Title
Dynamic Resource Allocation Through Workload Prediction for Energy Efficient Computing.
Abstract
Rapid and continuous increase in online information exchange and data based services has led to an increase in enterprise data centres. Energy efficient computing is key to a cost effective operation for all such enterprise IT systems. In this paper we propose dynamic resource allocation in server based IT systems through workload prediction for energy efficient computing. We use CPU core as a dynamic resource that can be allocated and deallocated based on predicted workload. We use online workload prediction as opposed to offline statistical analysis of workload characteristics. We use online learning and workload prediction using neural network for online dynamic resource allocation for energy efficient computing. We also analyse the effect of dynamic resource allocation on clients by measuring the request response time to clients for variable number of cores in operation. We show that dynamic resource allocation through workload prediction in server based IT systems can provide a cost effective, energy efficient and reliable operation without effecting quality of experience for clients.
Year
DOI
Venue
2016
10.1007/978-3-319-46562-3_3
ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS
Keywords
Field
DocType
Energy efficient computing,Dynamic resource allocation,Workload prediction,NARX neural network
Computer science,Efficient energy use,Workload,Information exchange,Resource allocation,Quality of experience,Enterprise data management,Multi-core processor,Request–response,Distributed computing
Conference
Volume
ISSN
Citations 
513
2194-5357
1
PageRank 
References 
Authors
0.36
0
3
Name
Order
Citations
PageRank
Adeel Ahmed110.36
David Brown2326.26
Alexander E. Gegov3478.47