Parallel and Distributed Processing Symposium, International (2008)
Miami, Florida USA
Apr. 14, 2008 to Apr. 18, 2008
The use of many distributed, heterogeneous resources as a large collective platform offers great potential. A key issue for these grid platforms is middleware scalability and how middleware services can be mapped on the available resources. Optimizing deployment is a difficult problem with no existing general solutions. In this paper, we address the following problem: how to perform out an adapted deployment for a hierarchy of servers and resource brokers on a heterogeneous system? Our objective is to generate a best platform from the available nodes so as to fulfill the clients demands. However, finding the best deployment among heterogeneous resources is a hard problem since it is close to find the best broadcast tree in a general graph, which is known to be NP-complete. Thus, in this paper, we present a heuristic for middleware deployment on heterogeneous resources. We apply our heuristic to automatically deploy a distributed problem solving environment on a large scale grid. We present experiments comparing the automatically generated deployment against a number of other reasonable deployments.
Middleware, Problem-solving, Scalability, Throughput, Processor scheduling, File servers, Computer science, Educational institutions, Broadcasting, Tree graphs
"Automatic middleware deployment planning on heterogeneous platforms", Parallel and Distributed Processing Symposium, International, vol. 00, no. , pp. 1-13, 2008, doi:10.1109/IPDPS.2008.4536171