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

• Published in: Sensors (Basel, Switzerland) Vol. 18; no. 8; p. 2479
• Main Authors: Xiao, Hongyu, Zhang, Zhenjiang, Zhou, Zhangbing
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 31.07.2018; MDPI
• Subjects: Algorithms; Collaboration; collaborative; Economic models; fog computing; Internet-of-Things; Nash bargaining solution; Pareto optimality; scheduling; time-sharing; Internet-of-Things; fog computing; collaborative; Pareto optimality; scheduling; time-sharing; Nash bargaining solution
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18082479

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).