Dynamic resource allocation for database servers

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The proposed project will investigate autonomic system adaptations to reduce the need for human-directed management of large-scale Internet server systems. Autonomic systems monitor and dynamically adapt their behavior to meet preset goals or behavioral requirements. Large-scale cluster systems are often present in organizations that provide dynamic content services such as e-commerce, on-line banking, stock trading and gaming. Such services generate content on-the-fly based on persistent state stored in databases. Database systems have traditionally been used to run a single application at a given time on a stand-alone database engine. Typically, in this configuration, an expert administrator could determine the optimal database settings for that application. This is not the case with large data centers, where multiple applications, such as, e-commerce, auctions and news, are commonly hosted concurrently on the same hardware, in order to reduce costs. The diverse nature of applications that may share the same infrastructure makes configuration and performance tuning difficult and time consuming. Furthermore, the increasing size of the large-scale cluster systems serving dynamic content makes them prone to failures. Recovering from failures, as well as activities aimed at reducing the probability of failures, such as, system backup take up a significant portion of personnel time and introduce the potential for human operator errors.We propose to develop autonomic database system mechanisms that will continually monitor and optimize performance and will automate failure recovery in dynamic content servers, thus, reducing or eliminating the human effort currently required. Specifically, we will investigate dynamic allocation of resources to applications in response to either performance bottlenecks or faults at the level of: i) database server nodes and ii) resources inside a database server node. Our proposed work is expected to lower the total cost of system management, while at the same time provide improved quality of service, thus benefit information technology companies and their customers.