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    田俊峰, 刘玉玲, 杜瑞忠. 分布式数据库服务器系统及其自适应配置管理策略[J]. 计算机研究与发展, 2005, 42(1): 126-133.
    引用本文: 田俊峰, 刘玉玲, 杜瑞忠. 分布式数据库服务器系统及其自适应配置管理策略[J]. 计算机研究与发展, 2005, 42(1): 126-133.
    Tian Junfeng, Liu Yuling, Du Ruizhong. The Model and Adaptive Configuration Management Strategy for a Distributed Database Server System[J]. Journal of Computer Research and Development, 2005, 42(1): 126-133.
    Citation: Tian Junfeng, Liu Yuling, Du Ruizhong. The Model and Adaptive Configuration Management Strategy for a Distributed Database Server System[J]. Journal of Computer Research and Development, 2005, 42(1): 126-133.

    分布式数据库服务器系统及其自适应配置管理策略

    The Model and Adaptive Configuration Management Strategy for a Distributed Database Server System

    • 摘要: 服务器冗余技术在解决传统分布式环境的可用性和性能瓶颈问题的同时,给系统的管理带来了新的挑战.介绍了一种分布式数据库服务器DDSS的构成原理及工作模型.为了解决当前冗余服务系统的配置管理中存在的冗余资源动态可扩展性不强的问题,针对服务器DDSS(模型把系统中的每种服务抽象成为一个对象类,并提出同一个服务对象类的多个实例互为冗余服务),对冗余资源的配置管理问题进行讨论,并提出基于移动代理技术的自适应配置管理ACM(adaptive configuration management)策略,在保证系统可用性的前提下提高系统的性能,减少资源浪费.在ACM中,通过定义奖惩函数(对于静态配置)和用户请求到达率(对于动态配置)来作为配置依据,对冗余实例进行动态增加或删除.最后,对算法的性能进行了分析、测试,并与传统算法进行了比较.

       

      Abstract: Server redundancy technology solves the problem of availability and the performance bottleneck in the traditional distributed environment, and at the same time presents a new challenge to the system management. A kind of constituting principle and working model of a distributed database server system (DDSS) is presented in this paper. To overcome the weakness of dynamic scalability of redundancy resource in configuration management of the present redundancy server system, aiming at the server DDSS (every service in the system is abstracted to an object class in the model, and multi-instance of the same object class redundantly serving each other is proposed), the configuration management of redundancy resource is discussed, and adaptive configuration management policy based on mobile agent technology is proposed. With the precondition of ensuring the system availability, the system performance is improved and the resource waste is reduced. In ACM, by defining award-penalty function (as for static configuration) and user request arriving rate (as for dynamic configuration) which is the gist of configuration, redundancy instances is added or deleted dynamically. Finally, the algorithmic performance is analyzed and tested, and compared with traditional algorithm.

       

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