Spatial energy balancing through proactive multipath routing in wireless multihop networks
In this paper, we investigate the use of proactive multipath routing to achieve energy-efficient operation of ad hoe wireless networks. The focus is on optimizing tradeoffs; between the energy cost of spreading traffic and the improved spatial balance of energy burdens. We propose a simple scheme for multipath routing based on spatial relationships among nodes. Then, combining stochastic geometric and queueing models, we develop a continuum model for such networks, permitting an evaluation of different types of scenarios, i.e., with and without energy replenishing and storage capabilities. We propose a parameterized family of energy balancing strategies and study the spatial distributions of energy burdens based on their associated second-order statistics. Our analysis and simulations show the fundamental importance of the tradeoff explored in this paper, and how its optimization depends on the relative values of the energy reserves/storage, replenishing rates, and network load characteristics. For example, one of our results shows that the degree of spreading should roughly scale as the square root of the bits (.) meters load offered by a session. Simulation results confirm that proactive multipath routing decreases the probability of energy depletion by orders of magnitude versus that of a shortest path routing scheme when the initial energy reserve is high.
gaussian random field m/gi/i queue sensor networks shot-noise process stochastic geometry