CSR: Medium: Collaborative Research: GridPac: A Resource Management System for Energy and Performance Optimization on Computational Grids

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Massive energy consumption is an escalating threat to the environment. Large-scale computational grids consume a substantial amount of energy, and their energy requirements for powering and cooling are becoming comparable to the costs of acquisition. There is a lack of generally applicable methods for reducing energy consumption while ensuring good quality of service. This project will develop GridPac (Grid with Power-Aware Computing), a middleware environment that will allow grid managers and service providers to schedule multiple workflows across a distributed grid for system-wide optimization. GridPac will be based on a novel framework to support a variety of task-level workflows. The main features of this work are to develop: (a) Novel static and dynamic algorithms for scheduling single and multiple workflows, which can be flexibly utilized by service providers in scalable grid environments. (b) Control algorithms to account for dynamic adjustment of schedules using energy monitoring of the grid resources. (c) Extensive benchmarking using a suite of commonly used grid workflows. (d) A prototype middleware to assist IT organizations to better support their users while reducing energy costs. The proposed work will lead to original scholarly contributions while harnessing the usage of computational grids. The project carries tremendous potential for economic, environmental, and societal impact. We will initiate new graduate and undergraduate level courses on related topics, and develop relevant tutorials, which will help to create awareness and educate a large audience on a critically important research topic.