SALAM: A SCALABLE ANCHOR-FREE LOCALIZATION ALGORITHM FOR WIRELESS SENSOR NETWORKS

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dc.contributor.advisorAgrawala, Ashok Ken_US
dc.contributor.authorYoussef, Adel Amin Abdel Azimen_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2006-06-14T05:52:37Z
dc.date.available2006-06-14T05:52:37Z
dc.date.issued2006-04-26en_US
dc.description.abstractIn this dissertation, we present SALAM, a scalable anchor-free protocol for localization in wireless sensor networks. SALAM can determine the positions of sensor nodes without any infrastructure support. We assume that each node has the capability to estimate distances to its corresponding neighbors, that are within its transmission range. SALAM allows to trade the accuracy of the estimated position against node transmission range and/or computational power. The application layer can choose from a whole range of different options, to estimate the sensor node's positions with different accuracy while conserving battery power. Scalability is achieved by dividing the network into overlapping multi-hop clusters each with its own cluster head node. Each cluster head is responsible for building a local relative map corresponding to its cluster using intra-cluster node's range measurements. To obtain the global relative topology of the network, the cluster head nodes collaboratively combine their local maps using simple matrix transformations. In order for two cluster heads to perform a matrix transformation, there must be at least three boundary nodes that belongs to both clusters (i.e. the two clusters are overlapping with degree 3). We formulate the overlapping multi-hop clustering problem and present a randomized distributed heuristic algorithm for solving the problem. We evaluate the performance of the proposed algorithm through analytical analysis and simulation. A major problem with multi-hop relative location estimation is the error accumulated in the node position as it becomes multi-hop away from the cluster head node. We analyze different sources of error and develop techniques to avoid these errors. We also show how the local coordinate system (LCS) affects the accuracy and propose different heuristics to select the LCS. Simulation results show that SALAM achieves precise localization of sensors. We show that our approach is scalable in terms of communication overhead regardless of the network size. In addition, we capture the impact of different parameters on the accuracy of the estimated node's positions. The results also show that SALAM is able to achieve accuracy better than the current ad-hoc localization algorithms.en_US
dc.format.extent1457769 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/3496
dc.language.isoen_US
dc.subject.pqcontrolledComputer Scienceen_US
dc.subject.pqcontrolledComputer Scienceen_US
dc.subject.pquncontrolledsensor networksen_US
dc.subject.pquncontrolledlocalizationen_US
dc.subject.pquncontrolledclusteringen_US
dc.subject.pquncontrolledspanning treeen_US
dc.titleSALAM: A SCALABLE ANCHOR-FREE LOCALIZATION ALGORITHM FOR WIRELESS SENSOR NETWORKSen_US
dc.typeDissertationen_US

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