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

Hongyu Xiao; Zhenjiang Zhang; Zhangbing Zhou

doi:10.3390/s18082479

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

Sensors (Basel). 2018 Jul 31;18(8):2479. doi: 10.3390/s18082479.

Authors

Hongyu Xiao^{1

2}, Zhenjiang Zhang^{3

4}, Zhangbing Zhou⁵

Affiliations

¹ Department of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China. [email protected].
² Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing 100044, China. [email protected].
³ Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing 100044, China. [email protected].
⁴ Department of Software Engineering, Beijing Jiaotong University, Beijing 100044, China. [email protected].
⁵ School of Information Engineering, China University of Geosciences at Beijing, Beijing 100083, China. [email protected].

Abstract

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).

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