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<p><b>Abstract</b>—Ensembles of distributed, heterogeneous resources, also known as <it>Computational Grids</it>, 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 <it>AppLeS</it> (<b>App</b>lication <b>Le</b>vel <b>S</b>cheduling) 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.</p>
Scheduling, parallel and distributed computing, heterogeneous computing, grid computing.
Richard Wolski, Francine Berman, Walfredo Cirne, Shava Smallen, Jennifer Schopf, Neil Spring, Jim Hayes, Marcio Faerman, Holly Dail, Dmitrii Zagorodnov, Alan Su, Silvia Figueira, Gary Shao, Henri Casanova, Graziano Obertelli, "Adaptive Computing on the Grid Using AppLeS", IEEE Transactions on Parallel & Distributed Systems, vol. 14, no. , pp. 369-382, April 2003, doi:10.1109/TPDS.2003.1195409
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