• Title/Summary/Keyword: Distributed algorithms

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Decombined Distributed Parallel VQ Codebook Generation Based on MapReduce (맵리듀스를 사용한 디컴바인드 분산 VQ 코드북 생성 방법)

  • Lee, Hyunjin
    • Journal of Digital Contents Society
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    • v.15 no.3
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    • pp.365-371
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    • 2014
  • In the era of big data, algorithms for the existing IT environment cannot accept on a distributed architecture such as hadoop. Thus, new distributed algorithms which apply a distributed framework such as MapReduce are needed. Lloyd's algorithm commonly used for vector quantization is developed using MapReduce recently. In this paper, we proposed a decombined distributed VQ codebook generation algorithm based on a distributed VQ codebook generation algorithm using MapReduce to get a result more fast. The result of applying the proposed algorithm to big data showed higher performance than the conventional method.

A Load Sharing Algorithm Including An Improved Response Time using Evolutionary Information in Distributed Systems

  • Lee, Seong-Hoon
    • International Journal of Contents
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    • v.4 no.2
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    • pp.13-18
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    • 2008
  • A load sharing algorithm is one of the important factors in computer system. In sender-initiated load sharing algorithms, when a distributed system becomes to heavy system load, it is difficult to find a suitable receiver because most processors have additional tasks to send. The sender continues to send unnecessary request messages for load transfer until a receiver is found while the system load is heavy. Because of these unnecessary request messages it results in inefficient communications, low cpu utilization, and low system throughput. To solve these problems, we propose a self-adjusting evolutionary algorithm for improved sender-initiated load sharing in distributed systems. This algorithm decreases response time and increases acceptance rate. Compared with the conventional sender-initiated load sharing algorithms, we show that the proposed algorithm performs better.

Development of the digital protection relay for protecting distributed generation (분산전원 보호용 디지털 보호계전기 개발)

  • Cho, Chul-Hee;Lee, Byeong-Ho;Oh, Eui-Seok;Ko, Chul-Jin;Kang, Sang-Hee
    • Proceedings of the KIEE Conference
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    • 2005.07a
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    • pp.181-183
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    • 2005
  • The existing distribution networks are growing with an increase of power demand more and more. Therefore, for efficient operation of distribution networks, operators are much in need of distributed generation. This paper describes a development of the digital protection relay(HIMAP) for protecting distributed generation which is expected to play an increasing role in electric power systems in the near future. This paper particularly introduces frequency protective algorithm and reverse power protective algorithm among the relaying algorithms for protecting distributed generation in distribution networks and resents capability of a developed digital protection relay including these algorithms.

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A GGQS-based hybrid algorithm for inter-cloud time-critical event dissemination

  • Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1259-1269
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    • 2012
  • Cloud computing has rapidly become a new infrastructure for organizations to reduce their capital cost in IT investment and to develop planetary-scale distributed applications. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a geographic group quorum system (GGQS)-based hybrid algorithm for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed algorithm first organizes these distributed clouds into a geographic group quorum overlay to support a constant event dissemination latency. Then it uses a hybrid protocol that combines geographic group-based broad-cast with quorum-based multicast. Our numerical results show that the GGQS-based hybrid algorithm improves the efficiency as compared with Chord-based, Plume an GQS-based algorithms.

Analysis of Distributed DDQ for QoS Router

  • Kim, Ki-Cheon
    • ETRI Journal
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    • v.28 no.1
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    • pp.31-44
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    • 2006
  • In a packet switching network, congestion is unavoidable and affects the quality of real-time traffic with such problems as delay and packet loss. Packet fair queuing (PFQ) algorithms are well-known solutions for quality-of-service (QoS) guarantee by packet scheduling. Our approach is different from previous algorithms in that it uses hardware time achieved by sampling a counter triggered by a periodic clock signal. This clock signal can be provided to all the modules of a routing system to get synchronization. In this architecture, a variant of the PFQ algorithm, called digitized delay queuing (DDQ), can be distributed on many line interface modules. We derive the delay bounds in a single processor system and in a distributed architecture. The definition of traffic contribution improves the simplicity of the mathematical models. The effect of different time between modules in a distributed architecture is the key idea for understanding the delay behavior of a routing system. The number of bins required for the DDQ algorithm is also derived to make the system configuration clear. The analytical models developed in this paper form the basis of improvement and application to a combined input and output queuing (CIOQ) router architecture for a higher speed QoS network.

