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动态负载均衡策略及相关模型研究 被引量:13

Research on dynamic load balancing strategy and corresponding model
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摘要 为了提高分布式计算机环境中负载均衡的效率,提出一种基于启动者动态改变和阈值自适应的高效动态负载均衡策略。该策略根据分布式环境中各计算机的负载状态以及接受者启动策略和发送者启动策略的优缺点,动态改变负载阈值和启动者策略。研究了四个关键问题,即负载的分配、负载探测、负载状态的定义以及均衡策略,给出适合该策略的问题解决办法和结构模型。理论分析和实验结果表明,该策略能够有效地均衡负载,减小系统内部通信量,同时能够有效地抑制系统负载抖动。 In order to improve the efficiency of load balancing in distributed computer environment,a novel efficient load balancing strategy,which is based on initializer dynamic change and self-adaptive threshold,is proposed.In accordance to the load state of the computer in the distributed environment,and considering the advantage and disadvantage of the sender and receiver initiated diffusion strategies,the strategy alters dynamically the threshold and initializer strategy.The paper addresses four problems which contain load distribution,load detection,the definition of the load state and initializer strategy,and provides the solution of the problems and structural model.Theoretical analysis and experimental results show that the strategy can efficiently balance load,decrease interior communication flux and restrain system load threshing.
出处 《计算机工程与应用》 CSCD 北大核心 2011年第8期131-134,共4页 Computer Engineering and Applications
基金 工信部2008电子信息产业发展基金(No.97)~~
关键词 启动者策略 负载阈值 负载探测 负载抖动 initializer strategy load threshold load detection load threshing
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参考文献5

  • 1Legrand A.Mapping and load-balancing iterative computations[J], Parallel and Distributed Systems, 2004,6 (3) : 546-558.
  • 2Barker K.A load balancing framework for adaptive and asyn, chronous applications[J].ParaUel and Distributed Systems,2004,2 (1):183-192.
  • 3蒋翠清,杨善林,黄梯云,梁昌勇.基于Agent的动态负载均衡技术及仿真实现[J].微电子学与计算机,2005,22(10):47-50. 被引量:9
  • 4Willebeek-LeMair M H,Reeves A P.Strategies for dynamic load balancing on highly parallel computers[J].IEEE Transactions on Parallel and Distributed Systems, 1993,4 (9) : 979-993.
  • 5Zhang Xiayu, Yu Yongquan, Chen Baixing, et aLAn extension based dynamic load balancing model of heterogeneous server cluster[C]//Proceedings 2007 IEEE International Conference on Granular Computing, GRC, 2007: 675-679.

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