面向边缘增强分布式电力无线传感网的资源分配

doi:10.11930/j.issn.1004-9649.202304069

中国电力 ›› 2023, Vol. 56 ›› Issue (8): 77-85,98.DOI: 10.11930/j.issn.1004-9649.202304069

• 面向电网设备状态感知的低功耗无线传感网技术及应用 • 上一篇下一篇

面向边缘增强分布式电力无线传感网的资源分配

吴钢¹, 周金辉¹, 李慧²

1. 国网浙江省电力有限公司电力科学研究院, 浙江杭州 310014;
2. 中国科学院上海微系统与信息技术研究所, 上海 200050

收稿日期:2023-04-19 修回日期:2023-07-08 发布日期:2023-08-28
作者简介:吴钢（1974—），男，硕士，高级工程师，从事电网数字化和智能化研究，E-mail：wugang_zj@163.com;周金辉（1983—），男，博士，高级工程师（教授级），从事配电网数字化与智能化技术与应用研究，E-mail：zhoujinhui_hz@163.com;李慧（1986—），女，通信作者，博士，研究员，从事无线传感网与人工智能技术研究，E-mail：hui.li@mail.sim.ac.cn
基金资助:
国家电网有限公司科技项目（电力物联终端智能化漏洞挖掘关键技术研究，5700-202219198A-1-1-ZN）。

Resource Allocation for Edge-enhanced Distributed Power Wireless Sensor Network

WU Gang¹, ZHOU Jinhui¹, LI Hui²

1. State Grid Zhejiang Electric Power Corporation Research Institute, Hangzhou 310014, China;
2. Shanghai Institute of Microsystem and Information Technology, CAS, Shanghai 200050, China

Received:2023-04-19 Revised:2023-07-08 Published:2023-08-28
Supported by:
This work is supported by Science and Technology Project of SGCC (Research on Key Technologies for Intelligent Vulnerability Mining of Power IoT Terminals, No.5700-202219198A-1-1-ZN).

摘要/Abstract

摘要： 针对目前传统电力无线传感网络中出现的访问时延高、能耗大以及用户服务质量恶化等问题，引入移动边缘计算（mobile edge computing，MEC），建立访问时延和网络能耗联合优化模型，目标为最小化时延和能耗的联合函数；随后在射频拉远单元的剩余资源量、负载排队等待时延和中心单元/分布单元的剩余资源量的共同约束下，通过控制负载转移过程中的等待时延，从而确定中心单元/分布单元的总资源处理量；接着根据MEC服务器的资源利用率，通过减少活跃的MEC服务器数量，来减少传感器设备的能耗。仿真分析了权重系数大小对目标函数的影响，以及算法在不同业务流量和时刻下的对比。结果表明：提出的分配机制在降低访问时延和设备能耗方面，效果优于其他对比算法。该机制能有效提高传感器的通信质量和系统工作效率，延长传感器设备寿命，降低网络成本开销。

关键词: 电力无线传感网络, 移动边缘计算, 能耗感知, 时延感知, 负载均衡

Abstract: Aiming at the problems of high access latency, high energy consumption, and deteriorating user service quality in traditional wireless power sensor networks, the mobile edge computing (MEC) is introduced to establish a joint optimization model of access latency and network energy consumption, with objective to minimize the joint function of latency and energy consumption. Then, the total resource processing capacity of the central unit/distribution unit is determined by controlling the waiting latency in the load transfer process under the common constraints of the remaining resources of the RF remote unit, the load queuing latency, and the remaining resources of the central unit/distribution unit. And then, based on the resource utilization of the MEC server, the energy consumption of the sensor devices is reduced by reducing the number of active MEC servers. The influence of the weight coefficient on the objective function and the comparison of the algorithm under different traffic flows and times are analyzed. The results show that the proposed allocation mechanism is better than other comparison algorithms in reducing access latency and energy consumption. Therefore, this mechanism can effectively improve the communication quality of the sensors and the efficiency of the system, extend the life of the sensor equipment, and reduce the network cost.

Key words: power wireless sensor networks, mobile edge computing, energy consumption aware, delay aware, load balancing

吴钢, 周金辉, 李慧. 面向边缘增强分布式电力无线传感网的资源分配[J]. 中国电力, 2023, 56(8): 77-85,98.

WU Gang, ZHOU Jinhui, LI Hui. Resource Allocation for Edge-enhanced Distributed Power Wireless Sensor Network[J]. Electric Power, 2023, 56(8): 77-85,98.

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面向边缘增强分布式电力无线传感网的资源分配

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