Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks

Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks

Sunitha R., Chandrika J.
Copyright: © 2021 |Pages: 15
DOI: 10.4018/IJDCF.20210901.oa8
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Abstract

The exponential growth of the internet of things and united applications have renewed the scholarly world to grow progressively proficient routing strategies. Quality of service (QoS) and reduced power consumption are the major requirements for effective data transmission. The larger part of the applications nowadays including internet of things (IoT) communication request power effective and QoS-driven WSN configuration. In this paper, an exceptionally strong and effective evolutionary computing allied WSN routing convention is designed for QoS and power effectiveness. The proposed routing convention includes proficient capacity called network condition-based malicious node detection. It adventures or mines the dynamic node/network parameters to recognize malignant nodes. Experimentation is done using network simulator tool NS2. Results ensure that the proposed routing model accomplishes higher throughput, low energy utilization, and low delay that sustains its suitability for real-time WSN.
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1. Introduction

The exponentially swift in wireless communication systems and associated applications have revitalize the research-industry to develop progressively capable and strong routing technique to fulfil growing demands. Contemporarily, the modern era of human lifestyle cannot be assumed without having communication system where each known and unknown intelligence will be utilized by every user to share information among multiple peers by making optimistic decision. There exist many applications include wireless sensor network components are military, Healthcare, Smart industries, spatio-temporal, smart agricultural, smart home, SCADA, smart city, etc (Azlan & Al-Anbuky, 2015; Ehsan & Hamdaoui, 2012; Medeiros de Ara’ujo & Becker, 2011; Spachos et al., 2015). On the other hand, to increase the QoS communication requirement by providing timely, reliable, and power efficient communication among the several deployed nodes in the network area as there is a demand for significant development of network computing and dynamic decision-making applications. Machine-to-Machine (M2M) communication and Internet-of-Things (IoT) are two among the recently developed technologies which apply wireless communication protocols as a backbone network to provide real-time data transmission among nodes to provide ideal energetic decision making (Ehsan & Hamdaoui, 2012). Its significances have expanded towards Big Data analytics, Industrial Interaction, Monitoring and Controlling, Enhanced Surveillance functions and so forth. To fulfill above stated requirements, distinctive network prototypes have been proposed, among which WSN is the overwhelming one.

WSN being a decentralized and infrastructure-less communication paradigm includes various sensor nodes distributed over the network that work agreeably to transmit detected data from source to the sink node in one or many hops. However, dynamic nature of the network and the node situations regularly impacts transmission effectively, compelling WSN to experience connection-outage, congestion, packet drop and retransmission (Medeiros de Ara’ujo & Becker, 2011). Such challenges frequently result into more energy-dissipation causing network life-time degradation and QoS violence. On the other hand, Quality of Service and Quality of Experience (QoE) being the unavoidable requests of the traditional communication frameworks require WSN to guarantee ideal information transmission over the network. Along with QoS provision, WSN being battery operated network needs ideal routing mechanism to reduce packet loss and retransmission probability and the sub-sequent node death rate to hold maximum network lifetime (Ehsan & Hamdaoui, 2012)(Medeiros de Ara’ujo & Becker, 2011)(Sen & Ukil, 2009). Sensor nodes are very sensitive to the vulnerabilities and often deployed in some dangerous environments. These nodes can get failure due to the hardware problem of any damages or by draining the energy. In the wireless networks, the node failure will be more than one normally compared to the wired or infrastructure-based wireless network. There is a need for the routing protocol deployment which detects the failures as early as possible and efficient enough to handle a greater number of faults meanwhile managing all the network functionalities. So, the routing protocol should automatically select the alternate paths if there is a node or link failure in one path.

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