Probabilistic Loop Scheduling for Applications with Uncertain Execution Time
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IEEE/ACM Transactions on Networking (TON)
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Energy and delay are critical issues for wireless sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime. Due to the uncertainties in execution time of some tasks, this paper models each varied execution time as a probabilistic random variable and incorporating applications' performance requirements to solve the MAP (Mode Assignment with Probability) problem. Using probabilistic design, we propose an optimal algorithm to minimize the total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The experimental results show that our approach achieves significant energy saving than previous work. For example, our algorithm achieves an average improvement of 32.6% on total energy consumption