{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Distributed Algorithms for Online Coordination in Wireless Sensor Networks","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/71048"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"With the rapid development of large-scale wireless sensor networks in the past few years, we expect the embedded sensors to be integrated smoothly with other mobile embedded devices. In this dissertation, we consider the following model of a hybrid network with both static and mobile nodes. There are pervasive static sensor nodes embedded in the environment to gather real-time data. The mobile nodes can be either robots with controlled mobility to aid the network operation and repair dysfunctional network components, or users of the sensor network that demand real-time knowledge gathered by the sensor nodes, or robots/users that use the sensor network as a communication infrastructure, or a mixture of the above. The specific scenarios include, but are not limited to, online resource management and allocation, maintaining group communication and coordination of mobile agents, and efficient and resilient routing schemes. To solve these problems, we introduce a framework to manage the efficient and highly selective information flow between the sensor nodes and the mobile nodes. This framework involves the following components: ?? We extract a hierarchical well separated tree (HST) to approximate the shortest path metric of the static sensor network. ?? With the HST, we allow spontaneous, distributed matching between users that may emerge anywhere and the resources available in the network. ?? We also show that in the same framework, we can coordinate mobile users by maintaining an approximate minimum Steiner tree with modest communication cost. ?? By using two or multiple HSTs, we also show how to support low-stretch routing that is also resilient to in-transit link failures. In addition to the above HST framework, we develop the compact conformal map for greedy routing in wireless mobile sensor networks. The map is only dependent on the network domain and is independent of the network connectivity. This is the first practical solution for using virtual coordinates for greedy routing in a sensor network and could be easily extended to the case of a mobile network."},{"label":"dcterms.available","value":"2015-04-24T14:45:43Z"},{"label":"dcterms.contributor","value":"Gao, Jie , Das, Samir"},{"label":"dcterms.creator","value":"Zhou, Dengpan"},{"label":"dcterms.dateAccepted","value":"2015-04-24T14:45:43Z"},{"label":"dcterms.dateSubmitted","value":"2015-04-24T14:45:43Z"},{"label":"dcterms.description","value":"Department of Computer Science"},{"label":"dcterms.extent","value":"198 pg."},{"label":"dcterms.format","value":"Monograph"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/71048"},{"label":"dcterms.issued","value":"2012-05-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2013-05-22T17:35:55Z (GMT). No. of bitstreams: 1\nZhou_grad.sunysb_0771E_10928.pdf: 6315654 bytes, checksum: 7664e9be83ad2574c9a631d3338d8b48 (MD5)\n Previous issue date: 1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"Approximate Algorithm, Computational Geometry, Distributed Algorithm, Routing, Spanner, Wireless Sensor Networks"},{"label":"dcterms.title","value":"Distributed Algorithms for Online Coordination in Wireless Sensor Networks"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/15%2F53%2F11%2F155311669365043781821142604826718094235/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/15%2F53%2F11%2F155311669365043781821142604826718094235","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}