• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.455-460
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• 2001

For some applications, the computational structure changes dynamically during the program execution. When this happens, static partitioning and allocation of tasks are not enough to achieve high performance in parallel computers. In this paper, we propose a dynamic load balancing algorithm efficiently distributes the computation with dynamically growing tree structure to processors. We present an implementation technique for the algorithm on mesh architectures, and analyze its complexity. We also demonstrate through experiments how our algorithm provides good quality solutions.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.499-510
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• 2004

This paper proposes a heuristic load balancing algorithm for multiprocessor systems. The algorithm minimizes the number of idle links to distribute load traffic and reduces its communication cost. Each processor iteratively tries to transfer unit load to/from every neighbor processors. However, real load transfer is collectively done after complete load traffic calculation to minimize useless traffic. The proposed algorithm can be employed in various interconnection topologies with slight modifications. In this paper, it is applied to both hypercube and mesh environments. For performance evaluation, simulation studies are performed. The performance of proposed algorithm is compared to those of two well-known algorithms. The results show that the proposed algorithm always balances the loads perfectly. Furthermore, it reduces the communication costs by $70{\%}{\~}90{\%}$ in the hypercube ; and it reduces the cost by $\75{\%}$ in the mesh, compared to existing algorithms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.35-44
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• 2005

This paper proposes an efficient heuristic load balancing algorithm for multiprocessor systems. The algorithm minimizes the number of idle links to distribute load traffic and reduces its communication cost. Each processor iteratively tries to transfer unit load to/from all neighbor processors. However, real load transfer is collectively done after all load traffic is calculated. This prevents useless traffic and thus reduces the overall load traffic. The proposed algorithm can be employed in various interconnection topologies with slight modifications. In this paper, it is applied to hypercube, mesh, k-ary n-cube and general graph environments. For performance evaluation, simulation studies are performed. The proposed algorithm and the well-known existing algorithms are implemented and compared. The results show that the proposed algorithm always balances the loads perfectly. furthermore, in comparison with the existing algorithms, it reduces the communication costs by 77%, 74% and 73% in the hypercube, the mesh, and k-ary n-cube, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12B
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• pp.811-817
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• 2005

Efficient bandwidth management is necessary in order to provide high quality service to users in a multimedia wireless/mobile network. In this paper, I propose an on-line load balancing algorithm with preemption. This technique is able to balance the traffic load among cells accommodating heterogeneous multimedia services while ensuring efficient bandwidth utilization. The most important features of my algorithm are its adaptability, flexibility and responsiveness to current network conditions. In addition, my online scheme to control bandwidth adaptively is a cell-oriented approach. This approach has low complexity making it practical for real cellular networks. Simulation results indicate the superior performance of my algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1016-1026
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• 1994

In this paper, we have studied load balancing problems in distributed systems. The nodes of distributed systems exchange periodically system state information each other. The information is stored in history. Based on the information, we compute an expected load index(ELI) using a five-degree interpolation polynomial in Newton`s backward difference interpolation formula. A new location policy of dynamic load balancing systems makes use of the ELI. We show that its performance is better than that of the existing load balancing algorithm through a simulation study.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.218-223
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• 2021

Pervasive enhancement and required enforcement of the Internet of Things (IoTs) in a distributed massively multiplayer online architecture have effected in massive growth of Big-Data in terms of server over-load. There have been some previous works to overcome the overloading of server works. However, there are lack of considered methods, which is commonly applicable. Therefore, we propose a combing Sparse Auto-Encoder and Load-Balancing, which is ProGReGA for Big-Data of server loads. In the process of Sparse Auto-Encoder, when it comes to selection of the feature-pattern, the less relevant feature-pattern could be eliminated from Big-Data. In relation to Load-Balancing, the alleviated degradation of ProGReGA can take advantage of the less redundant feature-pattern. That means the most relevant of Big-Data representation can work. In the performance evaluation, we can find that the proposed method have become more approachable and stable.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.739-740
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• 2009

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.200-209
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• 2006

Load building is an important step to make the delivery supply chain efficient. We present a family of load makeup algorithms using market based control strategy, named LoadMarket, in order to build efficient loads where each load consists of a certain number of finished products having destinations. LoadMarket adopts Clark-Wright algorithm for generating initial endowment for Load Traders who cooperate to minimize either total travel distance or the variance with respect to the travel distances of loads by means of the spot market or double-sided auction market mechanism. The efficiency of the LoadMarket algorithms is illustrated using simulation based experiments.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.63-72
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• 2007

This paper introduces a load-balancing algorithm focusing on distributing web requests evenly into the web cluster servers. The load-balancing algorithms based on conventional periodic load-information update mechanism are not suitable for dynamic page applications, which are common in Cyber Foraging services, due to the problems caused by periodic synchronized load-information updating and the difficulties of work load estimation caused by embedded executing scripts of dynamic pages. Update-on-Finish algorithm solves this problem by using non-periodic load-update mechanism, and the web switch knows the servers' real load information only after their reporting and then distributes new loads according to the new load-information table, however it results in much communication overhead. Our proposed mechanism improve update-on-finish algorithm by using K-Percents-Finish mechanism and thus largely reduce the communication overhead. Furthermore, we consider the different capabilities of servers with a threshold Ti value and propose a load-balancing algorithm for servers with various capabilities. Simulation results show that the proposed K-Percents-Finish Reporting mechanism can at least reduce 50% communication overhead than update-on-finish approach while sustaining better load balancing performance than periodic mechanisms in related work.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.667-680
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• 2016

As distributed computing platforms like Hadoop MapReduce have been developed, it is necessary to perform the conventional query processing techniques, which have been executed in a single computing machine, in distributed computing environments efficiently. Especially, studies on similarity join query processing in distributed computing environments have been done where similarity join means retrieving all data pairs with high similarity between given two data sets. But the existing similarity join query processing schemes for distributed computing environments have a problem of skewed computing load balance between clusters because they consider only the data transmission cost. In this paper, we propose Matrix-based Load-balancing Algorithm for efficient similarity join query processing in distributed computing environment. In order to uniform load balancing of clusters, the proposed algorithm estimates expected computing cost by using matrix and generates partitions based on the estimated cost. In addition, it can reduce computing loads by filtering out data which are not used in query processing in clusters. Finally, it is shown from our performance evaluation that the proposed algorithm is better on query processing performance than the existing one.