Executing Bag of Distributed Tasks on the Cloud: Investigating the Trade-offs Between Performance and Cost

Conference object, Preprint, Contribution for newspaper or weekly magazine English OPEN
Thai, Long; Varghese, Blesson; Barker, Adam;
(2014)
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • Related identifiers: doi: 10.1109/CloudCom.2014.29
  • Subject: Computer Science - Distributed, Parallel, and Cluster Computing | QA75 | QA75 Electronic computers. Computer science

This research is supported by the EPSRC grant ‘Working Together: Constraint Programming and Cloud Computing’ (EP/K015745/1), a Royal Society Industry Fellowship ‘Bringing Science to the Cloud’, an EPSRC Impact Acceleration Grant (IAA) and an Amazon Web Services (AWS) Ed... View more
  • References (15)
    15 references, page 1 of 2

    [1] B. Chun, D. Culler, T. Roscoe, A. Bavier, L. Peterson, M. Wawrzoniak, and M. Bowman, “Planetlab: An overlay testbed for broad-coverage services,” SIGCOMM Comput. Commun. Rev., vol. 33, pp. 3-12, July 2003.

    [2] J. Tordsson, R. S. Montero, R. Moreno-Vozmediano, and I. M. Llorente, “Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers,” Future Gener. Comput. Syst., vol. 28, pp. 358-367, Feb. 2012.

    [3] J. L. Lucas-Simarro, R. Moreno-Vozmediano, R. S. Montero, and I. M. Llorente, “Scheduling strategies for optimal service deployment across multiple clouds,” Future Gener. Comput. Syst., vol. 29, pp. 1431-1441, Aug. 2013.

    [4] Q. Zhang, Q. Zhu, M. Zhani, and R. Boutaba, “Dynamic service placement in geographically distributed clouds,” in Distributed Computing Systems (ICDCS), 2012 IEEE 32nd International Conference on, pp. 526-535, June 2012.

    [5] H. Qian and Q. Wang, “Towards proximity-aware application deployment in geo-distributed clouds,” Advances in Computer Science and its Applications, vol. 2, no. 3, 2013.

    [6] Y. Kang, Z. Zheng, and M. Lyu, “A latency-aware codeployment mechanism for cloud-based services,” in Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on, pp. 630-637, June 2012.

    [7] J. Zhu, Z. Zheng, Y. Zhou, and M. Lyu, “Scaling serviceoriented applications into geo-distributed clouds,” in Service Oriented System Engineering (SOSE), 2013 IEEE 7th International Symposium on, pp. 335-340, March 2013.

    [8] M. Luckeneder and A. Barker, “Location, location, location: Data-intensive distributed computing in the cloud,” in In Proceedings of IEEE CloudCom 2013, pp. 647-653, Dec 2013.

    [9] M. Ryden, K. Oh, A. Chandra, and J. B. Weissman, “Nebula: Distributed edge cloud for data intensive computing,” 2014.

    [10] K. Ranganathan and I. Foster, “Decoupling computation and data scheduling in distributed data-intensive applications,” in Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing, HPDC '02, (Washington, DC, USA), pp. 352-, IEEE Computer Society, 2002.

  • Related Organizations (3)
  • Metrics
Share - Bookmark