A virtual infrastructure for large-scale wireless sensor networks

The primary goal of a wireless sensor network is to collect useful information from the network. Most wireless sensor networks are assumed that the number of nodes are very large and they should operate with confined resources. Consequently it is important to take a scalable and energy-efficient architecture. In this paper, we present Railroad, a data collection and topology management architecture for large-scale wireless sensor networks. It proactively exploits a virtual infrastructure called Rail, which acts as a rendezvous area of the event data and queries. By using Rail, Railroad achieves scalability and energy efficiency under dynamic conditions with multiple mobile observers and targets. We evaluate the communication cost and the hot area message complexity of Railroad and compare them with previous approaches. We evaluate communication cost of Railroad by both an analytic model and simulations.