Minimizing Energy Consumption with Probabilistic Distance Models in Wireless Sensor Networks

Minimizing energy consumption in wireless sensor networks has been a challenging issue, and grid-based clustering and routing schemes have attracted a lot of attention due to their simplicity and feasibility. Thus how to determine the optimal grid size in order to minimize energy consumption and prolong network lifetime becomes an important problem during the network planning and dimensioning phase. So far most existing work uses the average distances within a grid and between neighbor grids to calculate the average energy consumption, which we found largely underestimates the real value. In this paper, we propose, analyze and evaluate the energy consumption models in wireless sensor networks with probabilistic distance distributions. These models have been validated by numerical and simulation results, which shows that they can be used to optimize grid size and minimize energy consumption accurately. We also use these models to study variable-size grids, which can further improve the energy efficiency by balancing the relayed traffic in wireless sensor networks.