The Vision of Autonomic Computing
Computer
Condor-G: A Computation Management Agent for Multi-Institutional Grids
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
The Autonomic Computing Paradigm
Cluster Computing
Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement
Computing and Visualization in Science
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
Scientific Programming
Enabling Self-Managing Applications using Model-based Online Control Strategies
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Experiments with in-transit processing for data intensive grid workflows
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
A Self-Managing Wide-Area Data Streaming Service using Model-based Online Control
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Issues and scenarios for self-managing grid middleware
Proceedings of the 2nd workshop on Grids meets autonomic computing
Discovering Piecewise Linear Models of Grid Workload
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Exploring application and infrastructure adaptation on hybrid grid-cloud infrastructure
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Self-adaptive architectures for autonomic computational science
SOAR'09 Proceedings of the First international conference on Self-organizing architectures
Towards Non-Stationary Grid Models
Journal of Grid Computing
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Emerging Grid infrastructures present unprecedented opportunities for computational science and engineering, with the potential for fundamental insights into complex phenomenon. However, it also presents unprecedented challenges in terms of its scale, heterogeneity, dynamism and overall complexity that must be addressed before this potential can be realized. Autonomic computing concepts have been effectively used to address similar challenges in enterprise systems and applications; in this paper, we explore the role of autonomic computing to Grid-based computational science applications. Specifically, we use three representative computational applications to motivate Autonomic Computational Science (ACS). Using these applications, we develop a conceptual framework for ACS, consisting of mechanisms, strategies and objectives, and demonstrate how these concepts can be used to express autonomic behaviors. Finally we explore a research agenda towards realizing ACS behaviors and developing self-* patterns for large scale autonomic computational science application.