L. Doherty, "Algorithms for Position and Data Recovery in Wireless Sensor Networks," Master's Report, University of California, Berkeley, June, 2000.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....with its neighbors) for localization are therefore preferable to centralized ones. The reader can consult [GBEE02, BEGH01, NN01, PCB00, ASSC02] for more practical aspects of current localization techniques. We are particularly interested in localization using radio signals which is discussed in [Doh00, DPG01]. Namely, if S is a node whose position p is unknown and Date: November 18, 2002. Partially supported by the NSF grant ITR SI: Societal Scale Information Systems: Technologies, Design and Applications, number EIA 0122599. S k1 , S km are its neighbors whose positions p k1 , p km ....

L. Doherty. Algorithms for position and data recovery in wireless sensor networks. Master's thesis, UC Berkeley, 2000.

....then take further action. This work is mainly motivated by the Sensorwebs and Smart Dust [KKP] projects at UC Berkeley, whose aim is to develop a unified framework for distributed sensor networks. Some previous theoretical work on environmental monitoring using random sensor networks was done in [Doh00] For a study of wireless sensor networks in real world habitat monitoring, see [MPS 02] We also mention [MEM01] which deals with gradient estimation from scattered data in geology. Due to high long range communication costs, low battery power, and need for robustness to node failures, it ....

L. Doherty, Algorithms for position and data recovery in wireless sensor networks, Master's thesis, UC Berkeley, 2000.

....oceanography, building science, etc. Our work is mainly motivated by the Sensorwebs and Smart Dust [KKP] projects at UC Berkeley, whose aim is to develop a unified framework for distributed sensor networks. Some previous work on environmental monitoring using random sensor networks was done in [Doh00]. Due to high long range communication costs and low battery power, it is natural to seek decentralized, distributed algorithms for sensor networks. This means that instead of relaying data to a central location which does all the computing, the nodes process information in a collaborative, ....

L. Doherty, Algorithms for position and data recovery in wireless sensor networks, Master's thesis, UC Berkeley, 2000.

....III presents a short GPS review, as its principles are central to our approach. Section IV explains the APS approach, with the proposed propagation methods, section V presents simulation results and we conclude with some considerations about node mobility effects on APS. 2 Related Work Reference [3] is proposing a positioning scheme that works in a centralized manner by collecting the entire topology in a server and then solving a large system that will minimize positioning errors for each node. Reference [5] presents a relative positioning system, without the use of GPS, in which the origin ....

L. Doherty, "Algorithms for Position and Data Recovery in Wireless Sensor Networks," MasteFs Report, University of California, Berkeley, June, 2000.

....than some threshold, based, e.g. on signal strength) an angular sector (if a node is equipped, say, with laser transmitters and receivers that can scan through some angle) or an intersection of an annulus and an angular sector. For more information on these types of constraints, please see [Doh00]. We assume that a certain positive number K of nodes know their location in Q, i.e. they are able to compute their position relative to some fixed coordinate system in Q; in practice this can be achieved by equipping K motes with GPS or a priori (meaning before deploying the ad hoc network) ....

....Design a distributed algorithm for localization of nodes in N . Estimate the complexity and error of the above algorithm. Find an optimal number of known nodes depending on Q, N , and r, which minimizes the error of the algorithm. Centralized algorithms for localization were studied in [Doh00, DPG00]. The reason we are interested in a distributed rather than a centralized solution is that we envision a massively distributed network in which communication with a centralized computer is expensive both because the power supply of each node is very limited and long range multi hop data ....

L. Doherty. Algorithms for position and data recovery in wireless sensor networks. Master's thesis, UC Berkeley, 2000.

....for making geographic forwarding decisions. Although some sort of PEP may be neccessary for applications in mobile networks, and could be used by the geographic forwarding network when available, it is unneccessary the proxy technique is adequate for delivering packets. While creative approaches [6] may produce a PEP accurate to within one radio range, no known system is reliable enough to use by itself for geographic forwarding. A client using the location proxy system does not actually send every packet through its proxy, but towards the location aware node closest to the destination. ....

Lance Doherty. Algorithms for position and data recovery in wireless sensor networks. Master's thesis, University of California at Berkeley, May 2000.

....interrogator system, the particles would upload their sensor data. While no one sensor would definitively detect a passing vehicle, the aggregate of sensors and dust particles would provide enough spatial sensor information, that when processed, would produce a robust vehicle detection scheme [4]. 1.2 Smart Dust Capabilities For this research, I assumed Smart Dust would have specific capabilities. Namely, Smart Dust would have four basic components: 1) Power. In order to monitor an environment for any length of time, the dust particle must have enough energy to survive anywhere from a ....

Doherty, L. Algorithms for Position and Data Recovery in Wireless Sensor Networks. Master's Report, University of California, Berkeley, June, 2000.

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L. Doherty, "Algorithms for Position and Data Recovery in Wireless Sensor Networks," Master's Report, University of California, Berkeley, June, 2000.

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Lance Doherty, "Algorithms for position and data recovery in wireless sensor networks," M.S. thesis, University of California at Berkeley, 2000.

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Lance Doherty, "Algorithms for position and data recovery in wireless sensor networks," M.S. thesis, University of California at Berkeley, 2000.

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L. Doherty, "Algorithms for Position and Data Recovery in Wireless Sensor Networks," Master's Report, University of California, Berkeley, June, 2000.

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L. Doherty, "Algorithms for Position and Data Recovery in Wireless Sensor Networks," Master 's Report, University of California, Berkeley, June, 2000.

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