Optimal Information Extraction in Energy-Limited Wireless Sensor Networks

2004 ◽  
Vol 22 (6) ◽  
pp. 1121-1129 ◽  
Author(s):  
F. Ordonez ◽  
B. Krishnamachari
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Information Extraction ◽  
Wireless Sensor ◽  
Optimal Information

scholarly journals Intelligent Communication in Wireless Sensor Networks

2018 ◽  
Vol 10 (9) ◽  
pp. 91 ◽  
Author(s):  
Mostefa Bendjima ◽  
Mohammed Feham
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Communication Architecture ◽  
Package Delivery ◽  
Optimal Information ◽  
Intelligent Communication

Wireless sensor networks (WSN) are designed to collect information by means of a large number of energy-limited battery sensor nodes. Therefore, it is important to minimize the energy consumed by each sensor, in order to extend the network life. The goal of this work is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent is sent to each sensor in order to process the information and to cooperate with neighboring sensors while mobile agents (MA) can be used to reduce information shared between source nodes (SN) and send them to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the multi-agent system (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the sensors of the network have been grouped into sectors. For each MA, we have established an optimal itinerary, consuming a minimum amount of energy with data aggregation efficiency in a minimum time. Successive simulations in large-scale wireless sensor networks through the SINALGO (published under a BSD license) simulator show the performance of the proposed method, in terms of energy consumption and package delivery rate.

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