移动边缘网络下服务缓存与资源分配联合优化策略

doi:10.11959/j.issn.1000-436x.2023020

通信学报 ›› 2023, Vol. 44 ›› Issue (1): 64-74.doi: 10.11959/j.issn.1000-436x.2023020

移动边缘网络下服务缓存与资源分配联合优化策略

龙隆¹, 刘子辰¹, 陆在旺¹^,², 张玉成¹^,², 李蕾¹^,²

¹ 中国科学院计算技术研究所，北京 100190
² 中国科学院大学计算技术研究所，北京 100049

修回日期:2022-12-05 出版日期:2023-01-25 发布日期:2023-01-01
作者简介:龙隆（1988- ），男，山西长治人，博士，中国科学院计算技术研究所工程师，主要研究方向为移动通信、移动边缘计算、计算与通信融合、农业模型与算法等
刘子辰（1984- ），男，山东临沂人，博士，中国科学院计算技术研究所工程师，主要研究方向为农机大数据、农业生产执行系统、图数据库系统
陆在旺（1992- ），男，山东潍坊人，中国科学院大学博士生，主要研究方向为智能通信、强化学习、多机调度、农业机器人等
张玉成（1981- ），男，江苏淮安人，博士，中国科学院计算技术研究所正高级工程师，主要研究方向为智能通信、智能农机、复杂农业系统控制理论与方法
李蕾（1987- ），女，河南洛阳人，中国科学院大学博士生，主要研究方向为人工智能、智慧农业等
基金资助:
国家重点研发计划基金资助项目(2022YFD2001004)

Joint optimization strategy of service cache and resource allocation in mobile edge network

Long LONG¹, Zichen LIU¹, Zaiwang LU¹^,², Yucheng ZHANG¹^,², Lei LI¹^,²

¹ Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
² Institute of Computing Technology, University of Chinese Academy of Sciences, Beijing 100190, China

Revised:2022-12-05 Online:2023-01-25 Published:2023-01-01
Supported by:
The National Key Research and Development Program of China(2022YFD2001004)

摘要/Abstract

摘要：

针对边缘服务器的计算与存储资源有限，过多的任务卸载将使其计算能力与负载能力不匹配，从而导致任务处理时延增加的问题，研究了基于多用户、边缘服务器以及云服务器组成的三层网络架构下的任务卸载与存储资源联合优化问题以降低系统整体时延。由于该问题为混合整数非线性问题，因此提出了一种服务缓存与资源分配联合优化策略。首先，将原问题的连续与离散变量进行解耦为2个子问题，即服务缓存决策问题以及计算资源与通信资源联合优化问题。然后，通过重构线性化方法、松弛法以及凸优化方法对2个子问题进行交替优化迭代获得近似最优解。仿真结果表明，所提策略在低复杂度情况下能够获得近似最优解，并且与其他策略相比时延降低10%左右。

关键词: 移动边缘计算, 多级网络, 服务缓存, 资源分配

Abstract:

Aiming at the problem that computing and storage resources of edge node in a mobile edge computing (MEC) system were limited, and excessive task offloading would cause the mismatch between the computing capacity and the load capacity of the edge server, resulting in the increase of task processing delay, the joint optimization of task offloading and storage resources under the three-layer network architecture composed of multi-user, edge server and cloud server was studied to reduce the overall system delay.For the problem was a mixed integer nonlinear problem, a joint optimization strategy of service caching and resource allocation was proposed.First, the continuous and discrete variables of the original problem were decoupled into two sub-problems, namely, the service cache decision problem and the joint optimization problem of computing resources and communication resources.Then, the linear reconstruction, relaxation method and convex optimization method were used to alternately optimize the two sub-problems to obtain the near-optimal solution.Simulation results demonstrate that the proposed strategy can obtain a near-optimal performance with low complexity, and can reduce up to 10% of the task duration compared with other strategies.

Key words: mobile edge computing, multilevel network, service cache, resource allocation

中图分类号:

TN929.52

龙隆, 刘子辰, 陆在旺, 张玉成, 李蕾. 移动边缘网络下服务缓存与资源分配联合优化策略[J]. 通信学报, 2023, 44(1): 64-74.

Long LONG, Zichen LIU, Zaiwang LU, Yucheng ZHANG, Lei LI. Joint optimization strategy of service cache and resource allocation in mobile edge network[J]. Journal on Communications, 2023, 44(1): 64-74.

图/表 7

图1

表1

仿真参数设置"

参数	数值
终端设备数L/个	10
上行链路带宽B/MHz	20
基站通信范围边长d/m	500
计算任务输入数据 $c_{A_{i}}^{input}$ /KB	U[100,200]
计算服务种类K/种	10
移动终端发射功率P_i,s /dBm	23
路径损耗r	4
噪声功率δ²/ (dBm·Hz^-1)	-174
边缘服务器的计算能力F/Megacycle	30 000
终端的计算能力 $f_{i}^{local}$ /Megacycle	N(500,50)
执行一个任务所需的服务缓存c_A /GB	U[30,80]
边缘服务器的最大存储能力C/GB	500
服务器与远端云间传输速率R/(Mbit·s^-1)	1

表1

图2

图3

图4

图5

图6

参考文献 8

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移动边缘网络下服务缓存与资源分配联合优化策略

Joint optimization strategy of service cache and resource allocation in mobile edge network

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