Research ArticleOpen accessEvery word in the titleSleeping Cluster based Medium Access Control Layer Routing Protocol for Wireless Sensor NetworksT. Nagamalar, T. R. RangaswamyWireless sensor networks play a vital role in remote area applications, where human intervention is not possible. In a Wireless Sensor Network (WSN) each and every node is strictly an energy as well as bandwidth constrained one. Problem Statement: In a standard WSN, most of the routing techniques, move data from multiple sources to a single fixed base station. Because … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 6,686 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleData Relay Clustering Algorithm for Wireless Sensor Networks: A Data Mining ApproachS. Nithyakalyani, S. Suresh KumarProblem statement: Nowadays sensors are very essential for today life to monitor environment where human cannot get involved very often. Wireless Sensor Networks (WSN) are used in many real world applications like environmental monitoring, traffic control, trajectory monitoring. It is more challenging for sensor network to sense and collect a large amount of data which are continuous over time, which … …Journal of Computer Science, Vol. 8, Issue 8 · 14 Jul 2012 · 7,193 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCluster Based Data Consistency for Cooperative Caching over Partitionable Mobile Adhoc NetworkP. Kuppusamy, B. KalaavathiProblem statement: Data availability and consistency are foremost issues in Mobile Ad hoc Networks due to the absence of permanent infrastructure. Cooperative caching addresses the data availability issue through coordinating the mobile nodes and sharing the cache copies among them. In the meantime, the mobile node must ensure the staleness of cache copies. The consistency maintenance resolves the staleness of … …American Journal of Applied Sciences, Vol. 9, Issue 8 · 10 Jul 2012 · 6,853 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDistributed Cluster Based Routing Technique with Multiple Sinks for Wireless Sensor NetworksS. V. Manisekaran, R. VenkatesanProblem Statement: In order to reduce or minimize energy consumption and to improve bandwidth utilization in Wireless Sensor Networks (WSN), it was essential to consider its architecture in the network topology, power consumption, data rate and fault tolerance. Our objective is to formulate an effective cluster formation of nodes with multiple sinks to reduce power consumption and minimize the data … …American Journal of Applied Sciences, Vol. 9, Issue 8 · 28 Jun 2012 · 6,865 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Density Based Dynamic Data Clustering Algorithm based on Incremental DatasetS. Angel Latha Mary, K.R. Shankar KumarProblem statement: Clustering and visualizing high-dimensional dynamic data is a challenging problem. Most of the existing clustering algorithms are based on the static statistical relationship among data. Dynamic clustering is a mechanism to adopt and discover clusters in real time environments. There are many applications such as incremental data mining in data warehousing applications, sensor network, which relies on dynamic … …Journal of Computer Science, Vol. 8, Issue 5 · 20 Feb 2012 · 7,465 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Efficient Way for Clustering Using Alternative Decision TreeE. Gothai, P. BalasubramanieProblem statement: To Improve the quality of clustering; a Multi-Level Clustering (MLC) algorithm which produces a most accurate cluster with most closely related object using Alternative Decision Tree (ADT) technique is proposed. Approach: Our proposed method combines tree projection and condition for clustering formation and also is capable to produce a customizable cluster for varying kind of data along with … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 13 Feb 2012 · 6,739 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Cluster Feature-Based Incremental Clustering Approach to Mixed DataA. M. Sowjanya, M. ShashiProblem statement: The main objective of this study is to develop an incremental clustering algorithm that can handle numerical as well as categorical attributes in a given dataset. The authors have previously reported a cluster feature-based algorithm, CFICA that can handle only numerical data. Appraoch: Since many of the real life data mining applications work with datasets that contain both … …Journal of Computer Science, Vol. 7, Issue 12 · 21 Oct 2011 · 7,159 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUsing Hyper Clustering Algorithms in Mobile Network PlanningLamiaa Fattouh Ibrahim, Hesham A. SalmanProblem statement: As a large amount of data stored in spatial databases, people may like to find groups of data which share similar features. Thus cluster analysis becomes an important area of research in data mining. Applications of clustering analysis have been utilized in many fields, such as when we search to construct a cluster served by base station in … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 30 Aug 2011 · 7,504 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,671 accessesView PDFCite