• The KIPS Transactions:PartC
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• v.14C no.6
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• pp.519-524
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• 2007

One of the most important issues on the sensor network with resource limited sensor nodes is prolonging the network lifetime by effectively utilizing the limited node energy. The most representative mechanism to achieve a long lived sensor network is the clustering mechanism which can be further classified into the single hop mode and the multi hop mode. The single hop mode requires that all sensor nodes in a cluster communicate directly with the cluster head(CH) via single hop md, in the multi hop mode, sensor nodes communicate with the CH with the help of other Intermediate nodes. One of the most critical factors that impact on the performance of the existing multi hop clustering mechanism is the cluster size and, without the assumption on the uniform node distribution, finding out the best cluster size is intractable. Since sensor nodes in a real sensor network are distributed non uniformly, the fixed size mechanism may not work best for real sensor networks. Therefore, in this paper, we propose a new dynamic size multi hop clustering mechanism in which the cluster size is determined according to the distance from the sink to relieve the traffic passing through the CHs near the sink. We show that our proposed scheme outperforms the existing fixed size clustering mechanisms by carrying out numerical analysis and simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.2
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• pp.1-11
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• 2002

In the present study, a parallel DSCM technique based on a cell-based data structure is developed for the efficient simulation of rarefied gas flows especially od PC clusters. Dynamic load balancing is archieved by decomposing the computational domain into several sub-domains and accounting for the number of particles and the number cells of each domain. Mesh adaptation algorithm is also applied to improve the resolution of the solution and to reduce the grid dependency. It was demonstrated that accurate solutions can be obtained after several levels of mesh adapation starting from a coars initial grid. The method was applied to a two-dimensioanal supersonic leading-edge flow and the axi-symmetric Rothe nozzle flow to validate the efficiency of the present method. It was found that the present method is a very effective tool for the efficient simulation of rarefied gas flow on PC-based parallel machines.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12B
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• pp.818-830
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• 2005

Recently, Peer-to-Peer (P2P) overlay networks like CAN, Chord, Pastry and Tapestry offer a novel platform for scalable and decentralized distributed applications. These systems provide efficient and fault-tolerant routing, object location, and load balancing within a self-organizing overlay network. Content Delivery Network (CDN) is an intermediate layer of infrastructure that helps to efficiently deliver the multimedia content from content providers to clients. In this paper, We propose a topology-aware P2P overlay network for CDN, Rosary, in which CDN servers perform Intra-Pastry and Inter-Pastry routing based on a two-level structured overlay network. This proposed system extends pastry by adapting itself to CDN environments, where a semi-hashing based scheme for Intra-Pastry routing is introduced, and dynamic landmark technology is used to construct the topology-aware overlay network. Through simulations on NS-2, it is shown that Rosary is scalable, efficient, and flexible.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.109-116
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• 2008

Even though many studies on parallel rendering based on PC clusters have been done. most of those did not cope with non-uniform scenes, where locations of 3D models are biased. In this work. we have built a PC cluster system with POV-Ray, a free rendering software on the public domain, and developed an adaptive load balancing scheme to optimize the parallel efficiency Especially, we noticed that a frame of 3D animation are closely coherent with adjacent frames. and thus we could estimate distribution of computation amount, based on the computation time of previous frame. The experimental results with 2 real animation data show that the proposed scheme reduces by 40% of execution time compared to the simple static partitioning scheme.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.129-139
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• 2003

The PC cluster architecture is considered as a cost-effective alternative to the existing supercomputers for realizing a high-performance information retrieval (IR) system. To implement an efficient IR system on a PC cluster, it is essential to achieve maximum parallelism by having the data appropriately distributed to the local hard disks of the PCs in such a way that the disk I/O and the subsequent computation are distributed as evenly as possible to all the PCs. If the terms in the inverted index file can be classified to closely related clusters, the parallelism can be maximized by distributing them to the PCs in an interleaved manner. One of the goals of this research is the development of methods for automatically clustering the terms based on the likelihood of the terms' co-occurrence in the same query. Also, in this paper, we propose a method for duplicate distribution of inverted index records among the PCs to achieve fault-tolerance as well as dynamic load balancing. Experiments with a large corpus revealed the efficiency and effectiveness of our method.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.435-447
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• 2004

For VOD systems, it is important to provide QoS to more users under the limited resources. To analyze QoS issues in real environment, we implement clustered VOD server and embedded client system based on the Linux open source platform. The parallel processing of MPEG data, load balancing for nodes and VCR like functions are implemented in the server side. To provide more user friendly interface, the general TV is used for a VOD client's terminal and the embedded board is used supporting for VCR functions. In this paper, we measure the performance of the implemented VOD system under the various user requirement features and evaluate the sources of performance limitations. From these analyses, we propose the dynamic admission control method based on the availability memory and network bandwidth. The proposed method enhances the utilization of the system resource for the more QoS media streams.

