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Energy Efficient Scheduling Methods for Computational Grids and Clouds

Jakóbik A., Grzonka D., Kołodziej J., Chis A. E., González-Vélez H.

Journal of Telecommunications and Information Technology

2017

nr 1

56--64

This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage proles are presented together with energy efficiency measuring methods. Modeling of computing dynamics is discussed from the viewpoint of system identication theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach.

Performance evaluation of MapReduce using full virtualisation on a departmental cloud

González-Vélez H., Kontagora M.

International Journal of Applied Mathematics and Computer Science

2011

Vol. 21, no 2

275-284

This work analyses the performance of Hadoop, an implementation of the MapReduce programming model for distributed parallel computing, executing on a virtualisation environment comprised of 1+16 nodes running the VMWare workstation software. A set of experiments using the standard Hadoop benchmarks has been designed in order to determine whether or not significant reductions in the execution time of computations are experienced when using Hadoop on this virtualisation platform on a departmental cloud. Our findings indicate that a significant decrease in computing times is observed under these conditions. They also highlight how overheads and virtualisation in a distributed environment hinder the possibility of achieving the maximum (peak) performance.