Avoiding energy-compromised hotspots in resource-limited wireless networks

International audienceThe vast literature on the wireless sensor research community contains many valuable proposals for managing energy consumption, the most important factor that determines sensors lifetime. Interesting researches have been facing this requirement by focusing on the extension of the entire network lifetime: either by switching between node states (active, sleep), or by using energy efficient routing. We argue that a better extension of the network lifetime can be obtained if an efficient combination of management mechanisms can be performed at the energy of each single sensor and at the load distribution over the network. Considering these two accuracy levels ({\it i.e.}, node and network), this paper presents a new approach that uses cost functions to choose energy efficient routes. In particular, by making different energy considerations at a node level, our approach distributes routing load, avoiding thus, energy-compromised hotspots that may cause network disconnections. The proposed cost functions have completely decentralized and adaptive behavior and take into consideration: the end-to-end energy consumption, the remaining energy of nodes, and the number of transmissions a node can make before its energy depletion. Our simulation results show that, though slightly increasing path lengths from sensor to sink nodes, the proposed scheme (1) improves significantly the network lifetime for different neighborhood densities degrees, while (2) preserves network connectivity for a longer period of time