TY - GEN
T1 - Estimating service response time for elastic cloud applications
AU - Salah, Khaled
AU - Boutaba, Raouf
PY - 2012
Y1 - 2012
N2 - This paper presents a Markovian analytical model to estimate service response time for elastic cloud applications. Given the expected application workload, the number of virtual machine (VM) instances, and the capacity of each VM instance, the model can approximate the mean service time. The mean service time is a critical metric to estimate, and contributes to the SLA end-to-end response time experienced by application users. The end-to-end response time is an aggregated delay of the service time in addition to delays incurred at the network nodes and links. Our analytical model focuses on estimating the mean service time; however, the model is sufficiently general and can be extremely useful in studying cloud performance. Equations for key performance measures are derived. These measures include mean response time, throughput, request loss, queueing probability, and CPU utilization. The correctness of the model has been verified using discrete-event simulation.
AB - This paper presents a Markovian analytical model to estimate service response time for elastic cloud applications. Given the expected application workload, the number of virtual machine (VM) instances, and the capacity of each VM instance, the model can approximate the mean service time. The mean service time is a critical metric to estimate, and contributes to the SLA end-to-end response time experienced by application users. The end-to-end response time is an aggregated delay of the service time in addition to delays incurred at the network nodes and links. Our analytical model focuses on estimating the mean service time; however, the model is sufficiently general and can be extremely useful in studying cloud performance. Equations for key performance measures are derived. These measures include mean response time, throughput, request loss, queueing probability, and CPU utilization. The correctness of the model has been verified using discrete-event simulation.
KW - Cloud Computing
KW - Elastic Applications
KW - Performance Modeling and Analysis
KW - Queueing Theory
KW - Service and Network Delays
KW - SLA
UR - http://www.scopus.com/inward/record.url?scp=84876120874&partnerID=8YFLogxK
U2 - 10.1109/CloudNet.2012.6483647
DO - 10.1109/CloudNet.2012.6483647
M3 - Conference contribution
AN - SCOPUS:84876120874
SN - 9781467327985
T3 - 2012 1st IEEE International Conference on Cloud Networking, CLOUDNET 2012 - Proceedings
SP - 12
EP - 16
BT - 2012 1st IEEE International Conference on Cloud Networking, CLOUDNET 2012 - Proceedings
T2 - 2012 1st IEEE International Conference on Cloud Networking, CLOUDNET 2012
Y2 - 28 November 2012 through 30 November 2012
ER -