计算机科学
Lyapunov优化
资源配置
移动边缘计算
马尔可夫决策过程
能源消耗
最优化问题
排队
分布式计算
数学优化
服务器
实时计算
算法
马尔可夫过程
计算机网络
人工智能
工程类
数学
李雅普诺夫方程
李雅普诺夫指数
统计
混乱的
电气工程
作者
Rong Chai,S. X. Zhang,Wenhang Jiang
标识
DOI:10.1109/pimrc56721.2023.10293930
摘要
Deploying edge computing servers on satellites to provide computing services for Internet of thing (IoT) devices will be an indispensable example for satellite IoT (SIoT) systems. In this paper, we study task offloading problem for SIoT systems. Considering the IoT devices and satellites task queue state and satellite-ground channel state, under the conditions of meeting the limited computing resources and transmit power, and the queue stability, the task offloading problem for SIoT systems is formulated as a minimizing the long-term average system energy consumption problem. In order to solve this problem, We first use Lyapunov optimization method to decouple the joint optimization problem into three subproblems, i.e., computing resource allocation subproblem of IoT devices, computing resource allocation subproblem of satellites, joint task offloading and power allocation subproblem. For computing resource allocation subproblems, we apply Lagrange dual algorithm to solve them. To solve joint task offloading and power allocation subproblem, we formulate it as a Markov decision process (MDP), and propose a parameterized deep Q-network (PDQN)-based task offloading and power allocation algorithm. Finally, the simulation results show that the proposed algorithm has good performance in optimizing the long-term average system energy consumption.
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