Secure Coronas Based Zone Clustering and Routing Model for Distributed Wireless Sensor Networks

Distributed Wireless Sensor Networks (DWSNs) comprised of set of sensor nodes that are geographically distributed in harsh environments. However, a centralized WSN does not consider the network scalability and also leads to high energy consumption. Due to these open issues, distributed computing approach is considered since it resolves scalability issue and several paths are established for data transmission. To achieve higher energy efficiency, scalability and security, in this paper we propose a distributed protocol called Secure Coronas-Based Zone Clustering and Routing (SC-ZCR). The proposed SC-ZCR aim at addressing the number of issues in DWSN and it support for long-term deployment. In SC-ZCR, we will pursue several processes including Zone Clustering, Energy Efficient Routing and Data Encryption and Security Verification. Zone clustering is carried out using Adaptive Neuro-Fuzzy System, where we consider four parameters: node angle, distance between sensor node to the sink node, node residual energy and belief value. Belief value of each sensor node is computed using Principal Component Analysis. Then energy efficient routing is established by Q-Hop Routing Protocol, which finds optimum and shortest path using Whale Optimization Algorithm. For data packets encryption, RC6 is used and then security level of data packets are verified using potential weight factor δ, which is computed using key size KK, block size BB, and number of rounds RR. Experiments conducted using NS3.26 simulator and the simulation result show that the proposed SC-ZCR outperforms in terms of Coverage Ratio, Residual Energy, Network Lifetime, Delay, Packet Drop Rate, and Security Strength