Adaptive Computing on the Grid Using AppLeS

Authors:
Francine Berman;Richard Wolski;Henri Casanova;Walfredo Cirne;Holly Dail;Marcio Faerman;Silvia Figueira;Jim Hayes;Graziano Obertelli;Jennifer Schopf;Gary Shao;Shava Smallen;Neil Spring;Alan Su;Dmitrii Zagorodnov
Affiliations:
-;-;-;-;-;-;-;-;-;-;-;-;-;-;-
Venue:
IEEE Transactions on Parallel and Distributed Systems
Year:
2003

Citing 56
Cited 118

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Abstract

Ensembles of distributed, heterogeneous resources, also known as Computational Grids, have emerged as critical platforms for high-performance and resource-intensive applications. Such platforms provide the potential for applications to aggregate enormous bandwidth, computational power, memory, secondary storage, and other resources during a single execution. However, achieving this performance potential in dynamic, heterogeneous environments is challenging. Recent experience with distributed applications indicates that adaptivity is fundamental to achieving application performance in dynamic grid environments. The AppLeS (Application Level Scheduling) project provides a methodology, application software, and software environments for adaptively scheduling and deploying applications in heterogeneous, multiuser grid environments. In this article, we discuss the AppLeS project and outline our findings.