MARC 主機 00000nam  2200361   4500 
001    AAI3317283 
005    20081112170636.5 
008    081112s2007    ||||||||||||||||| ||eng d 
020    9780549667230 
035    (UMI)AAI3317283 
040    UMI|cUMI 
100 1  Akcan, Huseyin 
245 10 Data reduction and GPS-free node localization in wireless 
       sensor networks 
300    111 p 
500    Source: Dissertation Abstracts International, Volume: 69-
       06, Section: B, page:  
500    Adviser: Herve Bronnimann 
502    Thesis (Ph.D.)--Polytechnic University, 2007 
520    This thesis addresses the topics of data reduction via 
       sampling in both central database environments, and 
       wireless sensor networks, and GPS-free node localization 
       in wireless sensor networks. The first contribution of 
       this thesis is a deterministic sampling algorithm for 
       sampling count data, which is common in data mining 
       applications. We show that our algorithm creates more 
       accurate and higher quality samples compared to previous 
       work, and the samples it generates can be used as a 
       surrogate for the original high volume data 
520    Our second contribution is a deterministic weighted 
       sampling algorithm that can be used as a new data 
       aggregation method for wireless sensor network data. The 
       aggregation algorithm shares similar ideas with our 
       previous sampling algorithm. In order to adapt to the 
       sensor network environment, however, we designed our 
       algorithm to perform weighted sampling in a distributed 
       manner. The weighted sampling design allows the algorithm 
       to work with any arbitrary network topology, while the 
       distributed design divides the sampling work equally on 
       all the sensor nodes in the network and prevents any node 
       from being a bottleneck (both with regards to CPU 
       consumption, and communication). We show that our 
       aggregation algorithm generates samples of better quality 
       than previous algorithms, using far less energy 
520    Our last contribution is two GPS-free node localization 
       algorithms, termed GPS-free Directed Localization (GDL), 
       and GPS & Compass-free Directed Localization (GCDL). The 
       importance of localization is apparent in mobile wireless 
       sensor networks, where the neighborhood changes frequently
       and knowledge about the neighbor positions is essential 
       for performing additional tasks such as aggregation or 
       coherent movement. Our algorithms perform localization 
       without the need of Global Positioning System (GPS) or any
       other infrastructure (e.g., anchor points). These 
       algorithms work with only local knowledge without using 
       historical data, and exploit mobility to perform 
       localization. The memoryless aspect of our algorithms 
       avoids the accumulation error over time, which is 
       essential in mobility scenarios where coherent movement of
       a swarm of nodes is required. We show that our algorithms 
       do work even at high environmental noise levels, and keep 
       a nice semi-rigid network formation in mobility scenarios 
590    School code: 0179 
590    DDC 
650  4 Computer Science 
690    0984 
710 2  Polytechnic University.|bComputer and Information Sciences
773 0  |tDissertation Abstracts International|g69-06B 
856 40 |u