Social Group Optimization-based New Routing Approach for WMN’s

Wireless Mesh Networks (WMNs) are hop-to-hop communication networks that are quickly deployable, dynamically self-organizing, self-configuring, self-healing, self-balancing, and self-aware. In WMNs, a node can leave or join the network at any time. Due to the mobile nature of nodes, the routes between source and destination can change frequently. Computing the shortest path under dynamic conditions for a given time constraint imposed due to node mobility can also be placed in the class of highly complex problems. However, as the network size grows, the performance of the nodes decreases. As a result, we require Soft Computing approaches to handle this problem. This article proposes a Social Group Optimization (SGO) based routing approach to wireless mesh networks. The proposed approach was implemented in MATLAB and tested on different dynamic nodes network scenarios. We compare the performance of the proposed approach with Ant Colony Optimization (ACO), Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR), BAT, Biogeography-based optimization (BBO), and Firefly Algorithm based routing approaches. We observe that the proposed approach outperformed all other approaches on the more than 1000 node network scenarios.

@article{Sharma2022,
  title     = {Social Group Optimization-based New Routing Approach for WMN’s},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {4},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Bhanu Sharma and Amar Singh},
  doi       = {10.14569/IJACSA.2022.0130462},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130462}
}