• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.406-409
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• 2008

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.237-244
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• 2021

Clustering is a most powerful un-supervised machine learning techniques for division of instances into homogenous group, which is called cluster. This Clustering is mainly used for generating a good quality of cluster through which we can discover hidden patterns and knowledge from the large datasets. It has huge application in different field like in medicine field, healthcare, gene-expression, image processing, agriculture, fraud detection, profitability analysis etc. The goal of this paper is to explore both hierarchical as well as partitioning clustering and understanding their problem with various approaches for their solution. Among different clustering K-means is better than other clustering due to its linear time complexity. Further this paper also focused on data mining that dealing with high-dimensional datasets with their problems and their existing approaches for their relevancy

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.169-178
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• 2023

Wireless sensor network is wieldy use for IoT application. The sensor node consider as physical device in IoT architecture. This all sensor node are operated with battery so the power consumption is very high during the data communication and low during the sensing the environment. Without proper planning of data communication the network might be dead very early so primary objective of the cluster based routing protocol is to enhance the battery life and run the application for longer time. In this paper we have comprehensive of twenty research paper related with clustering based routing protocol. We have taken basic information, network simulation parameters and performance parameters for the comparison. In particular, we have taken clustering manner, node deployment, scalability, data aggregation, power consumption and implementation cost many more points for the comparison of all 20 protocol. Along with basic information we also consider the network simulation parameters like number of nodes, simulation time, simulator name, initial energy and communication range as well energy consumption, throughput, network lifetime, packet delivery ration, jitter and fault tolerance parameters about the performance parameters. Finally we have summarize the technical aspect and few common parameter must be fulfill or consider for the design energy efficient cluster based routing protocol.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.427-429
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• 2005

Energy efficiency is the most challenging issue in wireless sensor network to prolong the life time of the network, as the sensors has to be unattended. Cluster based communication can reduce the traffic on the network and gives the opportunity to other sensors for periodic sleep and thus save energy. Passive clustering (PC) can perform a significant role to minimize the network load as it is less computational and light weight. First declaration wins method of PC without any priority generates severe collision in the network and forms the clusters very dense with large amount of overlapping region. We have proposed several modifications for the existing passive clustering algorithm to prolong the life time of the network with better cluster formation.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.117-121
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• 2008

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Therefore, the energy consumption is important in the routing design, otherwise cluster schemes are efficient in energy conserving. For the above reasons, an Energy conserving Context aware Clustering algorithm (ECC) is proposed to establish the network clustering structure, and a routing algorithm is introduced to choose the Optimal Energy Routing Protocol (OERP) path in this paper. Because in ad hoc network, the topology, nodes residual energy and energy consuming rate are dynamic changing. The network system should react continuously and rapidly to the changing conditions, and make corresponding action according different conditions. So we use the context aware computing to actualize the cluster head node, the routing path choosing. In this paper, we consider a novel routing protocol using the cluster schemes to find the optimal energy routing path based on a special topology structure of Resilient Ontology Multicasting Routing Protocol (RODMRP). The RODMRP is one of the hierarchical ad hoc network structure which combines the advantage of the tree based and the mesh based network. This scheme divides the nodes in different level found on the node energy condition, and the clustering is established based on the levels. This protocol considered the residual energy of the nodes and the total consuming energy ratio on the routing path to get the energy efficiently routing. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.47-56
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• 2012

In this study, we use a parallel simulator PASENS(Parallel SEnsor Network Simulator) to predict power consumption and data reception rate of the hierarchical routing protocols for sensor network - LEACH (Low-Energy Adaptive Clustering Hierarchy), TL-LEACH (Two Level Low-Energy Adaptive Clustering Hierarchy), M-LEACH (Multi hop Low-Energy Adaptive Clustering Hierarchy) and LEACH-C (LEACH-Centralized). According to simulation results, M-LEACH routing protocol shows the highest data reception rate for the wider area, since more sensor nodes are involved in the data transmission. And LEACH-C routing protocol, where the sink node considers the entire node's residual energy and location to determine the cluster head, results in the most efficient energy consumption and in the narrow area needed long life of sensor network.

• Journal of Information Technology Services
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• v.9 no.3
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• pp.95-106
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• 2010

Many researches have been performed to increase energy-efficiency in wireless sensor networks. One of primary research topics is about clustering protocols, which are adopted to configure sensor networks in the form of hierarchical structures by grouping sensor nodes into a cluster. However, legacy clustering protocols do not propose detailed methods from the perspective of implementation to determine a cluster's boundary and configure a cluster, and to communicate among clusters. Moreover, many of them involve assumptions inappropriate to apply those to a sensor field. In this paper, we have designed and implemented a new T-Clustering (Top-down Clustering) protocol, which takes into considerations a node's density, a distance between cluster heads, and remained energy of a node all together. Our proposal is a sink-node oriented top-down clustering protocol, and can form uniform clusters throughout the network. Further, it provides re-clustering functions according to the state of a network. In order to verify our protocol's feasibility, we have implemented and experimented T-Clustering protocol on Crossbow's MICAz nodes which are executed on TinyOS 2.0.2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1050-1057
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• 2010

Nowadays, the network attack occurs frequently. At the same time, the inbound network is also attacked. Even though the security system has been continuously developed in order to prevent from attacks, the network performance is sacrificed for the network security. Therefore, a security system which obtains performance and security together is urgently needed. In this paper, an arrangement of functional firewall and a secure clustering methodology, obtained from distributing functions of a conventional firewall, are proposed based on the idea that performance and security should be obtained together.

• Korean Management Science Review
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• v.26 no.3
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• pp.55-65
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• 2009

The objective of this paper is to propose an ant colony optimization (ACO) for clustering design in wireless sensor network problem. This proposed ACO approach is designed to deal with the dynamics of the sensor nodes which can be adaptable to topological changes to any network graph in a time. Long communication distances between sensors and a sink in a sensor network can greatly consume the energy of sensors and reduce the lifetime of a network. We can greatly minimize the total communication distance while minimizing the number of cluster heads using proposed ACO. Simulation results show that our proposed method is very efficient to find the best solutions comparing to the optimal solution using CPLEX in 100, 200, and 400 node sensor networks.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1836-1842
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• 2015

On road networks, the clustering of moving objects is important for traffic monitoring and routes recommendation. The existing schemes find out density route by considering the number of vehicles in a road segment. Since they don’t consider the features of each road segment such as width, length, and directions in a road network, the results are not correct in some real road networks. To overcome such problems, we propose a clustering method for congested routes discovering from the trajectories of moving objects on road networks. The proposed scheme can be divided into three steps. First, it divides each road network into segments with different width, length, and directions. Second, the congested road segments are detected through analyzing the trajectories of moving objects on the road network. The saturation degree of each road segment and the average moving speed of vehicles in a road segment are computed to detect the congested road segments. Finally, we compute the final congested routes by using a clustering scheme. The experimental results showed that the proposed scheme can efficiently discover the congested routes in different directions of the roads.