Predictive Data Delivery to Mobile Users through Mobility Learning in Wireless Sensor Networks
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Description
Mobile wireless sensor networks (MWSNs) can simply be defined as a wireless sensor network (WSN) in which the sensor nodes are mobile. MWSNs are a smaller, emerging field of research in contrast to their well-established predecessor. These are much more versatile than static sensor networks as they can be deployed in any scenario and cope with rapid topology changes. Classic multi-hop wireless routing protocols compute the shortest path between sources and destinations in a network. Since the shortest path minimizes the number of necessary transmissions, this strategy minimizes not only delay but also energy use. In the presence of mobility, however, the shortest path computed at one point in time is not necessarily the shortest possible path connecting the source and the sink. A shorter path might be available, if the nodes move closer to each other in the future. An optimal routing strategy can be devised if the trajectory of the mobile nodes is known. In this project, the system proposes data stashing that is a network optimization process. It uses the predictions to minimize network and energy overheads of packet transmissions.
Tags: 2015, Domain > Network Projects