A Multi-Cooperative-Based Approach to Manage Communication in Wireless Instrumentation Systems

被引：4

作者：

Hamani, Nacer ^{[1
]}

Jamont, Jean-Paul ^{[2
]}

Occello, Michel ^{[2
]}

Ben-Yelles, Choukri-Bey ^{[2
]}

Lagreze, Andre ^{[2
]}

Koudil, Mouloud ^{[1
]}

机构：

[1] Ecole Natl Super Informat, Algiers 16301, Algeria

[2] Univ Grenoble Alpes, Lab Concept & Integrat Syst, F-26000 Valence, France

来源：

IEEE SYSTEMS JOURNAL | 2018年 / 12卷 / 03期

关键词：

Agents-based systems; ant colony optimization (ACO); multi-agent systems; wireless sensor networks (WSNs); SENSOR NETWORKS; ROUTING ALGORITHM; OPTIMIZATION;

D O I：

10.1109/JSYST.2017.2721220

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Wireless instrumentation systems are a collection of resource-constrained nodes in charge of sensing, processing, and transmitting data. They are often battery powered, and consequently, subject to energy constraints. Since communication is the most energy-consuming task, efforts have to be made during the routing process in order to maximize the network lifespan and avoid network partitioning. In this context, the multi-wireless-agent communication (MWAC) model provides a self-organization process for managing communication in this kind of instrumentation system. Given an organization and a node, MWAC determines a single path to route messages to the destination. This may cause congestions for large data flows. This paper introduces antMWAC, a model designed to improve MWAC. Ant colony optimization is used to balance the traffic load on wireless nodes and insure a multipath routing. Ants interact with nodes to make the communication more efficient. The cooperation between them is increased to find a tradeoff between new path discovering and path reinforcement. The aim is to allow the nodes exploiting the information routed by ants and modifying ant decision parameters. Experiments show that antMWAC diversifies the nodes participating in routing operations, reducing node congestion.

引用

页码：2174 / 2185

页数：12

共 45 条

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