Computational intelligence paradigms for automata based secured energy efficient routing in wireless sensor network - A technical survey

Wireless Sensor Network (WSN) has been deployed in several areas of interest for controlling the region, automation of mundane tasks due to features such as smart sensor nodes, low cost, and small-scale factors. Earlier, the sensory units were costly and deficient in the computational and communicational capabilities which were overcome by sensing, processing, storing, and forwarding the data powered by a battery. There predominates diverse applications which affects the low-cost solutions of WSNs in numerous specialties such as observing patients in health care, target exposure, and tracking purposes, examining the atmosphere and climate, home applications, contributing protection for vehicular networks Owing to the diversity of the applications of Wireless Sensor Network, it needs to impose varying design, implementation, and performance requirements on the Wireless Sensor Network to have deep knowledge about the characteristics of WSNs. The pervasiveness of designing and optimizing WSN appeared to be a surplus to several application fields which influenced countless researchers to pay attention to several issues such as routing, mobility of nodes, coverage, and security. In recent years, designing of WSN becomes the leading domain for many researchers. A WSN is bounded with a collection of devices that are associated in the network to communicate the information collected from the field through the wireless links that have been established in the network. The data thus collected is transmitted through multiple nodes and also, the data is communicated to other networks through the gateway. During the design and deployment of WSNs, more attention is required at various levels like routing, coverage, and security. A complete system could be designed so that it could resolve the problems such as energy exhaustion, network lifetime, throughput, end-to-end time, routing, and intrusion detection could also monitor and keep control of the network environment. Therefore, this proposed technical research survey work has been carried out by devising an automaton system that can learn, monitor and control the dynamic behaviour of the network environment as well as can obtain an optimal route using Computational Intelligence Techniques. Besides, it detects the malicious activities that occur in the network using Hybrid Intrusion Detection System (IDS) model to enhance the throughput, lifetime of the network, utilization of the energy, end-to-end delay, accuracy, detection rate, computational time and recall rate.