Autonomic database management systems
Autonomic database management systems
批准号:
262150-2006
负责人:
Benoit, Darcy
金额:
$0.84万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2008
资助国家:
加拿大
项目状态:
已结题
起止时间:
2008-01-01 至 2009-12-31
中文摘要
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英文摘要
Autonomic computing is an approach to self-managed computing systems with a minimum of human interference. Autonomic systems are intended to perform with little human interaction by configuring themselves when installed (or when new hardware is added), manage their own resources for peak performance, heal themselves when software breaks (or detect broken hardware and ask for repairs) and protect themselves from both internal failures and outside attacks. Automated diagnosis and resource management will result in better performance and lower operating costs. One area where the impact of autonomic computing is significant is that of embedded systems and applications. Embedded systems and applications usually have a limited amount of resources available for application to run, and as such, performance is based on the efficient and intelligent use of resources. Limited resources are further exacerbated by the lack of regular system interfaces in which resources can be adjusted. For typical embedded applications such as an address book stored in a telephone, it is not possible to adjust resources in order to improve the performance of the system. In such cases, the embedded application must be responsible for managing its own resources and achieving the best possible performance given the resources available. The application of autonomic principles to embedded applications and systems is necessary as we expect more functionality from resource-constrained devices. Autonomic computing has been especially popular in database management systems (DBMSs) in the past several years. As databases increase in size and complexity, the ability to control performance by hand becomes impractical. This problem is further intensified as DBMSs are embedded into everyday devices and expected to handle significant amounts of information and perform well. DBMS performance on these embedded applications becomes more apparent and data volume increases. Advancements in this area will be applicable to the DBMS, embedded systems and autonomic systems community.
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资助金额:$0.84万
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