[1]赵尚维康,孙 君.工业物联网中基于 SMDP 的协同卸载方案[J].计算机技术与发展,2022,32(09):76-81.[doi:10. 3969 / j. issn. 1673-629X. 2022. 09. 012]
　ZHAO Shang-wei-kang,SUN Jun.Multi-MEC Collaborative Computing Unloading Scheme Based on SMDP in Industrial Internet of Things[J].,2022,32(09):76-81.[doi:10. 3969 / j. issn. 1673-629X. 2022. 09. 012]
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工业物联网中基于 SMDP 的协同卸载方案()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年09期
页码:
76-81
栏目:
软件技术与工程
出版日期:
2022-09-10

文章信息/Info

Title:
Multi-MEC Collaborative Computing Unloading Scheme Based on SMDP in Industrial Internet of Things
文章编号:
1673-629X(2022)09-0076-06
作者:
赵尚维康; 孙 君
南京邮电大学 江苏省无线通信实验室,江苏 南京 210003
Author(s):
ZHAO Shang-wei-kang; SUN Jun
Jiangsu Key Laboratory of Wireless Communications,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
工业物联网; 边缘计算; MDP; 计算卸载; 资源分配
Keywords:
industrial Internet of things; edge computing; Markov decision process; computation offloading; resource allocation
分类号:
TP302;TN913
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 09. 012
摘要:
为解决工业物联网(IIoT) 场景中计算资源紧缺的问题,在 IIoT 中引入边缘计算技术,充分利用并合理分配多接入边缘计算( MEC)服务器有限的计算能力解决 IIoT 中部分计算任务。首先通过分析 IIoT 中工业设备进行服务请求和小区范围内的MEC服务器接受服务请求这一过程,构建了多 MEC 协同计算卸载模型;其次,基于模型中需要分析复杂的系统环境信息并进行序列决策的特点,将系统时延和能耗总收益最大化的资源分配问题构建为半马尔可夫决策过程( SMDP) ;然后依据边缘网络中的通信传输时延和 MEC 计算资源构建折扣奖励函数,利用贝尔曼方程分析系统状态并得到状态值函数;最后根据状态值函数和折扣奖励,通过 SMDP 的状态值迭代获得最佳卸载和资源分配方案。 仿真结果表明,所提方案优化了系统拒绝服务率以及系统效益。
Abstract:
In order to solve the shortage of computing resources in the Industrial Internet of Things ( IIoT) scenario,we introduce edge computing technology into IIoT,makes full use of and reasonably allocates the limited computing power of multi-access edge computing( MEC) server? ? to solve some computing tasks in IIoT. Firstly,we construct a multi MEC collaborative computing unloading model byanalyzing the process of service request by industrial equipment in IIoT and service request received by MEC server in the cell. Secondly,based on the characteristics of complex system environment information and sequential decision - making in the model, the resourceallocation problem of maximizing the total return of system delay and energy consumption is constructed as a semi Markov decision process ( SMDP) . Then,according to the communication transmission delay and MEC computing resources in the edge network,the discount reward function is constructed, the system state is analyzed by Bellman equation, and the state value function is obtained.Finally,according to the state value function and discount reward,the best unloading and resource allocation scheme is obtained through the state value iteration of SMDP. Simulation results show that the proposed scheme optimizes the system denial of service rate and system benefit.

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更新日期/Last Update: 2022-09-10