Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Citation - Scopus: 2Telsiz Duyarga Ağlarında Hızlı Hareket Eden Hedefler için Küme Tabanlı Hedef İzleme Algoritması(Institute of Electrical and Electronics Engineers Inc., 2009) Alaybeyoğlu, Ayşegül; Dağdeviren, Orhan; Kantarcı, Aylin; Erciyes, KayhanKablosuz iletişim teknolojilerindeki ilerlemelerle birlikte telsiz duyarga ağları (TDA) birçok sivil ve askeri uygulamalarda özellikle de hareketli hedefin takibi gibi konularda yaygın olarak kullanılmaya başlanmıştır. Bu çalışmada da TDA’da hızlı hareket eden nesneler için küme tabanlı bir hedef izleme algoritması önerilmiştir. Literatürde bulunan mevcut çalışmalarda lider düğüm, hedefin sadece t+1 anında yaklaşacağı konumu tahminleyerek bu konuma en yakın düğümü uyandırır. Hedefin çok hızlı hareket etmesi durumunda ise hedefin kısa süre içerisinde bir grup düğümün yakınlarından algılanmadan geçip gitmesi söz konusudur. Önermiş olduğumuz algoritma ile hedefin hızına bağlı olarak, hedefin tahmini gideceği yöndeki düğümler önceden uyandırılarak, kümeler önceden oluşturulmaktadır. Böylece hedefin ani hızlanması durumunda, önceden oluşturmuş olduğumuz kümeler sayesinde hedefin kaybolma riskini azaltmış bulunmaktayız.Article Citation - WoS: 15Citation - Scopus: 21Tracking Fast Moving Targets in Wireless Sensor Networks(Institution of Electronics and Telecommunication Engineers, 2010) Alaybeyoğlu, Ayşegül; Erciyeş, Kayhan; Kantarcı, Aylin; Dağdeviren, OrhanWe propose a dynamic distributed algorithm for tracking objects that move fast in a sensor network. In the earlier efforts in tracking moving targets, the current leader node at time t predicts the location only for time t + 1 and if the target moves in high speed, it can pass by a group of nodes very fast without being detected. Therefore, as the target increases its speed, the probability of missing that target also increases. In this study, we propose a target tracking system that predicts future k locations of the target and awakens the -corresponding leader nodes so that the nodes along the trajectory self organize to form the clusters to collect data related to the target in advance and thus reduce the target misses. The algorithm first -provides detection of the target and forms a cluster with the neighboring nodes around it. After the selection of the cluster leader, the coordinates of the target is estimated using localization methods and cooperation -between the cluster nodes under the control of the leader node. The coordinates and the speed of the target are then used to estimate its trajectory. This information in turn provides the location of the nodes along the estimated trajectory which can be awaken, hence providing tracking of the moving object. We describe the algorithm, analyze its efficiency and show by simulations that it performs well to track very fast moving objects with speeds much higher than reported in literature.Conference Object Citation - Scopus: 5A Distributed Wakening Based Target Tracking Protocol for Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2010) Alaybeyoğlu, Ayşegül; Dağdeviren, Orhan; Kantarcı, Aylin; Erciyeş, KayhanWe propose a two layer protocol for tracking fast targets in sensor networks. At the lower layer, the Distributed Spanning Tree Algorithm (DSTA) [12] partitions the network into clusters with controllable diameter and constructs a spanning tree backbone of clusterheads rooted at the sink. At the upper layer, we propose a target tracking algorithm which wakes clusters of nodes by using the estimated trajectory beforehand, which is different from existing studies [3] in which target can be detected only when the nodes close to the target are awake. We provide the simulation results and show the effect of fore-waking operation by comparing error and miss ratios of existing approaches with our proposed target tracking algorithm. © 2010 IEEE.Conference Object Citation - WoS: 13Citation - Scopus: 14Performance Evaluation of Cluster-Based Target Tracking Protocols for Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2009) Alaybeyoğlu, Ayşegül; Dağdeviren, Orhan; Erciyeş, Kayhan; Kantarcı, AylinTarget tracking is an important application type for wireless sensor networks (WSN). Recently, various approaches [1-11] are proposed to maintain the accurate tracking of the targets as well as low energy consumption. Clustering is a fundamental technique to manage the scarce network resources [12-19]. The message complexity of an application can be significantly decreased when it is redesigned on top of a clustered network. Clustering has provided an efficient infrastructure in many existing studies [1-8]. The clusters can be constructed before the target enters the region which is called the static method [1-4] or clusters are created by using received signal strength (RSS) from target which is called the dynamic method [5-8]. In this paper we provide simulations of static and dynamic clustering algorithms against various mobility models and target speeds. The mobility models that we applied are Random Waypoint Model, Random Direct Model and Gauss Markov Model. We provide metrics to measure the tracking performance of both approaches. We show that the dynamic clustering is favorable in terms of tracking accuracy whereas the energy consumption of static clustering is significantly smaller. We also show that the target moving with Gauss Markov Model can be tracked more accurately than the other models.