Adaptive energy-aware routing framework in transmission cost constrained wireless sensor networks

Existing routing protocols in wireless sensor networks (WSN) utilize either the shortest path routing reducing (or minimizing) the transmission costs for real-time, inelastic traffic, or the load balancing routing (e.g. potential based routing) prolonging (or maximizing) the networks life time. However, how to efficiently deal with the trade-off between network life time and the least delay requirements is still an open problem. In this paper, by formulating the shortest path routing and the least energy cost routing in wireless sensor networks as L₁-norm and L₂-norm optimization problems, we propose an adaptive energy aware routing framework, namely, a convexly combined L₁- and L₂-norm optimization, that subsume the shortest path and the potential based routing strategies as two extreme cases. The proposed routing framework can adaptively select optimal (sparse) routes for source destination pairs, that satisfy a certain (elastic) transmission cost requirement, as well as maintaining the maximum network life time. The extensive simulation results demonstrate the efficiency of our routing framework.