• Chastain, Walter Cooper, and Stephen Emille Chin. “System and methods for UICC-based secure communication.” U.S. Patent No. 9,461,993. 4 Oct. 2016.
  • Song, Linqi, Sundara Rajan Srinivasavaradhan, and Christina Fragouli. “The Benefit of Being Flexible in Distributed Computation.” arXiv preprint arXiv:1705.08464 (2017).
  • Nasir, Muhammad Anis Uddin, et al. “Load Balancing for Skewed Streams on Heterogeneous Cluster.” arXiv preprint arXiv:1705.09073 (2017).
  • Yin, Jinsong, and Yuanyuan Qiao. “Performance modeling and optimization of MapReduce programs.” Cloud Computing and Intelligence Systems (CCIS), 2014 IEEE 3rd International Conference on. IEEE, 2014.
  • Yan, Wei, et al. “An Optimization Algorithm for Heterogeneous Hadoop Clusters Based on Dynamic Load Balancing.” Parallel and Distributed Computing, Applications and Technologies (PDCAT), 2016 17th International Conference on. IEEE, 2016.
  • Shi, Yingjie, Lei Wang, and Fang Du. “Performance and energy efficiency of big data systems: characterization, implication and improvement.” Proceedings of the 6th International Conference on Software and Computer Applications. ACM, 2017.
  • T. Gunarathne, W. Tak-Lon, J. Qiu, G. Fox, “MapReduce in the clouds for science,” 2nd IEEE Conference on Cloud Computing Technology and Science, CloudCom-2010, pp. 565–572, 2010.
  • R. Ananthanarayanan, K. Gupta, P. Pandey, H. Pucha, P. Sarkar, M. Shah, R. Tewari, “Cloud analytics: Do we really need to reinvent the storage stack?,” In Proc. of the HotCloud Workshop, San Diego, 2009.
  • R. L. Grossman, “The Case for Cloud Computing,” IT Professional, vol.11, no.2, pp.23-27, March-April 2009.
  • J. Dean, S. Ghemawat, “MapReduce: Simplified Data Processing on Large Clusters,” In Proc. of the 6th Symposium on Operating Systems Design and Implementation, San Francisco CA, 2004.
  • K. Shvachko, H. Huang, S. Radia, R. Chansler, “The hadoop distributed file system,” in Proc. of the 26th IEEE (MSST2010) Symposium on Massive Storage Systems and Technologies, 2010.
  • M. Isard, M. Budiu, Y. Yu, A. Birrell, D. Fetterly, “Dryad: distributed data-parallel programs from sequential building blocks,” In Proc. of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007 (EuroSys ’07), 2007.
  • M. Zaharia, A. Konwinski, A.D. Joseph, R. Katz, I. Stoica, “Improving MapReduce Performance in Heterogeneous Environments,” In USENIX OSDI, 2008.
  • G. Ananthanarayanan, S. Kandula, A. Greenberg, I. Stoica, Y. Lu, B. Saha, E. Harris, “Reining in the outliers in map-reduce clusters using Mantri,” In Proc. of the 9th USENIX OSDI Symposium, 2010.
  • K. Ren, Y. Kwon, M. Balazinska, B. Howe, “Hadoop’s adolescence: a comparative workload analysis from three research clusters,” Tech. Report UW-CSE-12-06-01, University of Washington, 2012.
  • Y. Chen, S. Alspaugh, R. H. Katz, “Design insights for MapReduce from diverse production workloads,” Technical Report UCB/EECS-2012-17, EECS Dep., University of California, Berkeley, 2012.
  • G. Ananthanarayanan, A. Ghodsi, S. Shenker, I. Stoica, “Effective straggler mitigation: attack of the clones,” In Proc. of the 10th Symp. on Networked Systems Design and Implementation (NSDI), 2013.
  • F. Ahmad, S. T. Chakradhar, A. Raghunathan, T. N. Vijaykumar, “Tarazu: optimizing mapreduce on heterogeneous clusters,” In Proc. of the 17th ASPLOS Conf., 2012.
  • G. Ananthanarayanan, S. Agarwal, S. Kandula, A. Greenberg, I. Stoica, D. Harlan, E. Harris, “Scarlett: Coping with Skewed Popularity Content in MapReduce Clusters,” In ACM EuroSys, 2011.
  • H. Karloff, S. Suri, S. Vassilvitskii, “A model of computation for MapReduce,” In Proc. ACM-SIAM Sympos. Discrete Algorithms (SODA), pp. 938–948, 2010.
  • B. Li, E. Mazur, Y. Diao, A. McGregor, P. Shenoy, “A Platform for Scalable One-Pass Analytics using MapReduce,” In Proceedings of ACM SIGMOD Conf., 2011.
  • X. Yang, J. Sun, “An analytical performance model of mapreduce,” In Proc. of Cloud Computing and Intelligence Systems (CCIS), 2011.
  • X. Lin, Z. Meng, C. Xu, M. Wang, “A practical performance model for hadoop mapreduce,” In Proc. Of CLUSTER Workshops, 2012.
  • E. Krevat, T. Shiran, E. Anderson, J. Tucek, J.J. Wylie, G.R. Ganger, “Applying Performance Models to Understand Data-intensive Computing Efficiency,” Technical Report CMU-PDL-10-108, Carnegie Mellon University, Pittsburgh, 2010.
  • Y. Kwon, M. Balazinska, B. Howe, J. Rolia, “SkewTune: Mitigating skew in MapReduce applications,” In Proc. of SIGMOD Conf., pages 25–36, 2012.
  • J. Tan, X. Meng, L. Zhang, “Delay tails in MapReduce scheduling,” in Proc. of the SIGMETRICS/PERFORMANCE Conf., 2012.
