Implementation of Energy-Aware Optimal Routing for Improving Traffic Capacity in Ad Hoc Wireless Network Using Hybrid Heuristic Algorithm

Ad hoc wireless network has been one of the significant research topics, as its uses are spread over various applications. The energy-aware routing (EAR) protocols must create a routing environment with both the security and energy factors, such that the ad hoc network can be sustained for a longer period. Thus, this work proposes an EAR model by considering various factors of the ad hoc network and thus aims to improve the overall network lifetime. At first, the necessary attributes for this process are gathered from standard data sources. After that, an energy-efficient optimal routing process is performed with the support of the proposed Hybrid Dark Forest-based Gazelle Optimization Algorithm (HDFGOA) for minimizing energy consumption and maximizing the network lifespan. In this process, the multiobjective functions such as residual energy, route energy, route quality, congestion, and signal interference noise ratio (SINR) are derived by the same HDFGOA. This supports to performance of the energy-efficient optimal routing process without any interference. Moreover, this process improves the traffic capacity of the ad hoc wireless networks. Finally, thorough experiments are performed for the developed energy-efficient optimal routing process with conventional algorithms to ensure the suggested process's effectiveness.