Energy Balanced Model for Lifetime Maximization in Randomly Distributed Wireless Sensor Networks

In this paper, an energy balanced model (EBM) for lifetime maximization for a randomly distributed sensor network is proposed. The lifetime of a sensor network depends on the rate of energy depletion caused by multiple factors, such as load imbalance, sensor deployment distribution, scheduling, transmission power control, and routing. Therefore, in this work, we have developed a mathematical model for analysis of load imbalance under uniform and accumulated data flow. Based on this analysis, we developed a model to rationalize energy distribution among the sensors for enhancing the lifetime of the network. To realize the proposed EBM, three algorithms—annulus formation, connectivity ensured routing and coverage preserved scheduling have been proposed. The proposed model has been simulated in ns-2 and results are compared with Energy-Balanced Transmission Policy and Energy Balancing and unequal Clustering Algorithm. Lifetime has been measured in terms of the time duration for which the network provides satisfactory level of coverage and data delivery ratio. EBM outperform both the existing models. In our model the variance of residual energy distribution among the sensors is lower than other two models. This validated the essence of energy rationalization hypothesized by our model.