Server selection schemes for service-oriented computing in mobile pervasive environment. (October 2016)

• Record Type: Journal Article
• Authors: Choudhury, Bikash; choudhury, Subhrabrata; Dutta, Animesh
• Is Part Of: Computers & electrical engineering. Volume 55(2016)
• Page Start: 73
• Page End: 87
• Publication Date: 2016-10
• Subjects: Service-oriented computing -- Pervasive system -- Server selection -- DCOP -- Multi-agent system; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2015.12.007
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: An efficient server-centric server selection scheme is proposed for small scenario. A client-centric scheme is proposed that outperforms the existing ones. The client-centric scheme does not guaranty optimal Nash Equilibrium (NE). A Mixed-strategy (MS) based solution is proposed that can attain more efficient NE. The MS based scheme performs better than existing and previously proposed schemes. Graphical abstract: Abstract: In this paper, we present a set of server selection schemes that includes all crucial components of resources available at each relevant node of the network to reach at the server selection decision and at the same time attempts to maximise the system-wide resource utilisation. First in the series, a server-centric scheme is proposed that formulates the problem as distributed constraint optimisation problem (DCOP) and solves it using Fast-max-sum (FMS) algorithm. Though it does not scale well in large network scenario yet it provides an estimate of the optimal values of performance metrics achievable under a specific scenario. Next, a client-centric scheme is proposed that outperforms the existing ones but does not guaranty to attain optimal Nash Equilibrium (NE). This motivates us to design another client-centric scheme that can avoid the price of anarchy by attaining superior NE of mix strategies.