基于Web Service的分布式系统中动态负载均衡策略的研究与实现
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摘要
目前,分布式系统及其分布式计算技术是计算机领域的热点问题。在对分布式系统的研究中人们注意到,在某一时刻,一些计算机系统的负载很轻,而另外一些计算机系统的负载却很重,整个系统的效率并不高,所以,采用有效的负载均衡策略就成为了提高分布式系统性能的主要手段。虽然负载均衡问题至今已有20多年的研究历史,但由于负载均衡是NP完全问题,因此,目前还没有一种有效的负载均衡策略能够适用于所有的环境,负载均衡问题还有待于进一步的研究。负载均衡可分为静态负载均衡和动态负载均衡两类。实验表明,通常情况下动态负载均衡比静态负载均衡的性能效果有30%~40%的提高,因此本文研究的是动态负载均衡策略,具体的研究内容如下:
     首先,根据实际需求,设计了一个基于Web Service的分布式决策支持系统。为了解决以往C/S、B/S结构的诸多问题,本文采用了B/S与Web服务相结合的整体结构,并采用Web Service技术实现信息的传递,实现了异构平台间跨越防火墙的互操作功能,同时也增强了系统的可扩展性。
     其次,基于提出的决策支持系统,结合已有的动态负载均衡策略,设计了一个适用于该系统的改进的动态负载均衡策略。该策略采用的是全局的、集中式的、周期性的启动策略,设置了一个管理者周期性的收集系统内各节点的状态信息,并能够根据系统状态的变化,决定由谁来触发负载分配,这样使得该策略在任何状态下都能保证合理的负载均衡活动。
     最后,实现设计的系统及动态负载均衡策略,并通过对实验结果进行分析,验证该策略的稳定性和有效性。
Currently, distributed system and distributed computing technology is a hot issue of the computer field. In many studies of distributed system it was noted that, at some point, the load of some computer systems is very light, while the load of others is very heavy, the efficiency of whole system is not high, therefore, effective load balancing strategy has become the primary way to improve the performance of distributed system. Load balancing has been researched for 20 years, but because it is a NP problem, there is no an effective load balancing strategy can be applied to all environments, this problem needs to be further studied. Load balancing can be divided into static load balancing and dynamic load balancing. Studies have shown that compared with static load balancing, the performance of dynamic load balancing can usually increase 30% to 40%, therefore, dynamic load balancing strategy is the focus of the paper, the specific contents are as follows:
     Firstly, according to the actual needs, a distributed decision support system based on Web Service is designed. In order to solve previous problems in C/S and B/S structure, B/S and Web service are applied to design the structure of this system, and Web Service technology is adopted to transfer the information and achieve interoperability functions across the firewall in heterogeneous platforms, the scalability of the system is also enhanced.
     Secondly, combined with existing dynamic load balancing strategy, it proposes an improved dynamic load balancing strategy based on this system. The strategy adopts an overall, central controlled, periodic start strategy, and sets up a manager to collect the status information of all nodes in this system periodically, and according to the change of system state, it decides that who is going to trigger the load distribution, so this strategy can ensure a reasonable load balancing activity in any condition.
     Finally, the system and the dynamic load balancing strategy have been implemented, and the experimental results are analyzed in order to verify the stability and effectiveness of the strategy.
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