF) [2][3] and Least Laxity First (LLF) [2][4] are the most widely used, discussed and evaluated periodic hard – real time priority driven online scheduling algorithms
We presented an energy efficient variant of Least Laxity First scheduler – Least Laxity First with Reduced Preemptions
We prove that our scheduler offers the same feasibility as LLF
Summary
RATE Monotonic (RM) [1][2], Earliest Deadline First (EDF) [2][3] and Least Laxity First (LLF) [2][4] are the most widely used, discussed and evaluated periodic hard – real time priority driven online scheduling algorithms. These scheduling algorithms focus on schedulability than other optimizations like idle time, preemptions and energy consumption [5 – 9]. Some of the widely adopted techniques to achieve energy efficiency in scheduling include optimization of idle time, preemptions and cache impacts in the schedule [8][15 – 20]. The time taken for preemptions in a schedule may add up to a significant delay in the execution of a process and affect its schedulability [24][25]
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