Paper Info
Title
Performance Evaluation of Energy-Aware Best Fit Decreasing Algorithms for Cloud Environments.
Abstract
Cloud computing is emerging computational paradigm that provide resources to perform complex tasks. Large datacenters are used to facilitate the incoming tasks by providing resources, such as CPU, memory, storage, and network bandwidth. Datacenters offers hosting and processing of complex tasks and services, where servers and cooling systems consume huge amount of energy. Excessive amount of energy consumption results in large power bills and Green House gases (GHG) emissions. Substantial amount of energy can be saved by powering down servers that are idle. Various authors have come up with energy efficient solutions that try to minimize overall energy consumption. One set of energy-efficient solutions is based on best fit decreasing (BFD) algorithm. In this paper, we evaluate the performance of existing energy efficient BFD algorithms based on various workloads and migration techniques. Moreover, considering the significance of Service Level Agreement (SLA), we introduce SLA-awareness in traditional BFD algorithm to minimize the SLA violation. We present the analysis and observations for each of the considered techniques based on total energy consumption, average SLA violations, and SLA performance degradation due to migration.
Year
DOI
Venue
2015
10.1109/DSDIS.2015.104
DSDIS
Keywords
Field
DocType
Cloud Computing, Resource Management, Energy Efficiency, Best Fit Decreasing, Performance Evaluation
Resource management,Algorithm design,Computer science,Efficient energy use,Service-level agreement,Server,Algorithm,Real-time computing,Bandwidth (signal processing),Energy consumption,Cloud computing
Conference
Citations 
PageRank 
References 
2
0.36
21
Authors
6
Name
Order
Citations
PageRank
Saad Mustafa1394.76
Kashif Bilal244325.77
Sajjad Ahmad Madani340926.21
Nikos Tziritas423021.85
Samee Ullah Khan5160581.01
Laurence T. Yang66870682.61