Abstract

The growth of Device-to-Device (D2D) communications and the extensive use of Wireless Sensor Networks (WSNs) bring new problems such as spectral coexistence and spectrum saturation. Cognitive Radio (CR) appears as a paradigm to solve these problems. The introduction of CR into WSNs as a solution to the spectrum utilization problem could be used not only to increase the reliability of communications, but also to optimize energy consumption. The contribution of this paper is a cognitive lightweight strategy based on game theory and collaboration proposed to save energy consumption in Cognitive Wireless Sensor Networks (CWSNs). The proposed strategy takes advantage of the two main capabilities of CWSNs, the ability to adapt communication parameters, specifically channel allocation, and collaboration among devices. The decision making is modeled through a light noncooperative game designed for low resources networks. Despite the fact that the game used is a noncooperative game, the decision process takes advantage of the collaboration among CWSN nodes in a distributed way. Simulations over Castalia Simulator have been carried out in order to validate the strategy in different scenarios with different interference schemes showing increases in energy savings around 50% depending on the scenario.

Highlights

  • The increased use of smart Device-to-Device (D2D) communications and the introduction of the Internet of Things (IoT) give Wireless Sensor Networks (WSNs) a great influence on the new communication paradigm

  • The contribution of this paper is a cognitive lightweight strategy based on game theory and collaboration proposed to save energy consumption in Cognitive Wireless Sensor Networks (CWSNs)

  • The framework used in the simulation is composed of two fundamental elements: a CWSN simulator and low power Cognitive

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Summary

Introduction

The increased use of smart Device-to-Device (D2D) communications and the introduction of the Internet of Things (IoT) give Wireless Sensor Networks (WSNs) a great influence on the new communication paradigm. Assuring the reliability and energy survivability of the wireless networks is a main cornerstone for the introduction and the extensive use of WSNs into our daily lives. Energy consumption in WSNs is a known historical problem that has been addressed from different areas and on many levels [1]. This problem should be approached from the point of view of their own efficiency for survival. Optimizing the energy consumption of wireless networks could reduce their environmental impact considerably

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