• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.777-779
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• 1999

A new distributed/parallel algorithm simulator, DASim(Distributed Algorithm Simulator), is proposed in this paper. The idea is to ease the task of design, analysis and implementation of distributed algorithms. A small high level language has been proposed for the purpose. Through this non-language specific high level language, the users are spared from the tedious details about how to program distributed or parallel algorithms. Further, visualization of these algorithms are pretty helpful to understand behaviors of these algorithms.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.63-72
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• 2022

Recently, blockchain has been attracting attention as a high-reliability technology in various fields. However, the Proof-of-Work-based distributed consensus algorithm applied to representative blockchains, such as Bitcoin and Ethereum, has limitations in applications to various industries owing to its excessive resource consumption and performance limitations. To overcome these limitations, various distributed consensus algorithms have appeared, and recently, hybrid distributed consensus algorithms that use two or more consensus algorithms to achieve decentralization and scalability have emerged. This paper introduces the technological trends of the latest high-performance distributed consensus algorithms by analyzing representative hybrid distributed consensus algorithms.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.191-200
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• 2001

Parallel Genetic Algorithms partition the whole population into several sub-populations and search the optimal solution by exchanging the information each others periodically. Distributed Genetic Algorithm, one of Parallel Genetic Algorithms, divides a large population into several sub-populations and executes the traditional Genetic Algorithm on each sub-population independently. And periodically promising individuals selected from sub-populations are migrated by following the migration interval and migration rate to different sub-populations. In this paper, for the Travelling Salesman Problems, we analyze and compare with Distributed Genetic Algorithms using different Genetic Algorithms and using same Genetic Algorithms on each separated sub-population The simulation result shows that using different Genetic Algorithms obtains better results than using same Genetic Algorithms in Distributed Genetic Algorithms. This results look like the property of rapidly searching the approximated optima and keeping the variety of solution make interaction in different Genetic Algorithms.

• Journal of the Korea Society for Simulation
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• v.2 no.1
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• pp.91-106
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• 1993

Load sharing in distributed systems improves systems performance. Research in the field has been focused on steady state performance for load sharing algorithms. However, transient characteristics of such algorithms may be important in a distributed system in which workload for some node is changing. Simulation is the only means to analyze such characteristics. This paper presents a simulation-based analysis of the transient characteristics of four load sharing algorithms ; forward probing, reverse probing, symmetric probing, and multi-threshold symmetric probing algorithms. Discrete event system models for execution of the algorithms in a distributed system has been developed in a SIMSCRIOT II.5 environment. Simulation results indicate that the MSYM algorithm shows the shortest response time in the transient period.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.257-267
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• 2004

Most algorithms for handling distributed deadlock problem in the generalized request model use the diffusing computation technique where propagation of probes and backward propagation of replies carrying dependency information between processes are both required to detect deadlock Since fast deadlock detection is critical, we propose an algorithm that lets probes rather than replies carry the information required for deadlock detection. This helps to remove the backward propagation of replies and reduce the time cost for deadlock detection to almost half of that of the existing algorithms. Moreover, the proposed algorithm is extended to deal with concurrent executions, which achieves further improvement of deadlock detection time, whereas the current algorithms deal only with a single execution. We compare the performance of the proposed algorithm with that of the other algorithms through simulation experiments.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.1-9
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• 2016

Algorithms implementing distributed shared memory (DSM) were developed for ensuring consistency. The performance of DSM algorithms is dependent on system and usage parameters. However, ensuring these algorithms to tolerate faults is a problem that needs to be researched. In this study, we proposed fault-tolerant scheme for DSM system and analyzed reliability and fault-tolerant overhead. Using our analysis, we can choose a proper algorithm for DSM on error prone environment.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.179-188
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• 2018

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

• International Journal of Contents
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• v.3 no.1
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• pp.34-38
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• 2007

Load redistribution is a critical resource in computer system. In sender-initiated load redistribution algorithms, the sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, we propose a genetic algorithm based approach for improved sender-initiated load redistribution in distributed systems. Compared with the conventional sender-initiated algorithms, the proposed algorithm decreases the response time and task processing time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.442-450
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• 2012

Almost domestic power plants are being operated by foreign distributed control system. Many korean power plants are being operated over their lifetime so they need to be retrofitted. So we are developing the distributed control system to solve this problem by our own technique. The simulator was already made to verify the reliability of the algorithms. The unit loop function tests of all algorithms were finished in the actual distributed control system for installation of power plant and their results were satisfactory. The unit loop function tests are for each unit equipment algorithm. So the total operation tests will be made with all algorithms together in the actual distributed control system to be applied to power plant. When the verification through all tests is finished, algorithms with hardware will be scheduled to be installed and operated in the actual power plant. This research result will contribute to the safe operation of the deteriorated power plant and korean electric power supply as well as domestic technical progress. This entire processes and results for the development are written for the example of boiler feedwater master algorithm out of all algorithms in this paper.