QoS and Energy Aware Cooperative Routing Protocol for Wildfire Monitoring Wireless Sensor Networks

Mohamed Maalej,Hichem Besbes,Sofiane Cherif

doi:10.1155/2013/437926

Abstract

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

Highlights

The automatic monitoring of wildfire generally supports multimodal observations
Simulation results show that when comparing network energy consumption between the two algorithms for the same network architecture, network energy consumption is saved for the received signal strength indicator (RSSI)/energy CC algorithm compared to the multiagent reinforcement-learning (MRL)-CC algorithm
To help automatic monitoring of wildfire, we propose in this paper to deploy Wireless sensor networks (WSN)

Summary

Introduction

The automatic monitoring of wildfire generally supports multimodal observations. This is due to the extent of the areas to be covered and the difficulty of detecting fire. The second problem which arises in this type of environment is the fading effect due to the presence of trees leading to an important shadowing phenomenon To solve these problems, we propose a new methodology to design and optimize WSN based on both energy conservation and consideration of the quality of transmission for choosing the routing protocol. MRL-CC has been based on internode distance and packet delay to enhance the QoS metrics It does not care about energy consumption and network lifetime which are important components for energy efficiency. We design cooperative communication routing protocol based on both energy consumption and QoS. The QoS is measured by the absolute received signal strength indicator (RSSI) To integrate these two parameters in the routing protocol, we use a competitive/opponent mechanism implemented at each node by the multiagent reinforcement-learning (MRL) algorithm.

Cooperative Communication in WSN Using Reinforcement Learning

Cooperative Communication Concept in WSN

Performance Evaluation

Li-ion AA batteries 2

Conclusions