• Journal of KIISE
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• v.42 no.1
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• pp.15-22
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• 2015

In this paper, we present a case study for a drug repositioning simulation based on distributed supercomputing technology that requires highly efficient processing of large-scale computations. Drug repositioning is the application of known drugs and compounds to new indications (i.e., new diseases), and this process requires efficient processing of a large number of docking tasks with relatively short per-task execution times. This mechanism shows the main characteristics of a Many-Task Computing (MTC) application, and as a representative case of MTC applications, we have applied a drug repositioning simulation in our HTCaaS system which can leverage distributed supercomputing infrastructure, and show that efficient task dispatching, dynamic resource allocation and load balancing, reliability, and seamless integration of multiple computing resources are crucial to support these challenging scientific applications.

• Annual Conference of KIPS
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• 2010.04a
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• pp.210-213
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• 2010

최근 사용자의 멀티미디어에 대한 요구의 증가가 VOD (Video-on-Demand) 서비스를 발전시키게 되었다. VOD는 엔터테인먼트나 원격 교육, 광고 및 정보 등 많은 분야에서 사용되고 있다. 이러한 VOD 서비스는 많은 디스크 I/O와 네트워크 I/O를 요구하며 기존 웹 서버 시스템과 비교했을 때 오랜 시간동안 서비스를 해야 하는 특징을 가지고 있다. 또한 VOD 서비스는 많은 네트워크와 디스크의 대역폭을 요구하며, 서비스의 QoS에 민감해서 사용자 응답시간이 길어지면 사용자 요청의 취소율이 높아지게 된다. 따라서 불만족스러운 서비스의 증가로 네트워크 부하만 증가하게 된다. 이러한 기존 웹 서버 환경과는 다른 부하의 패턴이 있는 VOD 서비스 환경에서는 부하를 균형적으로 분배하여 서비스의 QoS를 높이는 것이 매우 중요하다. 본 논문에서는 분산 VOD 시스템 환경에서 부하를 효율적으로 분산하기 위해 계층형 분산 VOD 시스템 모델과 사용자 요청 패턴의 히스토리와 유전 알고리즘을 기반으로 한 스케줄러를 제안한다. 본 논문에서 제안한 계층형 분산 VOD 시스템 모델은 서버들을 지역적으로 분산하고 제어 서버를 지역마다 설치하여 지역에 있는 VOD 서버들을 관리하도록 구성한다. 사용자 요청을 지역 서버군 내에서 분산시키기 위해서 히스토리를 기반으로 한 유전 알고리즘을 사용한다. 이러한 히스토리 정보를 기반으로 유전 알고리즘의 적합도 함수에 적용하여 VOD 시스템을 위한 유전 알고리즘과 유전 연산을 구현한다. 본 논문에서 제안한 부하 분산 알고리즘은 VOD 서비스 환경에서 사용자 요구에 대한 부하를 보다 정확하게 예측하여 부하를 분산할 수 있다. 본 논문에서 제안한 계층형 분산 VOD 시스템의 부하 분산 알고리즘의 성능을 테스트하기 위해 OPNET 기반 시뮬레이터를 구현한다. 라운드로빈(round-robin) 방식과 랜덤(random) 방식과의 비교 실험을 통해 본 논문에서 제안한 부하 분산 알고리즘의 성능을 평가한다. 비교 실험을 통해 본 논문에서 제안한 알고리즘이 보다 안정적인 QoS를 제공하는 것을 보여준다.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.75-89
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• 2006

LBS (Location-Based Service) systems have become a serious subject for research and development since recent rapid advances in wireless communication technologies and position measurement technologies such as global positioning system. The architecture named the GALIS (Gracefully Aging Location Information System) has been suggested which is a cluster-based distributed computing system architecture to overcome performance losses and to efficiently handle a large volume of data, at least millions. The GALIS consists of SLDS and LLDS. The SLDS manages current location information of moving objects and the LLDS manages past location information of moving objects. In this thesis, we implement a monitoring technique for the GALIS prototype, to allow dynamic load balancing among multiple computing nodes by keeping track of the load of each node in real-time during the location data management and spatio-temporal query processing. We also propose a buffering technique which efficiently manages the query results having overlapped query regions to improve query processing performance of the GALIS. The proposed scheme reduces query processing time by eliminating unnecessary query execution on the overlapped regions with the previous queries.