  • J. Tan, Y. Wang, W. Yu, and L. Zhang, “Non-work-conserving effects in MapReduce: diffusion limit and criticality,” In Proc. of the 14th ACM SIGMETRICS, Austin, Texas, USA, 2014.
  • M. Lin, J. Tan, A. Wierman, L. Zhang, “Joint optimization of overlapping phases in MapReduce,” Performance Evaluation, 2013.
  • T. Condie, N. Conway, P. Alvaro, J. M. Hellerstein, K. Elmleegy, and R. Sears, “Mapreduce online,” In Proc. of NSDI, 2010.
  • R. Chaiken, B. Jenkins, P.-A. Larson, B. Ramsey, D. Shakib, S. Weaver, J. Zhou, “Scope: Easy and efficient parallel processing of massive data sets,” In Proc. of VLDB, 2008.
  • Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka, S. Anthony, H. Liu, P. Wyckoff, R. Murthy, “Hive – a warehousing solution over a Map-Reduce framework,” PVLDB, vol.2, no.2, pp. 1626–1629, 2009.
  • S. Li, S. Hu, S. Wang, L. Su, T. Abdelzaher, I. Gupta, R. Pace. “WOHA: Deadline-Aware Map-Reduce Workflow Scheduling Framework over Hadoop Cluster,” In Proc. of 34th International Conference on Distributed Computing Systems (ICDCS), 2014.
  • V.A. Saletore, K. Krishnan, V. Viswanathan, M.E. Tolentino, “HcBench: Methodology, Development, and Characterization of a Customer Usage Representative Big Data/Hadoop Benchmark,” IEEE International Symposium on Workload Characterization, 2013.
  • M. A. Marsan, G. Chiola, “On Petri Nets with Deterministic and Exponentially Distributed Firing Times,” Advances in Petri Nets, LNCS, vol. 266, Springer, pp. 132-145, 1987.
  • Feldmann, W. Whitt, “Fitting mixtures of exponentials to long-tail distributions to analyze network performance models”, In Proc. of IEEE INFOCOM, 1997.
  • J. Li , Y.S. Fan, M.C. Zhou “Performance modeling and analysis of workflow,” IEEE Trans. on Systems, Man, Cybernetics—Part A: Systems and Humans, vol. 34, no. 2, pp. 229-242, 2004.
  • R. B. J. T. Allenby and A. B. Slomson, “How to count: An introduction to combinatorics,” 2nd ed. CRC Press, pp. 51-60, 2011.
  • Kemper, M. Mandjes, “Mean sojourn times in two-queue fork-join systems: bounds and approximations,” OR Spectrum 34(3), 2012.
  • S. Lebrecht, W. J. Knottenbelt, “Response Time Approximations in Fork-Join Queues,” in Proc. of the 23rd UK Performance Engineering Workshop (UKPEW), July, 2007.
  • E. Argollo, A. Falcón, P. Faraboschi, M. Monchiero, D. Ortega, “COTSon: infrastructure for full system simulation,” ACM SIGOPS Operating Systems Review, v.43 n.1, Jan 2009.
  • Kaw, E. Kalu, “Numerical Methods with Applications,” Holistic Numerical Methods Institute, Dec. 2008.
  • Makowski, S. Varma, “Interpolation approximations for symmetric fork-join queues,” Performance Evaluation, vol.20, 145-165, 1994.
  • V. J. Reddi, B. Lee, T. Chilimbi, K. Vaid, “Web Search Using Mobile Cores: Quantifying and Mitigating the Price of Efficiency,” in Proc. of ISCA, 2010.
  • Gross, J. F. Shortle, J. M. Thompson, C. M. Harris, “Fundamentals of Queueing Theory,” 4th ed. John Wiley&Sons, 2008.
  • S. Kavulya, J. Tany, R. Gandhi, P. Narasimhan, “An analysis of traces from a production mapreduce cluster,” In 10th IEEE/ACM CCGrid, pages 94–103, 2010.
  • Y. Chen, S. Alspaugh, and R. H. Katz, “Design insights for mapreduce from diverse production workloads,” Technical Report UCB/EECS-2012-17, EECS Dept, University of California, Berkeley, Jan 2012.
  • G. Ananthanarayanan, M. Hung, X. Ren, I. Stoica, A. Wierman, and M. Yu, “GRASS: Trimming Stragglers in Approximation Analytics,” In Proceedings of the USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2014.
  • S. Nadarajah, S. Kotz, “The generalized Pareto sum,” HYDROLOGICAL PROCESSES 22, doi:10.1002/hyp.6602, pp.288–294, 2008.
  • M. Alizadeh, A. Greenberg, D. A. Maltz, J. Padhye, P. Patel, B. Prabhakar, S. Sengupta, and M. Sridharan, “DCTCP: Efficient packet transport for the commoditized data center,” In SIGCOMM, 2010.
  • J. Dean and L. A. Barroso, “The tail at scale,” Communications of the ACM, Vol. 56 No. 2, pp.74-80, 2013.
  • Lazowska, J. Zahorjan, G. Graham, K. Sevcik, “Quantitative System Performance: Computer System Analysis Using Queueing Network Models,” Prentice-Hall, Englewood Cliffs, NJ, 1984.
  • J. F. C. Kingman, “The single server queue in heavy traffic,” Proc. Camb. Phil. Soc. 57, pp. 902-904, 1961.
  • Clauset , C. R. Shalizi , M. E. J. Newman, “Power-Law Distributions in Empirical Data,” SIAM Review, vol.51 no.4, pp.661-703, 2009.