GreenHadoop

TLDR

Renewable energy sources such as solar and wind are increasingly considered for powering datacenters, but their intermittent availability requires careful matching of energy demand and supply to reduce reliance on carbon‑intensive grid power. The study aims to develop a method for managing a datacenter’s computational workload so that it aligns with the fluctuating supply of green energy. GreenHadoop is a MapReduce framework that forecasts near‑term solar output, schedules jobs within their time bounds to maximize green usage, and when brown power is unavoidable, selects low‑cost periods while controlling peak consumption. Experimental results show that GreenHadoop substantially raises green energy utilization and lowers overall electricity costs compared to standard Hadoop.

Abstract

Interest has been growing in powering datacenters (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 datacenter's computational workload to match the green energy supply. In particular, we consider data-processing frameworks, in which many background computations can be delayed by a bounded amount of time. We propose GreenHadoop, a MapReduce framework for a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenHadoop 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, GreenHadoop selects times when brown energy is cheap, while also managing the cost of peak brown power consumption. Our experimental results demonstrate that GreenHadoop can significantly increase green energy consumption and decrease electricity cost, compared to Hadoop.