Time-Optimized Task Offloading Decision Making in Mobile Edge Computing

Mobile Edge Computing application domains such as vehicular networks, unmanned aerial vehicles, data analytics tasks at the edge and augmented reality have recently emerged. Under such domains, while mobile nodes are moving and have certain tasks to be offloaded to Edge Servers, choosing an appropriate time and an ideally suited server to guarantee the quality of service can be challenging. We tackle the offloading decision making problem by adopting the principles of Optimal Stopping Theory to minimize the execution delay in a sequential decision manner. A performance evaluation is provided by using real data sets compared with the optimal solution. The results show that our approach significantly minimizes the execution delay for task execution and the results are very close to the optimal solution.

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