Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7755

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Publisher: search.filters.publisher.Oxford University Press

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  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Extended Void Merging Tree Algorithm for Self-Similar Models
    (Oxford University Press, 2014) Russell, Esra
    In hierarchical evolution, voids exhibit two different behaviours related with their surroundings and environments, they can merge or collapse. These two different types of void processes can be described by the two-barrier excursion set formalism based on Brownian random walks. In this study, the analytical approximate description of the growing void merging algorithm is extended by taking into account the contributions of voids that are embedded into overdense region(s) which are destined to vanish due to gravitational collapse. Following this, to construct a realistic void merging model that consists of both collapse and merging processes, the twobarrier excursion set formalism of the void population is used. Assuming spherical voids in the Einstein-de Sitter Universe, the void merging algorithm which allows us to consider the two main processes of void hierarchy in one formalism is constructed. In addition to this, the merger rates, void survival probabilities, void size distributions in terms of the collapse barrier and finally, the void merging tree algorithm in the self-similar models are defined and derived.
  • Article
    Citation - WoS: 13
    Citation - Scopus: 18
    Graph Matching-Based Distributed Clustering and Backbone Formation Algorithms for Sensor Networks
    (Oxford University Press, 2010) Dağdeviren, Orhan; Erciyeş, Kayhan
    Clustering is a widely used technique to manage the essential operations such as routing and data aggregation in wireless sensor networks (WSNs). We propose two new graph-theoretic distributed clustering algorithms for WSNs that use a weighted matching method for selecting strong links. To the best of our knowledge, our algorithms are the first attempts that use graph matching for clustering. The first algorithm is divided into rounds; extended weighted matching operation is executed by nodes in each round; thus the clusters are constructed synchronously. The second algorithm is the enhanced version of the first algorithm, which provides not only clustering but also backbone formation in an energy-efficient and asynchronous manner. We show the operation of the algorithms, analyze them, provide the simulation results in an ns2 environment. We compare our proposed algorithms with the other graph-theoretic clustering algorithms and show that our algorithms select strong communication links and create a controllable number of balanced clusters while providing low-energy consumptions. We also discuss possible applications that may use the structure provided by these algorithms and the extensions to the algorithms. © The Author 2009. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.