MONet: A framework for self-adaptive energy-aware middleware for dynamic wireless sensor network. Issue 4 (6th November 2017)

• Record Type: Journal Article
• Authors: Barka, Kamel; Bilami, Azeddine; Gourdache, Samir
• Is Part Of: International journal of pervasive computing and communications. Volume 13:Issue 4(2017)
• Page Start: 345
• Page End: 369
• Publication Date: 2017-11-06
• Subjects: WSNs -- EMOA -- Genetic algorithm (GA) -- MONet -- Agent -- TinyDDS; Ubiquitous computing -- Periodicals; Mobile computing -- Periodicals; Computer network protocols -- Periodicals; Computer network architectures -- Periodicals; Application software -- Development -- Periodicals; 004.6
• DOI: 10.1108/IJPCC-D-17-00009
• Languages: English
• ISSNs: 1742-7371

Abstract

Abstract : Purpose: The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet). Design/methodology/approach: In MONet, the middleware level of each network node autonomously adjusts its routing parameters according to dynamic network conditions and seeks optimal trade-offs among performance objectives for a balance of its global performance. MONet controls the cooperation between agents (network nodes) while varying transmission paths to reduce and distribute power consumption equitably on all the sensor nodes of network. MONet-runtime uses a modified TinyDDS middleware platform. Findings: Simulation results confirm that MONet allows power efficiency to WSN nodes while adapting their sleep periods and self-heal false-positive sensor data. Originality/value: The framework implementation is lightweight and efficient enough to run on resource-limited nodes such as sensor nodes.