Optimal Stochastic Coded Computation Offloading in Unmanned Aerial Vehicles Network

Wei Chong Ng; Wei Yang Bryan Lim; Jer Shyuan Ng; Suttinee Sawadsitang; Zehui Xiong; Dusit Niyato

Optimal Stochastic Coded Computation Offloading in Unmanned Aerial Vehicles Network

Computer Science and Game Theory 2021-10-29 v1

Authors: Wei Chong Ng , Wei Yang Bryan Lim , Jer Shyuan Ng , Suttinee Sawadsitang , Zehui Xiong , Dusit Niyato

Abstract

Today, modern unmanned aerial vehicles (UAVs) are equipped with increasingly advanced capabilities that can run applications enabled by machine learning techniques, which require computationally intensive operations such as matrix multiplications. Due to computation constraints, the UAVs can offload their computation tasks to edge servers. To mitigate stragglers, coded distributed computing (CDC) based offloading can be adopted. In this paper, we propose an Optimal Task Allocation Scheme (OTAS) based on Stochastic Integer Programming with the objective to minimize energy consumption during computation offloading. The simulation results show that amid uncertainty of task completion, the energy consumption in the UAV network is minimized.

Keywords

uav optimization vehicular networks optimal transport

Cite

@article{arxiv.2110.14873,
  title  = {Optimal Stochastic Coded Computation Offloading in Unmanned Aerial Vehicles Network},
  author = {Wei Chong Ng and Wei Yang Bryan Lim and Jer Shyuan Ng and Suttinee Sawadsitang and Zehui Xiong and Dusit Niyato},
  journal= {arXiv preprint arXiv:2110.14873},
  year   = {2021}
}

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To be published in IEEE Global Communications Conference

Optimal Stochastic Coded Computation Offloading in Unmanned Aerial Vehicles Network

Abstract

Keywords

Cite

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