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Dynamic Computation Offloading for MIMO Mobile Edge Computing Systems With Energy Harvesting
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DOI：10.1109/TVT.2021.3075018.png)
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摘要
En 中文
By providing spatial diversity gain, the incorporation of multiple antennas into mobile edge computing (MEC) systems can improve the transmission performance. Meanwhile, employing energy harvesting (EH) helps enhance the system sustainability. In this paper, we focus on multi-input multi-output (MIMO) MEC systems with EH and studies the computation offloading. The design objective is to minimize the time average of a weighted sum of energy consumption and execution delay, meanwhile stabilizing the battery energy queue. To this end, we formulate the problem as a statistic program and propose a dynamic computation offloading (DCO) algorithm in which the transmitter covariance matrix, CPU-cycle frequencies for local computing, and partial offloading ratio are jointly optimized. Based on Lyapunov optimization, the program is first transformed into a nonconvex per-time slot problem. Then, we solve it by the successive convex approximation (SCA) technique, where a sequence of convex problems are created and solved. Simulation results demonstrate that the proposed algorithm is asymptotically optimal and outperforms several benchmark schemes in terms of both the average system cost and task drop ratio.
Keyword:
Task analysis
Optimization
MIMO communication
Heuristic algorithms
Energy consumption
Delays
Servers
Mobile edge computing
MIMO
Lyapunov optimization
energy harvesting
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期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
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