A Variation-Aware Approach for Task Allocation in Wireless Distributed Computing Systems

Wireless distributed computing (WDC) enables the radio nodes with reduced computing abilities to cooperate in processing complex computational tasks for minimizing the overall processing latency (makespan). However, the uncertainty of the dynamic mobile wireless environment, which is not an issue for the traditional distributed computing, poses a challenge for WDC. In this paper, a variation-aware approach for WDC is proposed to determine the task allocation by considering the heterogeneous computing capability of the radio nodes as well as the impact of the radio environment. To this end, the transmission latency is characterized as a random variable that depends on the channel fading and the transport protocol. A variation-aware task graph analysis is proposed for the estimation of the makespan's distribution. The evolutionary algorithms are employed for the allocation mapping. We use simulation results to affirm makespan estimation improvement of the proposed approach compared with the traditional deterministic approach, and give insights on the dominating factors for the improvement(1).