Sensor Data Analysis and Management

7 A Quantum-Behaved Particle-Swarm-Optimization-Based KNN Classifier for Improving WSN Lifetime

Ajmi Nader, Helali Abdelhamid, Mghaieth Ridha

Micro-Optoelectronic and Nanostructures Laboratory, University of Monastir, Faculty of Sciences of Monastir, Tunisia

7.1 Introduction

Currently, the new technology called Internet of things (IoT) is seen to be successful in many fields. This technology is the result of the development and combination of different technologies where wireless sensor networks (WSNs) [1] are recognized as key enablers. The use of WSNs is increasing day by day and has gained a lot of research interest in various practical applications in domains such as healthcare [2], military defense [3], environment [4], monitoring [5], and industries [6]. A typical sensor network contains a set of tiny devices that are deployed in a two-dimensional area in a random manner to monitor a specific phenomenon such as humidity, temperature, motion, vibration, pressure, etc. The general architecture of WSN is shown in Figure 7.1. Some of the constraints of WSNs include limited communication range, lower data rates, and higher energy consumption. But the main challenge with WSNs is to extend the network lifetime.

Figure 7.1 The general architecture of WSNs.

There are many previous techniques proposed in different ways to resolve thisissue. Among them, classification algorithms ...