An Efficient Smart Weighted and Neighborhood-enabled Load Balancing Scheme for Constraint Oriented Networks

In wireless sensor networks (WNSs), uniform load or traffic distribution strategy is one of the main challenging issues, which is tightly coupled with the resource-limited networks. To address this problem, various mechanisms have been developed and presented in the literature. However, these approaches were either application specific that is designed for a specific application area such as smart building or overlay complex. Therefore, a simplified and energy efficient load-balancing scheme is always needed for the resource-limited networks. In this paper, an efficient and neighborhood-enabled load-balancing scheme is presented to resolve the aforementioned issues specifically with available resources. For this purpose, the proposed scheme bounds every member node to collect various information about neighboring nodes i.e., those nodes resides in its communication range. Moreover, if residual energy Er of sensor node is less than the defined threshold value then it shares this information with neighboring nodes. In the proposed neighborhood-enabled load balancing scheme, every sensor node Ci prefers to route packets through the optimal paths particularly those paths where probability of critical nodes is negligible i.e., path where critical node(s) are not deployed. Simulation results showed that the proposed neighborhood-enabled load-balancing scheme is better than existing approaches in terms of network lifetime (both individual node and whole WSNs), throughput, and average packet delivery ratio and end-to-end delay performance metrics.

@article{Almaiah2020,
  title     = {An Efficient Smart Weighted and Neighborhood-enabled Load Balancing Scheme for Constraint Oriented Networks},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {12},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Mohammed Amin Almaiah},
  doi       = {10.14569/IJACSA.2020.0111269},
  url       = {https://doi.org/10.14569/IJACSA.2020.0111269}
}