• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.649-651
• /
• 2017

A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes' power and the clustering cost. We evaluate this performance through some experiments in terms of nodes' transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.6
• /
• pp.1107-1112
• /
• 2008

Clustering techniques, which are algorithm to increase the network lifetime in wireless sensor networks, is developed to minimize the energy consumption of nodes. Existing clustering techniques by to increase the network lifetime with equalizing each node's the energy consumption by rotating the role of CH(Cluster Head), but these algorithms did not present the solution that minimizes the energy consumption of neighboring nodes with sink. In this paper, we propose the clustering algorithm that prolongs the network lifetime by not including a part of nodes in POS(Personal Operating Space) of the sink in a cluster and communicating with sink directly to reduce the energy consumption of CH closed to sink.

• Journal of Information Management
• /
• v.42 no.1
• /
• pp.47-62
• /
• 2011

While an ideal author graph should have its nodes to represent authors, automatically-generated author graphs mostly use author names as their nodes due to the difficulty of resolving author names into individuals. However, employing author names as nodes of author graphs merges namesakes, otherwise separate nodes in the author graph, into the same node, which may distort the characteristics of the author graph. This study proposes an algorithm which resolves author ambiguities based on co-authorship and then yields an author graph consisting of not author name nodes but author nodes. Scientific collaboration relationship this algorithm depends on tends to produce the clustering results which minimize the over-clustering error at the expense of the under-clustering error. In experiments, the algorithm is applied to the real citation records where Korean namesakes occur, and the results are discussed.

• Journal of Korea Multimedia Society
• /
• v.13 no.6
• /
• pp.911-923
• /
• 2010

In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

• Journal of Information Processing Systems
• /
• v.7 no.1
• /
• pp.29-42
• /
• 2011

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way, since their energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor networks. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with the highest residual energy send data to the base station. Furthermore, we can save the energy of head nodes by using the modes selection method. The simulation results show that CPMS achieves longer lifetime and more data message transmissions than current important clustering protocols in wireless sensor networks.

• Journal of Computing Science and Engineering
• /
• v.1 no.2
• /
• pp.195-210
• /
• 2007

Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.7
• /
• pp.1735-1755
• /
• 2012

Wireless sensor networks (WSNs) are becoming increasingly attractive for a variety of applications and have become a hot research area. Routing is a key technology in WSNs and can be coarsely divided into two categories: flat routing and hierarchical routing. In a flat topology, all nodes perform the same task and have the same functionality in the network. In contrast, nodes in a hierarchical topology perform different tasks in WSNs and are typically organized into lots of clusters according to specific requirements or metrics. Owing to a variety of advantages, clustering routing protocols are becoming an active branch of routing technology in WSNs. In this paper, we present an overview on clustering routing algorithms for WSNs with focus on differentiating them according to diverse cluster shapes. We outline the main advantages of clustering and discuss the classification of clustering routing protocols in WSNs. In particular, we systematically analyze the typical clustering routing protocols in WSNs and compare the different approaches based on various metrics. Finally, we conclude the paper with some open questions.

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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.5
• /
• pp.942-948
• /
• 2016

WSN based on wireless sensor nodes, Sensor nodes can not be reassigned and recharged if they once placed. Each sensor node comes into being involved to a communication network with its limited energy. But the existing proposed clustering techniques, being applied to WSN environment with irregular dispersion of sensor nodes, have the network reliability issues which bring about a communication interruption with the local node feature of unbalanced distribution in WSN. Therefore, the communications participation of the sensor nodes in the suggested algorithm is extended by 25% as the sensor field divided in the light of the non-uniformed distribution of sensor nodes and a static or a dynamic clustering algorithm adopted according to its partition of sensor node density in WSN. And the entire network life cycle was extended by 14% to ensure the reliability of the network.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.2
• /
• pp.559-573
• /
• 2016

In this paper, we investigate the problem of achieving proportional fairness in hierarchical wireless sensor networks. Combining clustering formulation and scheduling, we maximize total bandwidth utility for proportional fairness while controlling the power consumption to a minimum value. This problem is decomposed into two sub-problems and solved in two stages, which are Clustering Formulation Stage and Scheduling Stage, respectively. The above algorithm, called CSPF_PC, runs in a network formulation sequence. In the Clustering Formulation Stage, we let the sensor nodes join to the cluster head nodes by adjusting transmit power in a greedy strategy; in the Scheduling Stage, the proportional fairness is achieved by scheduling the time-slot resource. Simulation results verify the superior performance of our algorithm over the compared algorithms on fairness index.