Density estimation in large-scale wireless sensor networks

Eroğlu, Alperen
Density estimation is a significant problem in large-scale wireless ad-hoc networks since the density drastically impacts the network performance. It is crucial to make the network adaptive in the run-time to the density changes that may not be predictable in advance. Local density estimators are required while taking run-time control decisions to improve the network performance. A wireless node may estimate the density locally by measuring the received signal strength (RSS) of packets sent by its neighbours. In this thesis, RSS-based individual and cooperative density estimators are validated by controlled field experiments conducted in the FIT IoT-LAB test-bed, in France. According to the experiments these methods cannot be used as accurate density estimators in practice. The success of the individual density is significantly affected by the position of the estimating node and the number of its neighbours. Also, the cooperative density estimator is affected negatively by correlated data. Hence, a new fusion approach is proposed as a new density estimator. New method is more accurate than the two other density estimators. However, it should be considered that the RSS is prone to large- and small-scale fading, and this phenomenon negatively affects the accuracy of density estimators.


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Eroğlu, Alperen; Onur, Ertan; Oğuztüzün, Mehmet Halit S. (2015-09-02)
Density of a wireless network drastically impacts its performance. Adapting the networking protocols at run-time to density changes, which may not be predictable in advance, may improve the network performance. Estimating the density of a wireless network is the challenge we address in this paper. A wireless node may locally estimate the network density by measuring the received signal strength (RSS) of packets sent by its neighbours. However, RSS is prone to large- and small-scale fading, and this phenomen...
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Density estimation is crucial for wireless ad hoc networks for adequate capacity planning. Protocols have to adapt their operation to the density since the throughput in an ad hoc network approaches asymptotically to zero as the density increases. A wireless node can estimate the global density by using local information such as the received power from neighbors. In this paper, we propose a cross layer protocol to compute the density estimate. The accuracy of the estimate can be enhanced and its variance ca...
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Uzun, Erkay; Yazıcı, Adnan; Department of Computer Engineering (2010)
Energy is a limited source in wireless sensor networks and in most applications, it is non-renewable; so designing energy-effcient communication patterns is very important. In this thesis, we define the static range assignment (SRA) problem for wireless sensor networks, which focuses on providing the required connectivity in the network with minimum energy consumption. We propose minimum spanning tree based (MST), pruned minimum spanning tree based (MSTP) and shortest path incremental (SPI) algorithms as eff...
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Wireless sensor networks are application-specific networks that necessitate the development of specific network and information processing architectures that can meet the requirements of the applications involved. The most important challenge related to wireless sensor networks is the limited energy and computational resources of the battery powered sensor nodes. Although the central processing of information produces the most accurate results, it is not an energy-efficient method because it requires a cont...
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Citation Formats
A. Eroğlu, “Density estimation in large-scale wireless sensor networks,” M.S. - Master of Science, Middle East Technical University, 2015.