• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.696-704
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• 2005

Flooding is usually utilized to find a multi hop route toward the destination which is not within transmission range in Ad Hoc networks. However, existing flooding schemes deteriorate the network performance because of periodic message exchanges, frequent occurrence of collisions, and redundant packet transmission. To resolve this, a flooding scheme using on demand cluster formation is proposed in this paper. The scheme employs ongoing Packets for constructing a cluster architecture as the existing on demand clustering scheme. Unlike to the existing on demand clustering scheme, the scheme makes use of unicast packet transmission to reduce the number of collisions and to find the flooding candidates easily. As a result, the proposed scheme yields fewer flooding nodes than other schemes. Simulation results proved that the proposed scheme reduces the number of transmissions and collisions than those of two other schemes.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.1-14
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• 2006

Sort-last parallel rendering using a cluster of GPUs has been widely used as an efficient method for visualizing large- scale volume datasets. The performance of this method is constrained by load balancing when data parallelism is included. In previous works static partitioning could lead to self-balance when only task level parallelism is included. In this paper, we present a load balancing scheme that adapts to the characteristic of volume dataset when data parallelism is also employed. We effectively combine the hierarchical data structures (octree and BSP tree) in order to skip empty regions and distribute workload to corresponding rendering nodes. Moreover, we also exploit a 3D clustering method to determine visibility order and save the AGP bandwidths on each rendering node. Experimental results show that our scheme can achieve significant performance gains compared with traditional static load distribution schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.845-854
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• 2008

In this paper, we propose a clustering algorithm for efficient energy management of sensor network consisted of sensor nodes that have restricted energy to solve these problem. Proposed algorithm improves energy efficiency by controlling sensing power. And it has distinctive feature that is applied in various network environment. The performance evaluation result shows that the energy efficiency is improved by 5% in the case of all sensor node fixed and by $10{\sim}15%$ in the case of all sensor node moving. It is confirmed through experiment process that the proposed algorithm brings energy efficiency ratio improvement of $5{\sim}15%$ more than the existing algorithm. Proposed algorithm derived an upper bound on the energy efficiency for Ubiquitous Computing environment that have various network environment that is with ZigBee technology of IEEE 802.15.4 bases. Also, we can blow bring elevation for lifetime of sensor network greatly for lifetime of sensor node as is small. And we think that may expand practical use extent of a sensor network technology more in fast changed network environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.141-150
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• 2011

In this paper, we propose a Cross-Layer Cooperative Routing(CLCR) architecture to support transmission efficiency in mobile wireless sensor networks. The main features and contributions of the proposed architecture and method are as follows. First, the clustering which uses the location information of nodes is utilized as infrastructure. Second, a cross-layer strategy which uses the technologies of network layer, MAC layer, physical layer together to support transmission efficiency and channel efficiency for cooperative-aided routing and transmission. Third, we consider realistic approach in the view points of the mobile ad-hoc wireless sensor networks while conventional methods just consider fixed sensor network environments. The performance evaluation of the proposed method is performed via simulation using OPNET and theoretical analysis. The results of performance evaluation of the proposed CLCR show improvement of transmission efficiency by the proposed CLCR.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.6
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• pp.264-273
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• 2006

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) by means of consecutive optimization and also discuss its comprehensive design methodology involving mechanisms of genetic optimization. The network is based on a structurally as well as parametrically optimized fuzzy polynomial neurons (FPNs) conducted with the aid of information granulation and genetic algorithms. In structurally identification of FPN, the design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). For the parametric identification, we obtained the effective model that the axes of MFs are identified by GA to reflect characteristic of given data. Especially, the genetically dynamic search method is introduced in the identification of parameter. It helps lead to rapidly optimal convergence over a limited region or a boundary condition. To evaluate the performance of the proposed model, the model is experimented with using two time series data(gas furnace process, nonlinear system data, and NOx process data).

• Journal of KIISE:Databases
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• v.36 no.1
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• pp.50-62
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• 2009

In wireless and mobile environments, data broadcasting is recognized as an effective way for data dissemination due to its benefits to bandwidth efficiency, energy-efficiency, and scalability. In this paper, we address the problem of delayed query processing raised by tree-based index structures in wireless broadcast environments, which increases the access time of the mobile clients. We propose a novel distributed index structure and a clustering strategy for streaming XML data which enable energy and latency-efficient broadcast of XML data. We first define the DIX node structure to implement a fully distributed index structure which contains tag name, attributes, and text content of an element as well as its corresponding indices. By exploiting the index information in the DIX node stream, a mobile client can access the wireless stream in a shorter latency. We also suggest a method of clustering DIX nodes in the stream, which can further enhance the performance of query processing over the stream in the mobile clients. Through extensive performance experiments, we demonstrate that our approach is effective for wireless broadcasting of XML data and outperforms the previous methods.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.153-160
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• 2009

One of the major challenges of designing a dissemination protocol for Wireless Sensor Networks(WSNs) is energy efficiency. Recently, this issue has received much attention from the research community, and SPMS, which outperforms the well-known protocol SPIN, specially is a representative protocol. In addition, one of many characters of SPMS is the use of the shortest path to minimize the energy consumption. However, since it repeatedly uses the same path as the shortest path, the maximizing of the network lifetime is impossible, though it reduces the energy consumption. In this paper, we propose a dissemination protocol using probability-based clustering which guarantees energy-efficient data transmission and maximizes network lifetime. The proposed protocol solves the network lifetime problem by a novel probability function, which is related to the residual energy and the transmission radius between nodes. The simulation results show that it guarantees energy-efficient transmission and moreover increases the network lifetime by approximately 78% than that of SPMS.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.189-196
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• 2010

The LEACH does not use flooding method for data transmission and this makes low power consumption. So performance of the WSN is increased. On the other hand, QoS based algorithm which use restricted flooding method in WSN also achieves low power consuming rate by reducing the number of nodes that are participated in routing path selection. But when the data is delivered to the sink node, the LEACH choose a routing path which has a small hop count. And it leads that the performance of the entire network is worse. In the paper we propose a QoS based energy efficient clustering and routing algorithm in WSN. I classify the type of packet with two classes, based on the energy efficiency that is the most important issue in WSN. We provide the differentiated services according to the different type of packet. Simulation results evaluated by the NS-2 show that proposed algorithm extended the network lifetime 2.47 times at average. And each of the case in the class 1 and class 2 data packet, the throughput is improved 312% and 61% each.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.60-70
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• 2018

A software defined storage (SDS) is being deployed in cloud environment to allow multiple users to virtualize physical servers, but a solution for optimizing space efficiency with limited physical resources is needed. In the conventional data deduplication system, it is difficult to deduplicate redundant data uploaded to distributed storages. In this paper, we propose a distributed deduplication method using similarity-based clustering and multi-layer bloom filter. Rabin hash is applied to determine the degree of similarity between virtual machine servers and cluster similar virtual machines. Therefore, it improves the performance compared to deduplication efficiency for individual storage nodes. In addition, a multi-layer bloom filter incorporated into the deduplication process to shorten processing time by reducing the number of the false positives. Experimental results show that the proposed method improves the deduplication ratio by 9% compared to deduplication method using IP address based clusters without any difference in processing time.