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Since the development of Wireless Sensor Networks (WSNs), the limited battery of the sensor nodes has been an unavoidable concern. Hence, to keep the WSNs operational for a longer possible duration, the recharging of node's battery through harvesting the ambient energy from surroundings (for an example, solar energy) has been proposed. In this work, we focus not only on utilizing the energy harvesting (EH)-enabled sensor nodes for routing purposes but also introduce a novel hybrid optimization ROATSA that uses Remora Optimization Algorithm (ROA) and Tunicate Swarm Algorithm (TSA) for energy-efficient cluster-based routing. The proposed work is termed as ROA and TSA-based Energy-Efficient Cluster-based Routing for EH-enabled WSN (ROTEE). Hybrid ROATSA is chosen due to enhanced convergence and exploitation capabilities. To reduce the financial burden on the network, we use only four EH-enabled nodes and locate them at each periphery of the network, equidistant to each other and the other nodes are 3-level energy heterogeneous sensor nodes. The selection of cluster head (CH) is optimized through ROATSA by considering profile index of each node by evaluating them at energy, distance, load balancing, node density, the delay involved, and network's average energy. The proposed work ROTEE shows supreme performance against the recently proposed clustering techniques.

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a mobile ad hoc network (MANET) is a set of movable devices that is established without wired medium forming with various topologies. Mantes are not using infrastructure as wired network use and anytime, anywhere can be established. The direction-finding algorithms are classified into two parts in this paper (1). proactive DSDV (table driven) and (2). reactive DSR (On demand) algorithms. We simulate various MANET routing algorithms in network simulator NS-2 and compare the performance metrics for each Routing protocol like throughput, packet delivery ratio and average end to end delay by varying the number of nodes (Node 20 and Node 30 Group)with different pause time by using cbr source traffic and node movement model.Keywords-Mobile ad-hoc network, pause time, throughput, Ratio of packet delivery, average end to end delay, NS2.

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