Performance modeling of cloud apps using message queueing as a service (MaaS)

This paper presents an analytical model to study the performance of cloud applications using message queueing as a service (MaaS). MaaS is a cloud service which allows the development departments to focus on delivering business and computing applications without being concerned with the underlying message queueing infrastructure to be scalable, secure, and reliable. Estimating the service delay (prior to provisioning cloud resources) of this type of cloud apps is an important engineering and resource management problem. Such estimation would help in computing the overall network and service delay that users experience. In a way, cloud providers would allocate the appropriate capacity for the needed cloud resources to meet the Service Level Agreement (SLA) parameters. In this paper, we present an analytical model by using Markov chain to study the performance of cloud apps which use MaaS. Given the expected request arrival rate, the queue size, and the expected service rate of each processing stage of the cloud app, our analytical model can estimate the app performance in terms of key SLA parameters which include response time, throughput, and request loss. In addition, our model yields equations for other key performance measures which include system idleness and utilization, queuing delay, and system and queue occupancies. Our analytical model is verified and validated by using discrete-event simulation and experimental measurements taken from an experiment conducted on AWS (Amazon Web Services) cloud.

[1]  Rajiv Ranjan,et al.  Streaming Big Data Processing in Datacenter Clouds , 2014, IEEE Cloud Computing.

[2]  Xiaoyun Zhu,et al.  AppRAISE: application-level performance management in virtualized server environments , 2009, IEEE Transactions on Network and Service Management.

[3]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[4]  MisicJelena,et al.  Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems , 2012 .

[5]  Martin Höst,et al.  Web server traffic in crisis conditions , 2005 .

[6]  Robert D. van der Mei,et al.  Web Server Performance Modeling , 2001, Telecommun. Syst..

[7]  Asser N. Tantawi,et al.  An analytical model for multi-tier internet services and its applications , 2005, SIGMETRICS '05.

[8]  Walter Willinger,et al.  On the Self-Similar Nature of Ethernet Traffic ( extended version ) , 1995 .

[9]  Marcel F. Neuts,et al.  Matrix-geometric solutions in stochastic models - an algorithmic approach , 1982 .

[10]  Sally Floyd,et al.  Wide-area traffic: the failure of Poisson modeling , 1994 .

[11]  S. Wittevrongel,et al.  Queueing Systems , 2019, Introduction to Stochastic Processes and Simulation.

[12]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[13]  Prashant J. Shenoy,et al.  Agile dynamic provisioning of multi-tier Internet applications , 2008, TAAS.

[14]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[15]  信息学.  Amazon Simple Queue Service , 2010 .

[16]  Osman Ghazali,et al.  Modeling of cloud system using Erlang formulas , 2011, The 17th Asia Pacific Conference on Communications.

[17]  Emily Halili,et al.  Apache JMeter , 2008 .

[18]  K. Preston White,et al.  An Effective Truncation Heuristic for Bias Reduction in Simulation Output , 1997, Simul..

[19]  Raj Jain,et al.  The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling , 1991, Wiley professional computing.

[20]  Raouf Boutaba,et al.  Estimating service response time for elastic cloud applications , 2012, 2012 IEEE 1st International Conference on Cloud Networking (CLOUDNET).

[21]  K. Mani Chandy,et al.  Approximate Methods for Analyzing Queueing Network Models of Computing Systems , 1978, CSUR.

[22]  R. Syski,et al.  Fundamentals of Queueing Theory , 1999, Technometrics.

[23]  Walter Willinger,et al.  Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level , 1997, TNET.

[24]  Raouf Boutaba,et al.  Performance Modeling and Analysis of Network Firewalls , 2012, IEEE Transactions on Network and Service Management.