Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
Browse
3 results
Search Results
Now showing 1 - 3 of 3
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.Article Citation - WoS: 14Citation - Scopus: 21A Survey of Agent Technologies for Wireless Sensor Networks(Medknow Publications and Media, 2011) Dagdeviren, Orhan; Korkmaz, İlker; Tekbacak, Fatih; Erciyeş, KayhanWireless sensor networks (WSNs) do not have a fixed infrastructure and consist of sensor nodes that perform sensing and communicating tasks. The WSNs have large application spectrum such as habitat monitoring, military surveillance, and target tracking, where sensor nodes may operate distributed in highly dynamic environments. Battery-constrained sensor nodes may aggregate the sensed data, localize themselves, and route the packets in an energy-efficient and decentralized manner to enable running the applications. Agents are capable of independent and autonomous action, so that they can successfully carry out tasks that have been delegated to them, thus agent-based approaches are very suitable to apply as the solution of the problems occurring in WSNs. So far many agent-based approaches were proposed for WSNs. This paper surveys the agent technologies for sensor networks by providing a classification, objectives and costs of these approaches with the open research problems. To the best of our knowledge, this is the first study that covers the intersection of the agent technology and sensor networks from a wide perspective.Article Citation - WoS: 13Citation - Scopus: 18Graph Matching-Based Distributed Clustering and Backbone Formation Algorithms for Sensor Networks(Oxford University Press, 2010) Dağdeviren, Orhan; Erciyeş, KayhanClustering 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.