Browsing by Subject "Centralized algorithms"

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    Cooperative positioning in wireless networks
    (John Wiley & Sons, 2016) Gholami, M. R.; Keskin, M. F.; Gezici, Sinan; Jansson, M.; Webster, J. G.
    In this article, we study cooperative positioning in wireless networks in which target nodes at unknown locations locally collaborate with each other to find their locations. We review different models available for positioning and categorize the model‐based algorithms in two groups: centralized and distributed. We then investigate a lower bound on the variance of unbiased estimators, namely the Cramer–Rao lower bound, which is a common benchmark in the positioning literature. We finally discuss some open problems and research topics in the area of positioning that are worth exploring in future studies.
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    Coordinated movement of multiple mobile sinks in a wireless sensor network for improved lifetime
    (SpringerOpen, 2015) Koç, M.; Korpeoglu, I.
    Sink mobility is one of the most effective solutions for improving lifetime and has been widely investigated for the last decade. Algorithms for single-sink mobility are not directly applied to the multiple-sink case due to the latter’s specific challenges. Most of the approaches proposed in the literature use mathematical programming techniques to solve the multiple-sink mobility problem. However, doing so leads to higher complexities when traffic flow information for any possible sink-site combinations is included in the model. In this paper, we propose two algorithms that do not consider all possible sink-site combinations to determine migration points. We first present a centralized movement algorithm that uses an energy-cost matrix for a user-defined threshold number of combinations to coordinate multiple-sink movement. We also give a distributed algorithm that does not use any prior network information and has a low message exchange overhead. Our simulations show that the centralized algorithm gives better network lifetime performance compared to previously proposed MinDiff-RE, random movement, and static-sink algorithms. Our distributed algorithm has a lower network lifetime than centralized algorithms; sinks travel significantly less than in all the other schemes.