• Journal of Communications and Networks
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• 제10권1호
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.466-471
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• 2014

An asynchronous optical packet-switching (AOPS) node with load-balancing capability can achieve better performance in reducing the high packet-loss ratio (PLR) and time delay caused by unbalanced traffic. This paper proposes a novel dynamic load-balancing algorithm for an AOPS node with limited buffer and without wavelength converters, and considering the data flow distribution and service levels. By calculating the occupancy state of the output ports, load state of the input ports, and priorities for data flow, the traffic is balanced accordingly. Simulations demonstrate that asynchronous variant data packets and output traffic can be automatically balanced according to service levels and the data flow distribution. A PLR of less than 0.01% can be achieved, as well as an average time delay of less than 0.46 ns.

• ETRI Journal
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• 제45권3호
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• pp.433-447
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• 2023

Critical issues such as connection congestion, long transmission delay, and packet loss become even worse during epidemic, disaster, and so on. In this study, a link load balancing method is proposed to address these issues on the data plane, a plane of the software-defined network (SDN) architecture. These problems are NP-complete, so a meta-heuristic approach, discrete particle swarm optimization, is used with a novel hybrid cost function. The superiority of the proposed method over existing methods in the literature is that it provides link and switch load balancing simultaneously. The goal is to choose a path that minimizes the connection load between the source and destination in multipath SDNs. Furthermore, the proposed work is dynamic, so selected paths are regularly updated. Simulation results prove that with the proposed method, streams reach the target with minimum time, no loss, low power consumption, and low memory usage.

• 한국정보과학회논문지:시스템및이론
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• 제28권11호
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• pp.549-560
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• 2001

클러스터 시스템을 계산능력과 메모리 크기에 있어서 바람직한 확장성을 제공한다. 또한 고속의 컴퓨터 네트워크 기술의 발달로 인해 클러스터 시스템은 값비싼 MPPs (Massively Parallel Processors)와 비교하여 경쟁력을 얻고 있다. 부적당한 작업 스케줄링은 시스템의 기능을 충분히 이용할수 없고, 병렬처리 프로그램에서 프로그램 실행 전에 각 태스크의 부하를 예측하기 어려우며, 태스크들은 다양한 형태로 서로 의존적이다. 동적 부하균등 알고리즘에서는 실행시간에 각 프로세서의 부하를 평가한 후, 각 태스크를 적절한 크기로 분할하고 그것들을 각 프로세서의 수행능력에 비례하여 클러스터 시스템에 할당한다. 그러나, 프로세싱 노드간의 통신비용이 높으면, 모든 노드들이 부하분산에 참여하는 것은 효율적이지 못하다. 본 논문에서는 부하분산에 참여하는 프로세서를 통신비용과 평균 부하로부터의 편차를 고려하여 제한하였다. 기존의 부하균등 방식과 제안된 동적 알고리즘을 비교하기 위하여, 통신비용, 노드 수, 그리고 부하의 범위와 같은 파라메터를 사용하여 다양한 모델의 클러스터 시스템에 관한 시뮬레이션을 수행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.303-305
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• 2005

In MMORPG, gamers can engage in a variety of activities with other players from all over the world. So, this kind of games has unprecedented heavy load. There are so many kind of method to balance the load of MMORPG. But. many of them are not adaptable to dynamic load variation. In this paper, we propose a dynamic map-partition method based on VML. By use of dynamic map-partition based on VML, we can easily adapt to dynamic load variation. And by changing VML. we can manage field servers within game system.

• ETRI Journal
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• 제35권3호
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• pp.414-424
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• 2013

We consider a new load balancing routing for delay-guaranteed services in the network in which the traffic is dynamic and network topologies frequently change. For such an ever-changing network, we propose a new online load balancing routing called AntLBR, which exploits the ant colony optimization method. Generally, to achieve load balancing, researchers have tried to calculate the traffic split ratio by solving a complicated linear programming (LP) problem under the static network environment. In contrast, the proposed AntLBR does not make any attempt to solve this complicated LP problem. So as to achieve load balancing, AntLBR simply forwards incoming flows by referring to the amount of pheromone trails. Simulation results indicate that the AntLBR algorithm achieves a more load-balanced network under the changing network environment than techniques used in previous research while guaranteeing the requirements of delay-guaranteed services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3394-3408
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• 2014

Conventional mobile state (MS) and base station (BS) association based on average signal strength often results in imbalance of cell load which may require more powerful processor at BSs and degrades the perceived transmission rate of MSs. To deal with this problem, a Markov decision process (MDP) for load balancing in a multi-cell system with multi-carriers is formulated. To solve the problem, exploiting Sarsa algorithm of on-line learning type [12], ${\alpha}$-controllable load balancing algorithm is proposed. It is designed to control tradeoff between the cell load deviation of BSs and the perceived transmission rates of MSs. We also propose an ${\varepsilon}$-differential soft greedy policy for on-line learning which is proven to be asymptotically convergent to the optimal greedy policy under some condition. Simulation results verify that the ${\alpha}$-controllable load balancing algorithm controls the behavior of the algorithm depending on the choice of ${\alpha}$. It is shown to be very efficient in balancing cell loads of BSs with low ${\alpha}$.

• 한국정보과학회논문지:시스템및이론
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• 제33권3호
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• pp.193-204
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• 2006

대부분의 분산 웹 시스템은 Domain Name System(DNS)을 이용하여 사용자 요청을 분산한다. DNS 기반 부하분산 시스템은 구성하기 쉬운 장점이 있지만, 주소 캐싱 매커니즘에 의해 서버들 사이의 부하 불균형이 발생한다. 또한, 서버의 상태를 파악하기 위해서 DNS의 수정이 필요하다. 본 논문에서는 DNS의 동적 갱신(dynamic update)과 라운드로빈 방법을 이용한 새로운 부하분산 기법을 제안한다. 본 논문에서 제안하는 방법은 DNS의 수정 없이 동적인 부하분산을 한다. 본 논문에서 제안하는 시스템은 서버의 부하량에 따라 서버를 DNS 리스트에 동적으로 추가, 삭제한다. 부하가 많은 서버를 DNS 리스트에서 제거함으로써 사용자 응답시간이 빠르다. 동적인 부하분산을 위하여 CPU와 메토리 네트워크 자원의 사용률에 따른 부하분산 알고리즘을 제안한다. GUI 기반의 관리도구를 이용하여 손쉽게 제안하는 시스템을 관리할 수 있다. 실험을 통하여 본 논문에서 구현한 모듈들이 제안된 시스템의 성능에 많은 영향을 주지 않는다는 것을 보여준다. 또한 기존 라운드로빈 DNS와의 비교실험을 통하여 사용자 응답시간과 파일전송률이 더 빠르다는 것을 보여준다.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1645-1654
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• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.