Achieving self-managed deployment in a distributed environment
Issue title: Special Supplement Issue in Section A and B: Selected Papers from the ISCA International Conference on Software Engineering and Data Engineering, 2010
Affiliations: [a] Department of Computer Science, Winston-Salem State University, Winston-Salem, NC, USA | [b] Department of Computer Science, Montclair State University, Montclair, NJ, USA | Department of Computer Science, Winona State University, Winona, MN, USA
Abstract: This paper proposes algorithms and mechanisms for achieving self-optimized deployment of computationally intensive scientific and engineering applications in highly dynamic and large-scale distributed environment. The primary focus is on the modeling of the application and underlying architecture into a common abstraction and on the incorporations of autonomic features to those abstractions to achieve self-optimized deployment. To represent the underlying heterogeneous infrastructure, a hierarchical (tree) model of distributed resources has been adopted that organizes distributed nodes in a utility aware way. To accomplish the self-optimization, a utility-function has been formulated that governs both the initial deployment of an application and its dynamic reconfiguration. In our approach, the deployment decisions are made solely based on locally available information and without costly global communication or synchronization. The self-management is therefore decentralized to provide better adaptability, scalability and robustness.
Keywords: Automatic partitioning, autonomic computing, self-management, self-optimization, utility function
