Lyapunov-Optimized and Energy-Constrained Stable Online Computation Offloading in Wireless Microtremor Sensor Networks

Lyapunov优化 计算机科学 瓶颈 最优化问题 无线传感器网络 计算 实时计算 数学优化 分布式计算 算法 人工智能 计算机网络 数学 嵌入式系统 Lyapunov重新设计 李雅普诺夫指数 混乱的
作者
Ruyun Tian,Hongyan Xing,Yihan Cao,Huaizhou Zhang
出处
期刊:IEEE Transactions on Signal and Information Processing over Networks [Institute of Electrical and Electronics Engineers]
卷期号:10: 83-93 被引量:1
标识
DOI:10.1109/tsipn.2024.3355748
摘要

The microtremor survey method (MSM) holds great potential for obtaining subsurface shear wave velocity structures in exploration geophysics. However, the lack of an instant imaging mechanism with local fast computation and processing has become a significant bottleneck hindering the development of MSM. In instant imaging tasks, the computational resources of ordinary nodes employed for imaging are often limited. In this paper, we consider a single-point microtremor array network with time-varying wireless channels and stochastic imaging task data arrivals in sequential time frames. In particular, we aim to design an online computation offloading algorithm to maximize the network data processing capability and optimize service quality subject to the long-term data queue stability and average power constraints. We formulate the problem as a the minimum delay problem that jointly determines the binary offloading and system resource allocation decisions in sequential time frames. To address the coupling in the decisions of different time frames, we propose a novel framework named LyECCO that combines the Lyapunov optimization and energy consumption optimization, solve the binary offloading problems with very low computational complexity. Simulation results show the feasibility of the LyECCO, which achieves optimal computation performance while stabilizing all queues in the system.
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