[1]葛欣炜,段聪颖,陈思光.基于雾计算的能耗最小化公平计算迁移研究[J].计算机技术与发展,2022,32(03):107-113.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 018]
　GE Xin-wei,DUAN Cong-ying,CHEN Si-guang.Fog Computing Based Energy Minimization and Fair Computation Offloading Mechanism[J].,2022,32(03):107-113.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 018]
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基于雾计算的能耗最小化公平计算迁移研究()
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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03期
页码:
107-113
栏目:
网络与安全
出版日期:
2022-03-10

文章信息/Info

Title:
Fog Computing Based Energy Minimization and Fair Computation Offloading Mechanism
文章编号:
1673-629X(2022)03-0107-07
作者:
葛欣炜1 ; 段聪颖1 ; 陈思光1; 2
1. 南京邮电大学 江苏省宽带无线通信和物联网重点实验室,江苏 南京 210003;
2. 南京邮电大学 江苏省通信与网络技术工程研究中心,江苏 南京 210003
Author(s):
GE Xin-wei1 ; DUAN Cong-ying1 ; CHEN Si-guang1 ; 2
1. Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;
2. Jiangsu Engineering Research Center of Communication and Network Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
雾计算; 计算迁移; 公平性; 能耗; 性能优化
Keywords:
fog computing; computation offloading; fairness; energy consumption; performance optimization
分类号:
TP393
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 03. 018
摘要:
针对现有雾计算网络的迁移优化研究主要集中在降低任务计算时延及能量消耗上,缺乏融合考虑雾节点选择的公平性, 该文提出了一种面向雾计算网络的能耗最小化公平计算迁移机制。 具体地,构建了一个最小化所有任务完成总能耗的优化问题,充分考虑了任务迁移比、传输功率和雾节点选择的联合优化;基于上述优化问题,提出一种任务迁移候选目的节点集生成算法,通过二分法获得各个雾节点在相应延迟约束下的最低能耗及其对应的迁移比与传输功率;进一步,为了在低能耗与目的节点选择公平性之间取得平衡,基于公平调度指标,提出一种目的节点公平选择算法,以低能耗且公平的方式实现计算任务分配。 最后,仿真结果表明,该机制可以在总能耗较低的情况下保证各个雾节点之间的公平性,较最大等效处理速率机制,平均雾节点存活率提升了 10. 9% 。
Abstract:
The existing research works on offloading optimization of fog computing networks mainly focus on reducing task computation latency and energy consumption,which ignore the joint consideration of the fairness selection of fog? ? ? ?node. Therefore,we propose an energy minimization and fair computation offloading mechanism for fog computing networks. Specifically,an optimization problem with the minimization of total energy consumption for all tasks is formulated,in which the optimization allocation of task offloading ratio,transmission power and fog node selection are jointly considered. According to such optimization problem,a candidate set generation algorithm of destination node for task offloading is developed,and the lowest energy consumption of each fog node under the corresponding delay constraint,the corresponding offloading ratio and transmission power are obtained through the bisection method. Furthermore,in order to make a trade off between the low energy consumption and fair selection of destination node,based on fair scheduling indicator,a fair selection algorithm of destination node is proposed to realize the allocation of computation tasks in a low-energy and fair manner. Finally,the simulation results show that this mechanism can ensure the fair selection of the fog node under the condition of low total energy consumption,and the survival rate of fog node is enhanced by 10. 9% on average as compared with the maximum equivalent processing rate mechanism.

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更新日期/Last Update: 2022-03-10