GWS-A Collaborative Load-Balancing Algorithm for Internet-of-Things

被引：10

作者：

Xiao, Hongyu ^{[1
,2
]}

Zhang, Zhenjiang ^{[2
,3
]}

Zhou, Zhangbing ^{[4
]}

机构：

[1] Beijing Jiaotong Univ, Dept Elect & Informat Engn, Beijing 100044, Peoples R China

[2] Beijing Jiaotong Univ, Beijing Municipal Commiss Educ, Key Lab Commun & Informat Syst, Beijing 100044, Peoples R China

[3] Beijing Jiaotong Univ, Dept Software Engn, Beijing 100044, Peoples R China

[4] China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China

来源：

SENSORS | 2018年 / 18卷 / 08期

基金：

中国国家自然科学基金;

关键词：

collaborative; Internet-of-Things; fog computing; Nash bargaining solution; Pareto optimality; scheduling; time-sharing;

D O I：

10.3390/s18082479

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, and is based on the Nash bargaining solution (NBS) for a cooperative game between FCNs. Pareto optimality is achieved through the collaborative working of FCNs to improve the performance of every FCN. Lastly the simulation results demonstrate that the game-theory based work-stealing algorithm (GWS) outperforms the classical work-stealing algorithm (CWS).

引用

页数：17

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