Abstract
Wireless sensor networks (WSNs) are among the most popular wireless technologies for sensor communication purposes nowadays. Usually, WSNs are developed for specific applications, either monitoring purposes or tracking purposes, for indoor or outdoor environments, where limited battery power is a main challenge. To overcome this problem, many routing protocols have been proposed through the last few years. Nevertheless, the extension of the network lifetime in consideration of the sensors capacities remains an open issue. In this paper, to achieve more efficient and reliable protocols according to current application scenarios, two well-known energy efficient protocols, i.e., Low-Energy Adaptive Clustering hierarchy (LEACH) and Energy–Efficient Sensor Routing (EESR), are redesigned considering neural networks. Specifically, to improve results in terms of energy efficiency, a Levenberg–Marquardt neural network (LMNN) is integrated. Furthermore, in order to improve the performance, a sub-cluster LEACH-derived protocol is also proposed. Simulation results show that the Sub-LEACH with LMNN outperformed its competitors in energy efficiency. In addition, the end-to-end delay was evaluated, and Sub-LEACH protocol proved to be the best among existing strategies. Moreover, an intrusion detection system (IDS) has been proposed for anomaly detection based on the support vector machine (SVM) approach for optimal feature selection. Results showed a 96.15% accuracy—again outperforming existing IDS models. Therefore, satisfactory results in terms of energy efficiency, end-to-end delay and anomaly detection analysis were attained.
Highlights
Wireless sensor networks (WSNs) are among the most popular wireless communication networks, where sensor nodes represent the main backbone [1,2]
For experimentation of the performance of the proposal, we have considered a wellknown standard dataset, i.e., NSLKDD data-set [37], which is freely available and mostly used for intrusion detection problems
Two quality of services-based parameters such as energy efficiency and end-to-end delay were considered for the evaluation of the proposed protocols
Summary
Wireless sensor networks (WSNs) are among the most popular wireless communication networks, where sensor nodes represent the main backbone [1,2]. Most WSNs are designed for a specific application, and generally, their sensor nodes present some basic functionalities such as sensing, processing, computation and communication. WSNs are application-based communication networks—i.e., according to a specific application, sensors are deployed in the monitoring field and the communication network is built. Examples of monitoring applications can be found in patient health monitoring, the chemical industry for toxic gas monitoring and the rubber industry. Tracking applications such as pet tracking, wild species tracking and man tracking can be cited for WSN technologies. The technology for WNSs has drastically changed in recent times, providing more innovative platforms for cost-effective and more efficient communication networks
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