摘要
Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper, we propose a new geographic routing protocol, SBFR (Scoped Bellman-Ford Routing), for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed Bellman- Ford method, and maintains a cost for routing to the sink. When forwarding a packet, a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good sealability, it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.
Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper, we propose a new geographic routing protocol, SBFR (Scoped Bellman-Ford Routing), for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed Bellman- Ford method, and maintains a cost for routing to the sink. When forwarding a packet, a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good sealability, it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.
基金
partially supported by the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z199
the National Natural Science Foundation of China under Grant Nos. 90718031 and 60721002
the National Basic Research 973 Program of China under Grant No. 2006CB303000.