• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.259-270
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• 2009

The applicability of the developed distributed rainfall runoff model using a multi-directional flow allocation algorithm and a real-time updating algorithm was evaluated. The rainfall runoff processes were simulated for the events of the Andong dam basin and the Namgang dam basin using raingauge network data and weather radar rainfall data, respectively. Model parameters of the basins were estimated using previous storm event then those parameters were applied to a current storm event. The physical propriety of the multi-directional flow allocation algorithm for flow routing was validated by presenting the result of flow grouping for the Andong dam basin. Results demonstrated that the developed model has efficiency of simulation time with maintaining accuracy by applying the multi-directional flow allocation algorithm and it can obtain more accurate results by applying the real-time updating algorithm. In this study, we demonstrated the applicability of a distributed rainfall runoff model for the advanced basin-wide flood management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.208-209
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• 2011

In this paper, we introduce a Naive Bayes learning algorithm for learning and reasoning in Map-Reduce model based environment. For this purpose, we use Apache Mahout to execute Distributed Naive Bayes on University of California, Irvine (UCI) benchmark data sets. From the experimental results, we see that Apache Mahout' s Distributed Naive Bayes algorithm is comparable to WEKA' s Naive Bayes algorithm in terms of performance. These results indicates that in the future Big Data environment, Map-Reduce model based systems such as Apache Mahout can be promising for machine learning usage.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.615-629
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• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.558-567
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• 2015

In recent years, we have seen a proliferation of mobile-network-enabled smart objects, such as smart-phones and smart-watches, that form a cyber-physical integrated network to connect the cyber and physical worlds through the capabilities of sensing, communicating, and computing. Discovery of the relationship between smart objects is a critical and nontrivial task in cyber-physical integrated network applications. Aiming to find the most stable relationship in the heterogeneous and dynamic cyber-physical network, we propose a distributed and efficient relationship-discovery algorithm, called dynamically maximizing remaining unchanged time with minimum connected dominant set (DMRUT-MCDS) for constructing a backbone with the smallest scale infrastructure. In our proposed algorithm, the impact of the duration of the relationship is considered in order to balance the size and sustain time of the infrastructure. The performance of our algorithm is studied through extensive simulations and the results show that DMRUT-MCDS performs well in different distribution networks.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.3
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• pp.120-130
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• 2001

We present an approach to parallelizing optimal power flow that is suitable for distributed implementation and is applicable to very large interconnected power systems. This approach can be used by utilities to optimize economy interchange without disclosing details of their operating costs to competitors. Recently, it is becoming necessary to incorporate contingency constraints into the formulation, and more rapid updates of telemetered data and faster solution time are becoming important to better track changes in the system. This concern led to a research to develop an efficient algorithm for a distributed optimal power flow based on the Auxiliary Problem Principle and to study the convergence rate improvement of the distributed algorithm. The objective of this paper is to find a set of control parameters with which the Auxiliary Problem Principle (Algorithm - APP) can be best implemented in solving optimal power flow problems. We employed several IEEE Reliability Test Systems, and Korea Power System to demonstrate the alternative parameter sets.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.119-125
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• 2006

Distributed Systems can be defined as set of computing resources connected by computer network. One of the most significant techniques in optimization problem domains is parallel genetic algorithms, which are based on distributed systems. Since the status of dynamic network environments such as Internet and mobile computing. can be changed continually, it must not be efficient on the dynamic environments to solve an optimization problem using previous parallel genetic algorithms themselves. In this paper, we propose the effective technique, in which the parallel genetic algorithm can be used efficiently on the dynamic network environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2454-2468
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• 2019

The existing direct position determinations(DPD) for coherently distributed(CD) sources are mostly applicable for uniform linear array(ULA), which result in a low degree of freedom(DOF), and it is difficult for them to realize the effective positioning in underdetermined condition. In this paper, a novel DPD algorithm for coherently distributed sources based on compressed sensing with a moving nested array is present. In this algorithm, the nested array is introduced to DPD firstly, and a positioning model of signal moving station based on nested array is constructed. Owing to the features of coherently distributed sources, the cost function of compressed sensing is established based on vectorization. For the sake of convenience, unconstrained transformation and convex transformation of cost functions are carried out. Finally, the position coordinates of the distribution source signals are obtained according to the theory of optimization. At the same time, the complexity is analyzed, and the simulation results show that, in comparison with two-step positioning algorithms and subspace-based algorithms, the proposed algorithm effectively solves the positioning problem in underdetermined condition with the same physical element number.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.90-95
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• 2022

This paper proposes a method to find a tree with the maximum number of terminals that can be connected by a given length when numerous terminals distributed in a cluster form are given to the Euclidean plane R2 with several constraints. First constraint is that a given terminal is distributed in a cluster form, second is that a given length cannot connect all terminals in the tree, and third is that there is no curved connection between each terminal. This paper proposes a method to establish more efficient interconnections within terminals distributed in a cluster form by improving a randomly distributed memetic genetic algorithm. The construction of interconnections has been extensively used in design-related fields, from networking to architecture. Additionally, in real life, the construction of interconnections is mostly distributed in the form of clusters. Therefore, the heuristic algorithm proposed in this paper can be effectively utilized in real life and is expected to provide various cost savings.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.553-561
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• 2004

Leader election is an important problem in developing fault-tolerant distributed systems. As a classic solution for leader election, there is Garcia-Molina's Bully Algorithm based on time-outs in synchronous systems. In this paper, we re-write the Bully Algorithm to use a failure detector instead of explicit time-outs. We show that this algorithm is more efficient than the Garcia-Molina's one in terms of the processing time. That is because the Bully_FD uses FD to know whether the process is up or down so fast and it speed up its execution time. Especially, where many processes are connected in the system and crash and recovery of processes are frequent, the Bully_FD algorithm is much more efficient than the classical Bully algorithm in terms of the processing time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.73-78
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• 2019

This paper proposes polynomial-time rule for maximum weighted independent set(MWIS) problem that is well known NP-hard. The well known distributed algorithm selects the maximum weighted node as a element of independent set in a local. But the merged independent nodes with less weighted nodes have more weights than maximum weighted node are frequently occur. In this case, existing algorithm fails to get the optimal solution. To deal with these problems, this paper constructs maximum weighted independent set in local area. Application result of proposed algorithm to various networks, this algorithm can be get the optimal solution that fail to existing algorithm.