[1] Dean J, Barrosoluiz A B. The tail at scale. Commun. ACM, 2013, 56(2):74-80.[2] Grandl R, Chen Y, Khalid J, Yang S, Anand A, Benson T, Akella A. Harmony:Coordinating network, compute, and storage in software-defined clouds. In Proc. the 4th Annual Symposium on Cloud Computing (poster), Oct. 2013.[3] Buyya R, Calheiros R N, Son J, Dastjerdi A V, Yoon Y. Software-defined cloud computing:Architectural elements and open challenges. In Proc. International Conference on Advances in Computing, Communications and Informatics, Sept. 2014.[4] Jararweh Y, Al-Ayyoub M, Benkhelifa E, Vouk M, Rindos A et al. Software defined cloud:Survey, system and evaluation. Future Generation Computer Systems, 2016, 58:56-74.[5] Bao Y G, Wang S. Labeled von Neumann architecture for software-defined cloud. Journal of Computer Science and Technology, 2017, 32(2):220-224.[6] Amazon EC2 service level agreement. 2013. http://aws.amazon.com/ec2/sla/, Feb. 2017.[7] App engine service level agreement (SLA). https://developers.google.com/appengine/sla, Feb. 2017.[8] Microsoft. Service level agreements. https://azure.microsoft.com/en-us/support/legal/sla/. Feb. 2017.[9] Neamtiu I, Dumitra? T. Cloud software upgrades:Challenges and opportunities. In Proc. International Workshop on the Maintenance and Evolution of Service-Oriented and Cloud-Based Systems, Sept. 2011.[10] Lu Q, Xu X, Zhu L, Bass L, Li Z, Sakr S, Bannerman P L, Liu A. Incorporating uncertainty into in-cloud application deployment decisions for availability. In Proc. IEEE International Conference on Cloud Computing, Jun. 2013, pp.454-461.[11] Meyer J F. On evaluating the performability of degradable computing systems. IEEE Transactions on computers, 1980, 100(8):720-731.[12] Smith R, Trivedi K S, Ramesh A. Performability analysis:Measures, an algorithm, and a case study. IEEE Transactions on Computers, 1988, 37(4):406-417.[13] Amari S V, Xing L, Shrestha A, Akers J, Trivedi K S. Performability analysis of multistate computing systems using multivalued decision diagrams. IEEE Transactions on Computers, 2010, 59(10):1419-1433.[14] Ghosh R, Trivedi K S, Naik V K, Kim D S. End-to-end performability analysis for Infrastructure-as-a-Service cloud:An interacting stochastic models approach. In Proc. the 16th IEEE Pacific Rim International Symposium on Dependable Computing, Dec. 2010, pp.125-132.[15] Entezari-Maleki R, Trivedi K S, Movaghar A. Performability evaluation of grid environments using stochastic reward nets. IEEE Transactions on Dependable and Secure Computing, 2015, 12(2):204-216.[16] Wei B, Lin C, Kong X. Dependability modeling and analysis for the virtual data center of cloud computing. In Proc. High Performance Computing and Communications, Sept. 2011, pp.784-789.[17] Ahmed W, Hasan O, Tahar S. Formalization of reliability block diagrams in higher-order logic. Journal of Applied Logic, 2016, 18:19-41.[18] Wang Y, Luo C, Liu Z. Reliability analysis of multi-node SDDC using fault tree. In Proc. International Industrial Informatics and Computer Engineering Conference, Jan. 2015, pp.1155-1158.[19] Trivedi K S. Probability and Statistics with Reliability, Queuing and Computer Science Applications. John Wiley & Sons, 2008.[20] Ivanchenko O, Kharchenko V. Semimarkov availability models for an Infrastructure as a Service cloud with multiple pools. In Proc. International Conference on ICT in Education, Research, and Industrial Applications, Nov. 2016, pp.349-360.[21] Longo F, Ghosh R, Naik V K, Trivedi K S. A scalable availability model for Infrastructure-as-a-Service cloud. In Proc. the 41st IEEE/IFIP International Conference on Dependable Systems & Networks, Jun. 2011, pp.335-346.[22] Ghosh R, Longo F, Frattini F, Russo S, Trivedi K S. Scalable analytics for IaaS cloud availability. IEEE Transactions on Cloud Computing, 2014, 2(1):57-70.[23] Wei B, Lin C, Kong X. Dependability modeling and analysis for the virtual clusters. In Proc. International Conference on Computer Science and Network Technology, Volume 4, Dec. 2011, pp.2316-2320.[24] Dantas J, Matos R, Araujo J, Maciel P. Models for dependability analysis of cloud computing architectures for eucalyptus platform. International Transactions on Systems Science and Applications, 2012, 8:13-25.[25] Dantas J, Matos R, Araujo J, Maciel P. Eucalyptus-based private clouds:Availability modeling and comparison to the cost of a public cloud. Computing, 2015, 97(11):1121-1140.[26] Qiu X, Dai Y, Xiang Y, Xing L. A hierarchical correlation model for evaluating reliability, performance, and power consumption of a cloud service. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2016, 46(3):401-412.[27] Cooper B F, Silberstein A, Tam E, Ramakrishnan R, Sears R. Benchmarking cloud serving systems with YCSB. In Proc. the 1st ACM Symposium on Cloud Computing, Jun. 2010, pp.143-154.[28] Leitner P, Cito J. Patterns in the chaos-A study of performance variation and predictability in public IaaS clouds. ACM Transactions on Internet Technology, 2014, 16(3):1-15.[29] Iosup A, Prodan R, Epema D. IaaS cloud benchmarking:Approaches, challenges, and experience. In Cloud Computing for Data-Intensive Applications, Li X, Qiu J (eds.), Springer, 2014, pp.83-104.[30] Varghese B, Subba L T, Thai L T, Barker A D. DocLite:A Docker-based lightweight cloud benchmarking tool. In Proc. the 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2016), May. 2016, pp.213-222.[31] Fujita H, Matsuno Y, Hanawa T, Sato M, Kato S, Ishikawa Y. DS-Bench Toolset:Tools for dependability bench-marking with simulation and assurance. In Proc. IEEE/IFIP International Conference on Dependable Systems and Networks, Jun. 2012.[32] Sangroya A, Serrano D, Bouchenak S. Benchmarking dependability of MapReduce systems. In Proc. the 31st IEEE Symposium on Reliable Distributed Systems, Feb. 2012, pp.21-30.[33] Sangroya A, Bouchenak S, Serrano D. Experience with benchmarking dependability and performance of MapReduce systems. Perform. Eval., 2016, 101:1-19.[34] Little J D C. A proof for the queuing formula:L=w. Operations Research, 1961, 9(3):383-387.[35] Trivedi K S, Sahner R. Sharpe at the age of twenty two. ACM SIGMETRICS Performance Evaluation Review, 2009, 36(4):52-57. |