GDP: A Paradigm for Intertask Communication in Grid Computing Through Distributed Pipes
Existing grid models target purely data parallel applications without inter-task communication. This paper proposes a transparent programming model to support communicating parallel tasks in a wide area grid. The proposed grid model with Distributed Pipes (DP) abstraction named as, GDP, enables location independent intertask communication among processes on machines spread over a wide area distributed system. This approach enables anonymous migration of communicating parallel tasks adjusting to grid dynamics. The proposed model supports sequential load to coexist with parallel load. A prototype of the proposed model has been implemented over clusters of nodes spread across the Internet. A steady state equilibrium engineering problem was studied over the model. Performance studies show linear to super linear speed up for the application.
KeywordsFault Tolerance Grid Environment Parallel Task User Process Tuple Space
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