• The Journal of Information Systems
• /
• v.14 no.3
• /
• pp.53-58
• /
• 2005

In this study, we will employ a multi-agent for the search and extraction of data in a distributed environment. We will use an Integrator Agent in the proposed model on the Hierarchical Clustering and Association Rule Discovery(HCARD). The HCARD will address the inadequacy of other data mining tools in processing performance and efficiency when use for knowledge discovery. The Integrator Agent was developed based on CORBA architecture for search and extraction of data from heterogeneous servers in the distributed environment. Our experiment shows that the HCARD generated essential association rules which can be practically explained for decision making purposes. Shorter processing time had been noted in computing for clusters using the HCARD and implying ideal processing period than computing the rules without HCARD.

• Journal of Internet Computing and Services
• /
• v.18 no.6
• /
• pp.47-53
• /
• 2017

Recently, huge datasets have been generating rapidly in a variety of fields. Then, there is an urgent need for technologies that will allow efficient and effective processing of huge datasets. Therefore the problems of partitioning a huge dataset effectively and alleviating the processing overhead of the partitioned data efficiently have been a critical factor for scalability and performance in distributed database system. In our work we utilized multicore servers to provide scalable service to our distributed system. The partitioning of database over multicore servers have emerged from a need for new architectural design of distributed database system from scalability and performance concerns in today's data deluge. The system allows uniform access through a web service interface to concurrently distributed databases over multicore servers, using SQMD (Single Query Multiple Database) mechanism based on publish/subscribe paradigm. We will present performance results with the distributed database system built on multicore server, which is time intensive with traditional architectures. We will also discuss future works.

• KIISE Transactions on Computing Practices
• /
• v.24 no.3
• /
• pp.105-112
• /
• 2018

As data size increase, a single database is not enough to serve current volume of tasks. Since data is partitioned and stored into multiple databases, analysis should also support parallelism in order to increase efficiency. However, traditional analysis requires data to be transferred out of database into nodes where analytic service is performed and user is required to know both database and analytic framework. In this paper, we propose an efficient way to perform K-means clustering algorithm inside the distributed column-based database and relational database. We also suggest an efficient way to optimize K-means algorithm within relational database.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.3 s.357
• /
• pp.18-25
• /
• 2007

In sensor networks, sensor nodes have limited computational capacity, power and memory. Thus energy efficiency is one of the most important requirements. How to extend the lifetime of wireless sensor networks has been widely discussed in recent years. However, one of the most effective approaches to cope with power conservation, network scalability, and load balancing is clustering technique. The function of a cluster head is to collect and route messages of all the nodes within its cluster. Cluster heads must be changed periodically for low energy consumption and load distribution. In this paper, we propose an energy-aware cluster head selection algorithm and Distance Estimation-based distributed Clustering Algorithm (DECA) in wireless sensor networks, which exchanges cluster heads for less energy consumption by distance estimation. Our simulation result shows that DECA can improve the system lifetime of sensor networks up to three times compared to the conventional scheme.

• Convergence Security Journal
• /
• v.16 no.5
• /
• pp.3-9
• /
• 2016

The wireless sensor networks have become an economically viable monitoring solution for a wide variety of civilian and military applications. The main challenge in wireless sensor networks is the secure transmission of information through the network, which ensures that the network is secure, energy-efficient and able to identify and prevent intrusions in a hostile or unattended environment. In that correspondence, this paper proposes a distributed clustering process that integrates the necessary measures for secure wireless sensors to ensure integrity, authenticity and confidentiality of the aggregated data. We use the notion of pre-distribution of symmetric and asymmetric keys for a secured key management scheme, and then describe the detailed scheme which each sensor node within its cluster makes use of the pre-distribution of cryptographic parameters before deployment. Finally, we present simulation results for the proposed scheme in wireless sensor network.

