Energy-Aware routing in MANET: Hybrid Genetic and Group Search Algorithm

Abstract

MANET is the infrastructure-less, self-organized wireless network. Here, the mobile nodes can join the group or leave from the network group dynamically. As the mobile ad hoc network (MANET) is established with the battery power nodes, reducing the power consumption of mobile node poses a major complex in the network system. Efficient and robust secure routing protocols are required in MANET due to the quickly changing network topology such that the overhead incurred in the track is excessive. To achieve the secure routing path mechanism with less delay and minimum energy consumption of the nodes, a multi-objective based optimization algorithm is introduced in this research work. Here, the best optimal route is chosen for routing the data packets from the source to the destination on the basis of defined multiobjectives like: energy, delay, distance and link state stability. The secure path energy efficient path is identified by the Crossover of GA with GSO Algorithm (CGA-GSO). This is the hybridized form of standard Genetic Algorithm (GA) and the Group search Optimization (GSO) algorithm. The performance of the proposed model will be analyzed over the traditional approaches concerning Energy and Delay as well.

Very Large-Scale Integration Floor Planning on FIR and Lattice Filters Design With Multi-Objective Hybrid Optimization

“…for successful floor planning with minimized cost. In literature (Beno et al 2014) [31] (Malik 2020), it has been suggested that the hybrid optimization models are good in enhancing the convergence of the solutions and thereby they aid in achieving the defined objective function. However, it's crucial to verify the predicted model's effectiveness in attaining the optimal solution specified in Eq (2).…”