An Auction Bidding Protocol for Distributed Bit Allocation in RSSI based Localization Networks
Several factors (e.g. target energy, sensor density) affect estimation error at a point of interest in sensor networks. One of these factors is the number of allocated bits to sensors that cover the point of interest when quantization is employed. In this paper, we investigate bit allocation in such networks such that estimation error requirements at multiple points of interest are satisfied as best as possible. To solve this nonlinear integer programming problem, we propose an iterative distributed auctionbidding protocol. Starting with some initial bit distribution, a network is divided into a a number of clusters each with its own auction. Each cluster head (CH) acts as an auctioneer and divides sensors into buyers or sellers of bits (i.e. commodity) With limited messaging, CHs redistribute bits among sensors, each bit at a time such that the difference between achieved and required estimation errors within each cluster is reduced in each round. We propose two bit pricing schemes used by sensors to decide on exchanging bits. Finally, simulation results show that our proposed 'distributed' protocol's error performance can be within 5% 10% of that of a 'centralized' genetic algorithm (GA) solution