Effective Modeling Approach for IaaS Data Center Performance Analysis under Heterogeneous Workload

Heterogeneity prevails not only among physical machines but also among workloads in real IaaS Cloud data centers (CDCs). The heterogeneity makes performance modeling of large and complex IaaS CDCs even more challenging. This paper considers the scenario where the number of virtual CPUs requested by each customer job may be different. We propose a hierarchical stochastic modeling approach applicable to IaaS CDC performance analysis under such a heterogeneous workload. Numerical results obtained from the proposed analytic model are verified through discrete-event simulations under various system parameter settings.

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

[2]  Gunter Bolch,et al.  Queueing Networks and Markov Chains - Modeling and Performance Evaluation with Computer Science Applications, Second Edition , 1998 .

[3]  Ram Chakka,et al.  Spectral expansion solution for some finite capacity queues , 1998, Ann. Oper. Res..

[4]  Randy H. Katz,et al.  Improving MapReduce Performance in Heterogeneous Environments , 2008, OSDI.

[5]  Kashi Venkatesh Vishwanath,et al.  Characterizing cloud computing hardware reliability , 2010, SoCC '10.

[6]  Gang Ren,et al.  Google-Wide Profiling: A Continuous Profiling Infrastructure for Data Centers , 2010, IEEE Micro.

[7]  Benjamin Hindman,et al.  Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.

[8]  Shicong Meng,et al.  Reliable State Monitoring in Cloud Datacenters , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[9]  Engin Kirda.  A security analysis of Amazon's Elastic Compute Cloud service , 2012, DSN Workshops.

[10]  Engin Kirda,et al.  A security analysis of Amazon's Elastic Compute Cloud service , 2012, IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN 2012).

[11]  Randy H. Katz,et al.  Heterogeneity and dynamicity of clouds at scale: Google trace analysis , 2012, SoCC '12.

[12]  Babak Falsafi,et al.  Clearing the clouds: a study of emerging scale-out workloads on modern hardware , 2012, ASPLOS XVII.

[13]  Kishor S. Trivedi,et al.  Modeling and performance analysis of large scale IaaS Clouds , 2013, Future Gener. Comput. Syst..

[14]  Evgenia Smirni,et al.  State-of-the-practice in data center virtualization: Toward a better understanding of VM usage , 2013, 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).

[15]  Jelena V. Misic,et al.  Analysis of a Pool Management Scheme for Cloud Computing Centers , 2013, IEEE Transactions on Parallel and Distributed Systems.

[16]  Qingsheng Zhu,et al.  A Petri-Net-Based Approach to Reliability Determination of Ontology-Based Service Compositions , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[17]  Jelena V. Misic,et al.  Modeling the Performance of Heterogeneous IaaS Cloud Centers , 2013, 2013 IEEE 33rd International Conference on Distributed Computing Systems Workshops.

[18]  Peter G. Harrison,et al.  Understanding, modelling, and improving the performance of web applications in multicore virtualised environments , 2014, ICPE.

[19]  Christina Delimitrou,et al.  Quasar: resource-efficient and QoS-aware cluster management , 2014, ASPLOS.

[20]  Kishor S. Trivedi,et al.  Scalable Analytics for IaaS Cloud Availability , 2014, IEEE Transactions on Cloud Computing.

[21]  Rajkumar Buyya,et al.  SLA-based virtual machine management for heterogeneous workloads in a cloud datacenter , 2014, J. Netw. Comput. Appl..

[22]  Benjamin C. Lee,et al.  Market mechanisms for managing datacenters with heterogeneous microarchitectures , 2014, TOCS.

[23]  Dario Bruneo,et al.  A Stochastic Model to Investigate Data Center Performance and QoS in IaaS Cloud Computing Systems , 2014, IEEE Transactions on Parallel and Distributed Systems.

[24]  Abhishek Verma,et al.  Large-scale cluster management at Google with Borg , 2015, EuroSys.

[25]  Cho-Li Wang,et al.  Optimization of Composite Cloud Service Processing with Virtual Machines , 2015, IEEE Transactions on Computers.

[26]  N. Rao,et al.  A Security Analysis of Amazon’s Elastic Compute Cloud Service , 2015 .

[27]  Bin Wang,et al.  Modeling Active Virtual Machines on IaaS Clouds Using an M/G/m/m+K Queue , 2016, IEEE Transactions on Services Computing.