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Behavior leaning and evolution of collective autonomous mobile robots using reinforcement learning and distributed genetic algorithms (강화학습과 분산유전알고리즘을 이용한 자율이동로봇군의 행동학습 및 진화)

  • 이동욱;심귀보
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.8
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    • pp.56-64
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    • 1997
  • In distributed autonomous robotic systems, each robot must behaves by itself according to the its states and environements, and if necessary, must cooperates with other orbots in order to carray out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new learning and evolution method based on reinforement learning having delayed reward ability and distributed genectic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforement learning having delayed reward is still useful even though when there is no immediate reward. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the perfodrmance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper, we verify the effectiveness of the proposed method by applying it to cooperative search problem.

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Design and Performance Analysis of Caching Algorithms for Distributed Non-uniform Objects (분산 이질형 객체 환경에서 캐슁 알고리즘의 설계 및 성능 분석)

  • Bahn, Hyo-Kyung;Noh, Sam-Hyeok;Min, Sang-Lyul;Koh, Kern
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.6
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    • pp.583-591
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    • 2000
  • Caching mechanisms have been studied extensively to buffer the speed gap of hierarchical storages in the context of cache memory, paging system, and buffer management system. As the wide-area distributed environments such as the WWW extend broadly, caching of remote objects becomes more and more important. In the wide-area distributed environments, the cost and the benefit of caching an object is not uniform due to the location of the object; which should be considered in the cache replacement algorithms. For online operation, the time complexity of the replacement algorithm should not be excessive. To date, most replacement algorithms for the wide-area distributed environments do not meet both the non-uniformity of objects and the time complexity constraint. This paper proposes a replacement algorithm which considers the non-uniformity of objects properly; it also allows for an efficient implementation. Trace-driven simulations show that proposed algorithm outperforms existing replacement algorithms.

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Support vector machines for big data analysis (빅 데이터 분석을 위한 지지벡터기계)

  • Choi, Hosik;Park, Hye Won;Park, Changyi
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.5
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    • pp.989-998
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    • 2013
  • We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

General Algorithms for Construction of Broadcast and Multicast Trees with Applications to Wireless Networks

  • Nguyen Gam D.
    • Journal of Communications and Networks
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    • v.7 no.3
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    • pp.263-277
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    • 2005
  • In this paper, we introduce algorithms for constructing broadcasting and multicasting trees. These algorithms are general because they may be used for tree cost functions that are of arbitrary form. Thus, essentially the same algorithmic procedures are used for different tree cost functions. We evaluate the effectiveness of the general algorithms by applying them to different cost functions that are often used to model wired and wireless net­works. Besides providing a unifying framework for dealing with many present and future tree-construction applications, these algorithms typically outperform some existing algorithms that are specifically designed for energy-aware wireless networks. These general algorithms perform well at the expense of higher computational complexity. They are centralized algorithms, requiring the full network information for tree construction. Thus, we also present variations of these general algorithms to yield other algorithms that have lower complexity and distributed implementation.

Fully Distributed Economic Dispatching Methods Based on Alternating Direction Multiplier Method

  • Yang, Linfeng;Zhang, Tingting;Chen, Guo;Zhang, Zhenrong;Luo, Jiangyao;Pan, Shanshan
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1778-1790
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    • 2018
  • Based on the requirements and characteristics of multi-zone autonomous decision-making in modern power system, fully distributed computing methods are needed to optimize the economic dispatch (ED) problem coordination of multi-regional power system on the basis of constructing decomposition and interaction mechanism. In this paper, four fully distributed methods based on alternating direction method of multipliers (ADMM) are used for solving the ED problem in distributed manner. By duplicating variables, the 2-block classical ADMM can be directly used to solve ED problem fully distributed. The second method is employing ADMM to solve the dual problem of ED in fully distributed manner. N-block methods based on ADMM including Alternating Direction Method with Gaussian back substitution (ADM_G) and Exchange ADMM (E_ADMM) are employed also. These two methods all can solve ED problem in distributed manner. However, the former one cannot be carried out in parallel. In this paper, four fully distributed methods solve the ED problem in distributed collaborative manner. And we also discussed the difference of four algorithms from the aspects of algorithm convergence, calculation speed and parameter change. Some simulation results are reported to test the performance of these distributed algorithms in serial and parallel.