通过在SGBDD上按需复制数据,实现集群负载均衡

Reinaldo Lourenso, S. Kofuji
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引用次数: 0

摘要

在过去几年中,已证实网络流量和处理负载的显著增长,主要是在数据库服务器上。造成这种增长的因素有很多,例如:对信息可用性需求的增长,以及存储信息的大小和数量的增加,这在多媒体应用中得到了验证。处理大量信息问题的一种解决方案是利用基于集群的服务器,与分布式数据库系统一起工作。这种类型的解决方案允许并行处理大量的信息。尽管事实上,由于高性能、低成本和高可伸缩性的特点,集群系统中的多处理被越来越多地使用,但我们证实,针对这些体系结构的特定数据库系统在数据复制和负载平衡方面存在一些限制。这项工作的主要目标是研究和实现一种机制,通过在分布式数据库管理系统(DDBMS)中复制请求最多的数据,在信息高需求时期实现更好的集群负载平衡。副本生成的整个过程是自治的,在空闲或负载较小的节点上动态分发副本。
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Balanceamento de Carga em Clusters por Replicação de Dados Sob Demanda em um SGBDD
In the last years, a significant growth of network traffic and processing load has been verified, mainly in database servers. Many factors have been responsible for this growth, such as: growth on demand for information availability, and increase of both size and quantity of stored information, as can be verified in multimedia application. One solution for the problem of processing large volume of information is the utilization of cluster based servers, working together with distributed database systems. This type of solution allows the parallel manipulation of great quantities of information. Although multiprocessing in clusters systems is, in fact, being used more and more due to high performance, low cost and high scalability characteristics, we verified that specific database systems for these architectures present some restrictions in relation to data replication, and load balance. The main objective of this work is the study and implementation of a mechanism that allows a better cluster load balance, in periods of high demand for information, by replicating the most requested data in a Distributed Database Management System (DDBMS). The complete process of copies generation is autonomous, with dynamic distribution of copies for the idle or less loaded node.
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Projeto Mercúrio - Interface de comunicação de Alta Velocidade Replicação de Dados em Servidores Paralelos de Comércio Eletrônico ReMMoS - Um Modelo de Replicação em Ambientes que Suportam Mobilidade de Objetos Avaliando Sistemas Operacionais para Máquinas de Alto Desempenho Algoritmos Genéticos para Escalonamento de Processadores
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