HOCOR: Hybrid Optimization-Based Cooperative Opportunistic Routing for Underwater Wireless Sensor Networks.

The Internet of Things (IoT) enabled Underwater Wireless Sensor Networks (UWSNs) to emerge for applications like underwater imagining, underwater equipment monitoring, marine data collection, etc. These all applications relied on the routing method for data transmissions. However, a designing routing protocol for UWSNs using acoustic should address lower throughput, longer delay, high energy consumption, and collisions. We propose the novel Hybrid Optimization-based Cooperative Opportunistic Routing (HOCOR) for improving the performance of IoT-enabled UWSNs. As the Swarm Intelligence (SI) methods have already proven effective for routing and clustering problems of various wireless networks, we aim to design a hybrid SI technique using popular Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. In this hybrid SI technique, we exploit the benefits of both GA and PSO for optimal forwarding relay selection. In HOCOR, hybrid optimization aims at forming a reliable opportunistic data transmission route from any underwater sensor node to the surface sink. The hybrid optimization solves the problem of maximizing the Quality of Service (QoS) and network lifetime using the novel fitness function while evaluating each sensor node. The fitness function of the hybrid optimization algorithm computes the four parameters of each underwater sensor node such as underwater distance, node connectivity, packet transmission ability, and residual energy. We select these parameters to avoid packet collisions and void communications in UWSNs. Simulation results show that the HOCOR protocol outperforms the state-of-art methods in terms of the average throughput, Packet Delivery Ratio (PDR), average energy consumption, and average delay. [ABSTRACT FROM AUTHOR]