• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.250-252
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• 2005

본 논문에서는 분산 해쉬 테이블(Distributed Hash Table)을 이용하는 구조적 P2P(Peer-to-Peer) 시스템에서의 로드 밸런싱 문제를 다룬다. 이러한 환경에서 시스템은 여러 가지 이유로 각 피어들이 서로 다른 부하(load)를 갖는 상황을 맞이하게 된다. P2P 시스템에 오브젝트가 지속적으로 삽입되고 삭제되는 동적인 환경에서 오브젝트의 생존시간을 고려하여 피어가 갖는 로드의 변화를 예측함으로써 불필요한 로드의 이동을 제거하는 효율적인 로드 밸런싱 기법을 제안한다.

• Journal of Ocean Engineering and Technology
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• v.27 no.4
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• pp.83-89
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• 2013

A numerical scheme based on a mode superposition method is presented for the dynamic response analysis of a top-tensioned riser (TTR) under sheared current loads. The natural frequencies and mode shapes of the TTR have been calculated analytically for a beam with a slowly varying tension and pinned-pinned boundary conditions at the top and bottom ends. The lift coefficients and corresponding amplitudes used to estimate the vortex-induced modal force and damping for each mode were predicted via iterative calculations based on the input and output power balancing concept. Here, the power-in regions were controlled by the normal distribution function, for which the center was coincident with the lock -in location by local vortex-shedding, and the range was defined by the constant standard deviation for the reduced velocity by the local current speed. Finally, dynamic responses such as root-mean-squared displacement and stress were calculated using the mode superposition technique. In order to verify the presented scheme, a numerical calculation was performed for a TTR under an arbitrary linearly sheared current and linearly varying tension. A comparison with the results of the existing software showed that the presented scheme could give reliable and feasible solutions. Case studies were performed to investigate the effects of various current loads and tensions.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.133-146
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• 2001

In a dynamic load distribution policies, each node gathers the current system sates information before making a decision on load balancing. Load balancing policies based on this strategy can suffer from processor thrashing. In this paper, we propose a new algorithm which attempts to decrease the frequency of the processor thrashing, the algorithm is based on the integration of three components. The first, the algorithm of which determine the size of jobs be transferred. The second, negotiation protocol with obtains a mutual agreement between a sender and a receiver on the transferring job size. And the third, a symmetrically-initiated location policy. The algorithm proposed in this paper used Siman IV as simulation tool to prove the improvement of performance. I analyzed the result of simulation, and compared with related works. The mean response time shows that there are no difference with existing policy, but appear a outstanding improvement in high load. The thrashing coefficient that shows the average response time, CPU overhead and the thrashing ratio at both the receiving and sending node has been used in the analysis. A significant improvement in the average response time and the CPU overhead ratio was detected using our algorithm when an overhead occurred in the system over other algorithm. The thrashing coefficient differed in the sending node and the receiving node of the system. Using our algorithm, the thrashing coefficient at the sending node showed more improvement when there was an overhead in the system, proving to be more useful. Therefore, it can be concluded that the thrashing ratio can be reduce by properly setting the maximum and minimum value of the system’s threshold queue.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.535-544
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• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.361-363
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• 2002

부하 분산 시스템의 성능을 향상시키기 위해서는 각 연산 노드들에 대한 부하수준을 잘 파악하여야 한다. 기존의 부하 분산 시스템들은 부하 측정기준(load metric)으로 실행 큐(run queue)에 있는 작업의 수(number of jobs)를 주로 이용한다. 그러나, 여러 프로세스들이 동시에 실행될 때, 각 프로세스의 실행이 서로의 성능에 미치는 정도인 프로세스간 독립수준(interprocess dependence level)을 고려하면 좀 더 정확하게 시스템 부하수준을 측정할 수 있다. 본 연구에서는 시스템 성능에 실제로 영향을 미치는 프로세스들의 수를 의미하는 유효 작업의 수(effective number of jobs)라는 부하 측정기준을 적용하여 성능이 향상된 부하 분산 시스템을 설계하고 구현하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4293-4304
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• 2014

In order to ensure the wireless connectivity and seamless service to mobile users, the next generation network system will be an integration of multiple wireless access networks. In a heterogeneous wireless access system, bandwidth allocation becomes crucial for load balancing to avoid network congestion and improve system utilization efficiency. In this article, we propose a new dynamic bandwidth allocation scheme for hierarchical wireless network systems. First, we derive a multi-objective decision criterion for each access point. Second, a bargaining strategy selection algorithm is developed for the dynamic bandwidth re-allocation. Based on the intervenient Stackelberg game model, the proposed scheme effectively formulates the competitive interaction situation between several access points. The system performance of proposed scheme is evaluated by using extensive simulations. With a simulation study, it is confirmed that the proposed scheme can achieve better performance than other existing schemes under widely diverse network environments.

• ETRI Journal
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• v.40 no.5
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• pp.604-612
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• 2018

To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node-selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy-adjustment factor are introduced to optimize the node-selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node-selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data-receiving rate in sufficient time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2294-2314
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• 2011

The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

• Journal of Communications and Networks
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• v.6 no.3
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• pp.216-225
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• 2004

In a cellular network, if there are too many data users in a cell, data may suffer long delay, and system's quality-of-service (QoS) will degrade. Some traditional schemes such as dynamic channel-allocation scheme (DCA) will assign more channels to hot (or overloaded) cells through a central control system (CC) and the throughput increase will be upper bounded by the number of new channels assigned to the cell. In mobile-assisted data forwarding (MADF), we add an ad-hoc overlay to the fixed cellular infrastructure and special channels-called forwarding channels- are used to connect mobile units in a hot cell and its surrounding cold cells without going through the hot cell's base station. Thus, mobile units in a hot cell can forward data to other cold cells to achieve load balancing. Most of the forwarding-channel management work in MADF is done by mobile units themselves in order to relieve the load from the CC. The traffic increase in a certain cell will not be upper bounded by the number of forwarding channels. It can be more if the users in hot cell are significantly far away from one another and these users can use the same forwarding channels to forward data to different cold neighboring cells without interference. We find that, in a system using MADF, under a certain delay requirement, the throughput in a certain cell or for the whole net-work can be greatly improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.181-188
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• 2016

This paper demonstrates that centralized economic load dispatch optimization is much more economical than independent optimization carried out by individual power generating companies. The algorithm applied here optimizes by balancing the generation power at the valve-point, then readjusting generation power by comparing incremental operating cost incurred by marginal increase in the generation power and decremental operating cost likewise incurred by marginal decrease in the generation power. Upon comparing 3 individual optimization cases of 10, 13, and 40 generators respectively with centralized optimization of 63 generators, centralized operation for economic load dispatch optimization has proven to maximize economic benefits by markedly reducing operation costs of individual optimization.