• International Journal of Contents
• /
• v.8 no.2
• /
• pp.13-18
• /
• 2012

In wireless sensor networks, an energy efficient data gathering scheme is one of core technologies to process a query. The cluster-based data gathering methods minimize the energy consumption of sensor nodes by maximizing the efficiency of data aggregation. However, since the existing clustering methods consider only uniform network environments, they are not suitable for the real world applications that sensor nodes can be distributed unevenly. To solve such a problem, we propose a balanced multi-hop clustering scheme in non-uniform wireless sensor networks. The proposed scheme constructs a cluster based on the logical distance to the cluster head using a min-distance hop count. To show the superiority of our proposed scheme, we compare it with the existing clustering schemes in sensor networks. Our experimental results show that our proposed scheme prolongs about 48% lifetime over the existing methods on average.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.4
• /
• pp.665-683
• /
• 2011

Wireless sensor networks (WSN) consist of a large amount of sensor nodes distributed in a certain region. Due to the limited battery power of a sensor node, lots of energy-efficient schemes have been studied. Clustering is primarily used for energy efficiency purpose. However, clustering in WSNs faces several unattained issues, such as ensuring connectivity and scheduling inter-cluster transmissions. In this paper, we propose a location-based spiral clustering (LBSC) algorithm for improving connectivity and avoiding inter-cluster collisions. It also provides reliable location aware routing paths from all cluster heads to a sink node during cluster formation. Proposed algorithm can simultaneously make clusters in four spiral directions from the center of sensor field by using the location information and residual energy level of neighbor sensor nodes. Three logical addresses are used for categorizing the clusters into four global groups and scheduling the intra- and inter-cluster transmission time for each cluster. We evaluated the performance with simulations and compared it with other algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.29 no.7
• /
• pp.62-70
• /
• 2015

The energy of a sensor in a Wireless Sensor Network (WSN) puts a limit on the lifetime of the network. To prolong the lifetime, a clustering plan is used. Clustering technology gets its energy efficiency through reducing the number of communication occurrences between the sensors and the base station (BS). In the distributed clustering protocol, LEACH-like (Low Energy Adaptive Clustering Hierarchy - like), the number of sensor's cluster head (CH) roles is different depending on the sensor's residual energy, which prolongs the time at which half of nodes die (HNA) and network lifetime. The position of the CH in each cluster tends to be at the center of the side close to BS, which forces cluster members to consume more energy to send data to the CH. In this paper, a protocol, pseudo-LEACH, is proposed, in which a cluster with a CH placed at the center of the cluster is formed. The scheme used allows the network to consume less energy. As a result, the timing of the HNA is extended and the stable network period increases at about 10% as shown by the simulation using MATLAB.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.571-573
• /
• 2009

Mobile Ad-hoc Network(MANET) needs efficient node management because the wireless network has energy constraints. Mobility of MANET would require the topology change frequently compared with a static network. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. Previously proposed a hybrid routing CACH prolong the network lifetime and decrease latency. However the algorithm has a problem when node density is increase. In this paper, we propose a new method that the CACHE(Context-aware Clustering Hierarchy and Energy efficient) algorithm. The proposed analysis could not only help in defining the optimum depth of hierarchy architecture CACH utilize, but also improve the problem about node density.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.5
• /
• pp.341-350
• /
• 2014

In this paper, an energy efficient clustering scheme using self organization method is proposed. The proposed scheme selects a cluster head considering not only the number of neighbor nodes but also the residual battery amount. In addition, the network life time is extended by re-selecting the cluster heads only in case the current cluster head's residual energy falls down below a certain threshold level. Accordingly, the energy consumption is evenly distributed over the entire network nodes. The cluster head delivers the collected data from member nodes to a Sink node in a way of multi-hop relaying. In order to evaluate the proposed scheme, we run computer simulation in terms of the total residual amount of battery, the number of alive nodes after a certain amount of time, the accumulated energy cost for network configuration, and the deviation of energy consumption of all nodes, comparing with LEACH which is one of the most popular network clustering schemes. Numerical results show that the proposed scheme has twice network life-time of LEACH scheme and has much more evenly distributed energy consumption over the entire network.