• MUPPIDI. VAMSI PRABHAS
• Dr. M. SAMPATH KUMAR

Interest has been growing in powering datacentres (at least partially) with renewable or “green” sources of energy, such as solar or wind. However, it is challenging to use these sources because, unlike the “brown” (carbon-intensive) energy drawn from the electrical grid, they are not always available. This means that energy demand and supply must be matched, if we are to take full advantage of the green energy to minimize brown energy consumption. In this paper, we investigate how to manage a datacentre’s computational workload to match the green energy supply. In particular, we consider data-processing frameworks, in which many back-ground computations can be delayed by a bounded amount of time. We propose Green-Aware, a MapReduce frame-work for a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). Green-Aware predicts the amount of solar energy that will be available in the near future, and schedules the MapReduce jobs to maximize the green energy consumption within the jobs’ time bounds. If brown energy must be used to avoid time bound violations, Green-Aware selects times when brown energy is cheap, while also managing the cost of peak brown power consumption. Our experimental results demonstrate that Green-Hadoop can significantly increase green energy consumption and decrease electricity cost, compared to Hadoop

Green energy; renewable energy; MapReduce; energy-aware scheduling; cost-aware scheduling

"LEVERAGING COST-EFFECTIVE AND GREEN-AWARE DATA PROCESSING FRAMEWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.797-804, June 2019, Available :http://www.jetir.org/papers/JETIR1907419.pdf

"LEVERAGING COST-EFFECTIVE AND GREEN-AWARE DATA PROCESSING FRAMEWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp797-804, June 2019, Available at : http://www.jetir.org/papers/JETIR1907419.pdf