• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.38-43
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• 2011

Cluster-based routing is high energy consumption of cluster head nodes. A recent approach to resolving the problem is the dynamic cluster technique that periodically re-selects cluster head nodes to distribute energy consumption of the sensor nodes. However, the dynamic clustering technique has a problem that repetitive construction of clustering consumes the more energies. This paper proposes a solution to the problems described above from the energy efficiency perspective. The round-robin cluster header(RRCH) technique, which fixes the initially structured cluster and sequentially selects cluster head nodes, is suggested for solving the energy consumption problem regarding repetitive cluster construction. A simulation result were compared with the performances of two of the most widely used conventional techniques, the LEACH(Low Energy Adaptive Clustering Hierarchy) and HEED(Hybrid, Energy Efficient, Distributed Clustering) algorithms, based on energy consumption, remaining energy for each node and uniform distribution. The evaluation confirmed that in terms of energy consumption, the technique proposed in this paper was 26.5% and 20% more efficient than LEACH and HEED, respectively.

• The KIPS Transactions:PartC
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• v.16C no.4
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• pp.495-504
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• 2009

Wireless sensor networks (WSN) consisting of a largenumber of sensors aims to gather data in a variety of environments and is beingused and applied in many different fields. The sensor nodes composing a sensornetwork operate on battery of limited power and as a result, high energyefficiency and long network lifetime are major goals of research in the WSN. Inthis paper we propose a novel cluster-based local multi-hop routing protocolthat enhances the overall energy efficiency and guarantees reliability in thesystem. The proposed protocol minimizes energy consumption for datatransmission among sensor nodes by forming a multi-hop in the cluster.Moreover, through local cluster head rotation scheme, it efficiently manageswaste of energy caused by frequent formation of clusters which was an issue inthe existing methods. Simulation results show that our scheme enhances energyefficiency and ensure longer network time in the sensor network as comparedwith existing schemes such as LEACH, LEACH-C and PEACH.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.69-80
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• 2010

Wireless sensor networks (WSN) consisting of a large number of sensors aim to gather data in a variety of environments and are being used and applied to many different fields. The sensor nodes composing a sensor network operate on battery of limited power and as a result, high energy efficiency and long network lifetime are major goals of research in the WSN. In this paper we propose a novel tree-based clustering approach for energy efficient wireless sensor networks. The proposed scheme forms the cluster and the nodes in a cluster construct a tree with the root of the cluster-head., The height of the tree is the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme enhances energy efficiency and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4A
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• pp.388-398
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• 2011

In this paper, we introduce an EMSP(Efficient Mobility Support Protocol) for mobile sensor network with mobility-aware. We propose virtual cluster and node split scheme considering movements of mobile nodes. The existing M-LEACH protocol suffers from communication cost spent on JOIN request information during invitation phase. To address this issue, the large boundary of the cluster in LUR-tree can reduce superfluous update cost. In addition to the expansion of the cluster, the proposed approach exploits node split algorithms used in R-tree in order to uniformly form a cluster. The simulated results show that energy-consumption has less up to about 40% than LEACH-C and 8% than M-LEACH protocol. Finally, we show that the proposed scheme outperforms those of other in terms of lifetime of sensor fields and scalability in wireless sensor network.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.119-124
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• 2008

The LEACH is a study method of a clustering base that was representative in many routing techniques that was suggested in sensor network environment. This is suggested technique to manage the sensor network group which consisted of many sensors in efficiency. However, it does not consider energy remaining quantity of the cluster header to manage cluster group, the problem where the cluster group is able to destroyed on the middle which transmits data. We are going to propose to solve such a problem by this paper for new clustering technique to accomplish management for a cluster group. It uses the technique which it proposes from the dissertation which it sees and are to the data transfer and the control also the connection directivity of the cluster group to improve also the lag time diminishes, test result it will lead and the possibility which it will know it was.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.84-95
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• 2008

Wireless sensor networks have recently emerged as a platform for several applications. By deploying wireless sensor nodes and constructing a sensor network, we can remotely obtain information about the behavior, conditions, and positions of objects in a region. Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable to prolong the lifetime of a sensor network as long as possible. In this paper, we propose a novel clustering algorithm that distributes the energy consumption of a cluster head. First, we analyze the energy consumption if cluster heads and divide each cluster into a collection layer and a transmission layer according to their roles. Then, we elect a cluster head for each layer to distribute the energy consumption of single cluster head. In order to show the superiority of our clustering algorithm, we compare it with the existing clustering algorithm in terms of the lifetime of the sensor network. As a result, our experimental results show that the proposed clustering algorithm achieves about $10%{\sim}40%$ performance improvements over the existing clustering algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1164-1183
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• 2019

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.7-15
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• 2014

In this paper, we propose an efficient routing protocol to achieve an optimal route searching process of the network lifetime by balancing power consumption per node. The proposed protocols aim at finding energy-efficient paths at low protocol power. In our protocol, each intermediate node keeps power level and branch number of child nodes and it transmits the data the nearest neighbor node. Our protocol may minimize the energy consumption at each node, thus prolong the lifetime of the system regardless of the location of the sink outside or inside the cluster. In the proposed protocol for inter-cluster communication, a cluster head chooses a relay node from its adjacent cluster heads according to the node's residual energy and its distance to the base station. Simulation results show that proposed protocol successfully balances the energy consumption over the network, and achieves a remarkable network lifetime improvement as highly as 7.5%.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.61-69
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• 2009

Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing life-time of wireless sensor networks. In this paper, we present the threshold based cluster head replacement strategy for clustering protocols in wireless sensor networks. This protocol minimizes the number of cluster head selection by preventing the cluster head replacement up to the threshold of residual energy. Reducing the amount of head selection and replacement cost, the life-time of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that our protocol outperformed than LEACH in terms of balancing energy consumption and network life-time.