History-Aware Adaptive Backoff for Neighbor Discovery in Wireless Networks

摘要

The ability of discovering neighboring nodes, namely neighbor discovery, is essential for the self-organization of wireless ad hoc networks. In this paper, we first propose a history-aware adaptive backoff algorithm for neighbor discovery using collision detection and feedback mechanisms. Given successful discovery feedbacks, undiscovered nodes can adjust their contention windows. With collision feedbacks and historical information, only transmission nodes enter the re-contention process, and decrease the size of their contention windows to accelerate the neighbor discovery process. Then, we give a theoretical analysis of our algorithm on discovery time and energy consumption, and derive the optimal size of contention windows. Finally, we validate our theoretical analysis by simulations, and show the performance improvement over existing algorithms.