Adaptive Computation Scaling and Task Offloading in Mobile Edge Computing | IEEE Conference Publication | IEEE Xplore

Adaptive Computation Scaling and Task Offloading in Mobile Edge Computing


Abstract:

The energy consumption and applications' execution latency of mobile devices (MDs) can be improved by migrating application tasks to a nearby edge device. In this paper, ...Show More

Abstract:

The energy consumption and applications' execution latency of mobile devices (MDs) can be improved by migrating application tasks to a nearby edge device. In this paper, we propose an optimization framework to investigate the scenario when a MD can offload tasks to multiple access points (APs) and scale its central process unit (CPU) frequency. Firstly, the optimal solution is derived from an exhaustive search based approach; and then a semidefinite relaxation (SDR) based approach is proposed to efficiently solve the problem. The obtained results from our simulation indicate that the SDR-based algorithm is able to achieve close-to-optimal performance. We also show that our proposed scheme can reduce the MD's energy consumption and tasks' execution latency, by taking advantage of having multiple APs and flexible CPU frequency.
Date of Conference: 19-22 March 2017
Date Added to IEEE Xplore: 11 May 2017
ISBN Information:
Electronic ISSN: 1558-2612
Conference Location: San Francisco, CA, USA

References

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