NDLI: Optimal resource-aware deployment planning for component-based distributed applications

Content Provider	IEEE Xplore Digital Library
Author	Kichkaylo, T. Karamcheti, V.
Copyright Year	2004
Description	Author affiliation: New York Univ., NY, USA (Kichkaylo, T.; Karamcheti, V.)
Abstract	Component-based approaches are becoming increasingly popular in the areas of adaptive distributed systems, Web services, and grid computing. In each case, the underlying infrastructure needs to address a deployment problem involving the placement of application components onto computational, data, and network resources across a wide-area environment subject to a variety of qualitative and quantitative constraints. In general, the deployment needs to also introduce auxiliary components (e.g., to compress/decompress data, or invoke GridFTP sessions to make data available at a remote site), and reuse preexisting components and data. To provide the flexibility required in the latter case, recently proposed systems such as Sekitei and Pegasus have proposed solutions that rely upon Al planning-based techniques. Although promising, the inherent complexity of Al planning and the fact that constraints governing component deployment often involve nonlinear and nonreversible functions have prevented such solutions from generating deployments in resource-constrained situations and achieving optimality in terms of overall resource usage or other cost metrics. We address both of these shortcomings in the context of the Sekitei system. Our extension relies upon information supplied by a domain expert, which classifies component behavior into a discrete set of levels. This discretization, often justified in practice, permits the planner to identify cost-optimal plans (whose quality improves with the level definitions) without restricting the form of the constraint functions. We describe the modified Sekitei algorithm, and characterize, using a media stream delivery application, its scaling behavior when generating optimal deployments for various network configurations.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Distributed Comput
Starting Page	150
Ending Page	159
File Size	708327
Page Count	10
File Format	PDF
ISBN	0769521754
ISSN	10828907
DOI	10.1109/HPDC.2004.1323517
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Web services Grid computing Couplings Adaptive systems Artificial intelligence Costs Mesh generation Writing Terminology Computer networks
Content Type	Text
Resource Type	Article

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