Gossip-based scalable directed diffusion for wireless sensor networks

Abstract

Directed diffusion (DD) is a promising data-centric routing scheme for wireless sensor networks (WSNs). But the heavy flooding overhead involved in interest propagation causes scalability issues when DD is applied in large scale, interactive and dynamically changing sensor networks. To solve this problem, we propose a scalable version of DD called gossip-based scalable directed diffusion (GSDD) in this paper. GSDD uses the same routing framework as DD but integrates gossiping in interest propagation and employs dynamic regional gossiping in path exploration phase to reduce the flooding overhead. Our analysis and simulation results demonstrate that GSDD is able to reduce the data delivery cost of DD by up to 25%; thus, significantly reduce energy consumption and prolong the lifetime of sensor nodes. Therefore, GSDD overcomes the scalability problem of DD and is suitable for large-scale WSNs. © 2011 John Wiley & Sons, Ltd. We propose a scalable version of directed diffusion called gossip-based scalable directed diffusion (GSDD) in this paper. GSDD integrates gossiping in interest propagation and employs dynamic regional gossiping in path exploration phase of the directed diffusion protocol to reduce the flooding overhead. Therefore GSDD overcomes the scalability problem of directed diffusion and is suitable for large scale wireless sensor networks. © 2011 John Wiley & Sons, Ltd.