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Incentive-Based Scheduling for Green Computational Grid
Abstract
In the computing grid environment, jobs scheduling is fundamentally the process of allocating computing jobs with choices relevant to the available resources. As the scale of grid computing system grows in size over time, exponential increase in energy consumption is foreseen. As such, large data centers (DC) are embarking on green computing initiatives to address the IT operations impact on the environment. The main component within a computing system consuming the most electricity and generating the most heat is the microprocessor. The heat generated by these high-performance microprocessors is emitting high CO2 footprint. Therefore, jobs scheduling with thermal considerations (thermal-aware) to the microprocessors is important in DC grid operations. An approach for jobs scheduling is proposed in this chapter for reducing electricity usage (green computing) in DC grid. This approach is the outcome of the R&D works based on the DC grid environment in Universiti Teknologi PETRONAS, Malaysia.
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