An optimal resource control scheme under fidelity and energy constraints in sensor networks
To control congestion, either the traffic from sources should be "reduced" (traffic controlling) or the available resources should be "increased" (resource controlling). Compared to the wired and other wireless counterparts, wireless sensor networks usually have elastic resource availability, and the applications require a certain level of throughput called fidelity. As a result, resource control strategies cannot only alleviate congestion but also ensure the required fidelity level during congestion by accommodating higher incoming traffic. In this paper, we first attempt to formally define the resource control framework that adjusts the resource provisioning at the hotspot nodes during congestion. In an effort to find the optimal resource control under the fidelity and energy constraints, we present a resource increase and decrease algorithm called Early Increase/Early Decrease (EIED) that tries to adjust the effective channel capacity quickly to suit the incoming traffic volume in an energy-efficient manner, thereby increasing the fidelity level observed by the application. Under the energy-constrained optimization, we prove this algorithm incurs the lowest overhead of energy consumption for the given fidelity level that is required by the application. We also prove that the EIED algorithm performed in a distributed manner also lowers the energy consumption per packet at an end-to-end level. The effectiveness of the EIED algorithm is verified by simulations based on realistic sensor network configurations.
resource control fidelity sensor networks congestion control energy efficiency