A Price-Based Distributed Algorithm for Optimal Utility-Energy Trade-Off in Wireless Sensor Networks

Wireless sensor networks (WSNs) are energy- constrained in nature, in this paper, we formulate the problem of data transport in sensor networks as a network utility maximization (NUM) problem, but we argue that each source utility not only depends on its source rate, but also on the consumed energy, this leads to a coupled utility model, where the utilities are functions of source rates and consumed energy. Differentiating from the classical NUM framework which usually takes the consumed energy as constraints. Our utility model regards consumed energy as one of the components of measure of the utility values, which indicates the tradeoff of source rates and consumed energy, it is a more accurate utility model for abstracting the energy characteristics for data gathering and transmission in WSNs. Due to the coupled energy utility, our optimization problem is not separable. Despite the difficulty, we present a systematic approach to decouple our NUM problem with coupled utilities by introducing into the slack variables and using dual decomposition techniques, and obtain a distributed algorithm for solving this problem. The proposed algorithm can converge to the Pareto optimal tradeoff between rates and energy for all users.

I. Introduction

We consider a wireless sensor network of nodes distributed in a certain region, and assume that sensors are powered by small batteries that cannot be replaced. Under this energy constraint, sensor nodes can only transmit a finite number of bits in their lifetime. Consequently, reducing the energy consumption per bit for end-to-end transmissions is a key concern in WSNs.