Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Dynamic resource brokering for multi-user query execution
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Economic models for allocating resources in computer systems
Market-based control
The Vision of Autonomic Computing
Computer
Towards Automated Performance Tuning for Complex Workloads
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Supporting capacity planning for DB2 UDB
CASCON '02 Proceedings of the 2002 conference of the Centre for Advanced Studies on Collaborative research
Utility Functions in Autonomic Systems
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Achieving Class-Based QoS for Transactional Workloads
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Workload Class Importance Policy in Autonomic Database Management Systems
POLICY '06 Proceedings of the Seventh IEEE International Workshop on Policies for Distributed Systems and Networks
Workload adaptation in autonomic DBMSs
CASCON '06 Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative research
Performance management for cluster-based web services
IEEE Journal on Selected Areas in Communications
The use of economic models to capture importance policy for autonomic database management systems
Proceedings of the 1st ACM/IEEE workshop on Autonomic computing in economics
Optimizing queries to remote resources
Journal of Intelligent Information Systems
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Resource allocation in database management systems is a performance management process in which an autonomic DBMS makes resource allocation decisions based on properties like workload business importance. We propose the use of economic models to guide the resource allocation decisions. An economic model is described in terms of business concepts and has been successfully applied in computer system resource allocation problems. In this paper, we present an approach that uses economic models to allocate multiple resources, such as main memory buffer space and CPU shares, to workloads running concurrently on a DBMS. The economic model enables workloads to meet their service level objectives by allocating resources through partitioning the individual DBMS resources and making system-level resource allocation plans for the workloads. The resource allocation plans can be dynamically changed to respond to changes in workload performance requirements. Experiments are conducted on IBM® DB2® databases to verify the effectiveness of our approach.