In the past decade there has been a remarkable change from mainframe computing to a distributed client/server approach. In the coming decade this trend is likely to continue with further shifts towards network centric computing. The main cause for such trend is mass production of cheap, fast and reliable microprocessors. A network of workstations is becoming a common sight in modern computing environments. Each workstation provides powerful computing resources which are periodically in strong demand by the local user. However even in busy environment, a significant proportion of these machines will be idle or underutilized at any time. By supplementing the local computing resources through offloading tasks to idle nodes, better utilization can be
The database field has developed very powerful technologies for finding efficient execution plans for declaratively specified queries. Moreover, database queries have increasingly complex in the age of the distributed DBMS (DDBMS). In order to optimize queries accurately, sufficient information must be available to determine which data access techniques are most effective. The role of query optimization is to find a strategy close to optimal. To optimize the query efficiently, it is important to choose the site to execute. For site selection, the statistical information of underlining relations is essential. In this paper, we propose the query optimization model based on mobile agents. This model provides a strategy for executing each query over the network in the most cost-effective way. Our proposed system focuses on these modules: Query Decomposition: decomposes the input query into mono-relation query using the detachment techniques, Optimization Plan: computes all possible plans using statistical database information and intermediate relation size by cooperating with mobile agents and chooses the optimized plan and Execution Plan: executes the optimized plan by using mobile agent and send results to client.
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