Paper Info
Title
A Novel Method for the Synthetic Generation of Non-I.I.D Workloads for Cloud Data Centers
Abstract
Cloud data center workloads have time- dependencies and are hence non-i.i.d (independent and identically distributed). In this paper, we propose a new model-based method for creating synthetic workload traces for cloud data centers that have similar time characteristics and cumulative distributions to those of the actual traces. We evaluate our method using the actual resource request traces of Azure collected in 2019 and the well-known Google cloud trace. Our method enables generating synthetic traces that can be used for a more realistic evaluation of cloud data centers.
Year
DOI
Venue
2020
10.1109/ISCC50000.2020.9219577
2020 IEEE Symposium on Computers and Communications (ISCC)
Keywords
DocType
ISSN
cloud computing,model-based workload generation,distribution fitting
Conference
1530-1346
ISBN
Citations 
PageRank 
978-1-7281-8086-1
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Furkan Koltuk100.34
Ece Guran Schmidt214616.27