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Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness

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dc.contributor.authorDhanapala, Dulanjalie C., author
dc.contributor.authorJayasumana, Anura P., advisor
dc.contributor.authorKirby, Michael, committee member
dc.contributor.authorPezeshki, Ali, committee member
dc.contributor.authorRay, Indrakshi, committee member
dc.date.accessioned2007-01-03T08:26:20Z
dc.date.available2007-01-03T08:26:20Z
dc.date.issued2012
dc.description.abstractFuture Wireless Sensor Networks (WSNs) will be collections of thousands to millions of sensor nodes, automated to self-organize, adapt, and collaborate to facilitate distributed monitoring and actuation. They may even be deployed over harsh geographical terrains and 3D structures. Low-cost sensor nodes that facilitate such massive scale networks have stringent resource constraints (e.g., in memory and energy) and limited capabilities (e.g., in communication range and computational power). Economic constraints exclude the use of expensive hardware such as Global Positioning Systems (GPSs) for network organization and structuring in many WSN applications. Alternatives that depend on signal strength measurements are highly sensitive to noise and fading, and thus often are not pragmatic for network organization. Robust, scalable, and efficient algorithms for network organization and reliable information exchange that overcome the above limitations without degrading the network's lifespan are vital for facilitating future large-scale WSN networks. This research develops fundamental algorithms and techniques targeting self-organization, data dissemination, and discovery of physical properties such as boundaries of large-scale WSNs without the need for costly physical position information. Our approach is based on Anchor Centric Virtual Coordinate Systems, commonly called Virtual Coordinate Systems (VCSs), in which each node is characterized by a coordinate vector of shortest path hop distances to a set of anchor nodes. We develop and evaluate algorithms and techniques for the following tasks associated with use of VCSs in WSNs: (a) novelty analysis of each anchor coordinate and compressed representation of VCSs; (b) regaining lost directionality and identifying a 'good' set of anchors; (c) generating topology preserving maps (TPMs); (d) efficient and reliable data dissemination, and boundary identification without physical information; and (f) achieving network awareness at individual nodes. After investigating properties and issues related to VCS, a Directional VCS (DVCS) is proposed based on a novel transformation that restores the lost directionality information in VCS. Extreme Node Search (ENS), a novel and efficient anchor placement scheme, starts with two randomly placed anchors and then uses this directional transformation to identify the number and placement of anchors in a completely distributed manner. Furthermore, a novelty-filtering-based approach for identifying a set of 'good' anchors that reduces the overhead and power consumption in routing is discussed. Physical layout information such as physical voids and even relative physical positions of sensor nodes with respect to X-Y directions are absent in a VCS description. Obtaining such information independent of physical information or signal strength measurements has not been possible until now. Two novel techniques to extract Topology Preserving Maps (TPMs) from VCS, based on Singular Value Decomposition (SVD) and DVCS are presented. A TPM is a distorted version of the layout of the network, but one that preserves the neighborhood information of the network. The generalized SVD-based TPM scheme for 3D networks provides TPMs even in situations where obtaining accurate physical information is not possible. The ability to restore directionality and topology-based Cartesian coordinates makes VCS competitive and, in many cases, a better alternative to geographic coordinates. This is demonstrated using two novel routing schemes in VC domain that outperform the well-known physical information-based routing schemes. The first scheme, DVC Routing (DVCR) uses the directionality recovered by DVCS. Geo-Logical Routing (GLR) is a technique that combines the advantages of geographic and logical routing to achieve higher routability at a lower cost by alternating between topology and virtual coordinate spaces to overcome local minima in the two domains. GLR uses topology domain coordinates derived solely from VCS as a better alternative for physical location information. A boundary detection scheme that is capable of identifying physical boundaries even for 3D surfaces is also proposed. "Network awareness" is a node's cognition of its neighborhood, its position in the network, and the network-wide status of the sensed phenomena. A novel technique is presented whereby a node achieves network awareness by passive listening to routine messages associated with applications in large-scale WSNs. With the knowledge of the network topology and phenomena distribution, every node is capable of making solo decisions that are more sensible and intelligent, thereby improving overall network performance, efficiency, and lifespan. In essence, this research has laid a firm foundation for use of Anchor Centric Virtual Coordinate Systems in WSN applications, without the need for physical coordinates. Topology coordinates, derived from virtual coordinates, provide a novel, economical, and in many cases, a better alternative to physical coordinates. A novel concept of network awareness at nodes is demonstrated.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierDhanapala_colostate_0053A_11371.pdf
dc.identifierETDF2012500295ECEN
dc.identifier.urihttp://hdl.handle.net/10217/71554
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectnetwork awareness
dc.subjectphenomena discovery
dc.subjectrouting
dc.subjectsensor networks
dc.subjecttopology preserving maps
dc.subjectvirtual coordinate systems
dc.titleAnchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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