EEMR-PSO-CUCKOO: Energy Efficient MANET Routing Using Hybrid PSO and CUCKOO Search

Mobility creates instability of mobile Ad Hoc networks (MANET) and uncertainty for competent routing in an unpredictable, infrastructure-less topology. Energy is one of the constraints in the MANET due to mobility and generates irregular bandwidth utilization of the networking real-time environment for changeable distance among the mobile nodes. Many researchers have proposed using PSO or hybrid PSO-ACO approaches to find an energy-efficient, stable routing path considering mobility, energy consumption, bandwidth utilization, and distance. This paper designs an energy-efficient MANET routing EEMR-PSO-CUCKOO (Energy Efficient MANET Routing Using Hybrid PSO and CUCKOO Search) algorithm. The performance analysis shows that the proposed routing protocol is more efficient and establishes a new direction than the existing one concerning network lifetime, bandwidth utilization for data transmission, and End-to-End delay. The mobility and energy environment for the PSO algorithm is applied here to create energy-efficient cluster heads by considering the additive weight-based fitness value of the individual nodes. Finally, meta-heuristic CUCKOO’s Levy flight optimization technique finds the optimized path among the cluster heads to transmit the data to the node via cluster heads. CUCKOO’s Levy fly optimization technique considers the remaining bandwidth and distance among the cluster head. Hybrid PSO and Cuckoo Search-based optimized EEMR-PSO-CUCKOO algorithm works over various MANET conditions with varying mobile nodes and CHs scenarios. Extensive simulation results show that our proposed hybrid technique improves the End-to-End delay and packet delivery ratio (PDR) in the performance of the given solution by comparing with the existing protocol ACO, PSO, Hybrid-ACO-PSO, and CSO-AODV. Further, the performance of the given key improved compared with the current protocol in terms of energy consumption or throughput and network lifetime with existing AODV, AOMDV, PSO-AOMDV, and CSO-AODV, demonstrating the dominance of the proposed algorithm.