Cataloged from PDF version of article.Mobility prediction is one of the most essential issues that need to be explored for mobility management\ud in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell\ud movement of a mobile user in a Personal Communication Systems network. In the first phase of our threephase\ud algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second\ud phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are\ud accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation\ud as compared to two other prediction methods. The performance results obtained in terms of Precision\ud and Recall indicate that our method can make more accurate predictions than the other methods.\ud 2004 Elsevier B.V. All rights reserved

Wireless sensor networks have a broad range of applications in the category of environmental monitoring. In this thesis, we consider the problem of forest fire detection and monitoring as a possible application area of wireless sensor networks. Forest fires are one of the main causes of environmental degradation nowadays. The current surveillance systems for forest fires lack in supporting real-time monitoring of every point of the region at all time and early detection of the fire threats. Solutions using wireless sensor networks, on the other hand, can gather temperature and humidity values from all points of field continuously, day and night, and, provide fresh and accurate data to the fire fighter center quickly. However, sensor networks and nodes face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully.In our study, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, clustering and communication protocols, and environment/season-aware activity-rate selection schemes to detect the fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the physical conditions that may hinder the activity of the network. We also implemented a simulator to validate and evaluate our proposed framework, which is using an external fire simulator library. We did extensive simulation experiments and observed that our framework can provide fast reaction to forest fires while also consuming energy efficiently. Kablosuz duyarga agları kullanılarak dogal ortamların izlenmesiüzerine biŗ cok uygulama alanı geliştirilmiştir. Bu tezçalışmamızda, bizler de orman yangınlarının erken tespitinde ve yangının izlenmesi sürecinde kablosuz duyarga aglarını kullanarak bir sistem tasarladık. Orman yangınları dünyadaçevresel tahribata neden olan başlıca sebeplerden biridir. Şu anki yangın gözetleme ve takip sistemleri ormanları anlık olarak bütünüyle izleme ve olası bir yangın tehlikesiniönceden tespit etme konusunda başarısız olmaktadır.Öte yandan, kablosuz duyarga aglarını kullanarak geliştirilençözümler sıcaklık ve nem degerlerini, anlık olarak, sahanın farklı noktalarından, gece ve gündüz farketmeksizin sürekli olarak alabilmekte ve de merkezi birimlere taze ve güvenilir bilgi sunabilmektedir. Fakat, duyarga aglarında kullanılan duyarga dügümleri kısıtlı enerji kaynaklarına sahiptir ve zorlu dış koşullara karşı dayanıklı degillerdir. Geliştirilen uygulamalarda bu engellerin dikkatli birşekilde ele alınması gereklidir.Tezçalışmamızda kablosuz duyarga aglarını kullanarak orman yangınlarını erken tespit etmek ve izleyebilmek amacıyla geniş kapsamlı bir sistem geliştirdik. Sundugumuz sistem kablosuz duyarga aglarıyla ilgili bir ag altyapısı, dügümlerin ormana yerleştirilmesi ile ilgiliözel bir mekanizma ve dügümlerin küme içi ve kümeler arası iletişim protokollerini içermektedi...

Dynamic attributes are attributes that change continuously over time making it impractical to issue explicit updates for every change. In this paper, we adapt a variant of the quadtree structure to solve the problem of indexing dynamic attributes. The approach is based on the key idea of using a linear function of time for each dynamic attribute that allows us to predict its value in the future. We contribute an algorithm for regenerating the quadtree-based index periodically that minimizes CPU and disk access cost. We also provide an experimental study of performance focusing on query processing and index update overheads.

________________________________________________________________________We propose a unique cluster-based retrieval (CBR) strategy using a new cluster-skipping inverted file for improving query processing efficiency. The new inverted file incorporates cluster membership and centroid information along with the usual document information into a single structure. In our incremental-CBR strategy, during query evaluation both best(-matching) clusters and best(-matching) documents of such clusters are computed together with a single posting list access per query term. As we switch from term to term, best clusters are recomputed and can dynamically change. During query-document matching, only relevant portions of the posting lists corresponding to the best clusters are considered and the rest is skipped. The proposed approach is essentially tailored for environments where inverted files are compressed, and provides substantial efficiency improvements while yielding comparable or sometimes better effectiveness figures. Our experiments with various collections show that, the incremental-CBR strategy using compressed cluster-skipping inverted file significantly improves CPU time efficiency regardless of the query length. The new compressed inverted file imposes an acceptable storage overhead in comparison to a typical inverted file. We also show that our approach scales well with the collection size.

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