(A) virtual infrastructure for large-scale wireless sensor networks

Abstract

Recent advances in microelectronics and communication systems are opening the era of wireless sensor networks composed of a large number of wireless sensor nodes. However, they should operate with confined resources including computation power, memory, and energy compared with traditional high-performance devices. Consequently, it is very important to take a scalable and energy-efficient algorithms and architectures. One of the primary goals of wireless sensor networks is to collect useful information from the network. When a user or an observer wants to gather information from the network, it is needed to use a structurally well-organized method to achieve the goal. I propose Railroad, a data dissemination/collection and topology management architecture for large-scale wireless sensor networks. It proactively exploits a virtual infrastructure called a Rail, which acts as a rendezvous area of the event data and queries. By using the Rail, Railroad achieves scalability and energy efficiency under dynamic conditions with multiple mobile observers and targets. There exist only one Rail in a network. It is formed by a decentralized process and every node has abstract information where the Rail is geographically located. At the moment when an event message is generated, a metadata for the event message is sent to the Rail to register a new event is originated. A query message is sent to the Rail when an observer wants to get information from the network. The query message circulate around the Rail and tries to search whether there are some metadata about newly registered event messages. I evaluate the communication cost and the hot area message complexity of Railroad and compare them with previous approaches. I evaluate communication cost of Railroad by both an analytic model and simulations.