Advertisement

High Performance Computing by the Crowd

  • Nunziato Cassavia
  • Sergio Flesca
  • Michele Ianni
  • Elio Masciari
  • Giuseppe Papuzzo
  • Chiara Pulice
Chapter
Part of the Studies in Big Data book series (SBD, volume 40)

Abstract

Computational techniques both from a software and hardware viewpoint are nowadays growing at impressive rates leading to the development of projects whose complexity could be quite challenging, e.g., bio-medical simulations. Tackling such high demand could be quite hard in many context due to technical and economic motivation. A good trade-off can be the use of collaborative approaches. In this paper, we address this problem in a peer to peer way. More in detail, we leverage the idling computational resources of users connected to a network. We designed a framework that allows users to share their CPU and memory in a secure and efficient way. Indeed, users help each others by asking the network computational resources when they face high computing demanding tasks. As we do not require to power additional resources for solving tasks (we better exploit unused resources already powered instead), we hypothesize a remarkable side effect at steady state: energy consumption reduction compared with traditional server farm or cloud based executions.

References

  1. 1.
    Agrawal, D., et al.: Challenges and opportunities with big data. A community white paper developed by leading researchers across the United States (2012)Google Scholar
  2. 2.
    Bhatia, R.: Grid computing and security issues. Int. J. Sci. Res. Publ. (IJSRP) 3(8) (2013)Google Scholar
  3. 3.
    Borkar, V.R., Carey, M.J., Li, C.: Inside “Big Data Management”: ogres, onions, or parfaits? In: International Conference on Extending Database Technology, pp. 3–14 (2012)Google Scholar
  4. 4.
    Brew, A., Greene, D., Cunningham, P.: Using crowdsourcing and active learning to track sentiment in online media. In: Proceedings of the 2010 Conference on ECAI 2010: 19th European Conference on Artificial Intelligence, pp. 145–150 (2010)Google Scholar
  5. 5.
    Chen, Z., Guo, S., Duan, R., Wang, S.: Security analysis on mutual authentication against man-in-the-middle attack. In: 2009 First International Conference on Information Science and Engineering, pp. 1855–1858 (2009)Google Scholar
  6. 6.
    T. Economist: Data, data everywhere. The Economist (2010)Google Scholar
  7. 7.
    Firdhous, M.: Implementation of security in distributed systems - a comparative study. CoRR (2012). arXiv:abs/1211.2032
  8. 8.
    Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: CrowdDB: answering queries with crowdsourcing. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 61–72Google Scholar
  9. 9.
    Harris, M.: Many-core GPU computing with NVIDIA CUDA. In: Proceedings of the 22nd Annual International Conference on Supercomputing, ICS ’08 (2008)Google Scholar
  10. 10.
    Howe, J.: Crowdsourcing: Why the Power of the Crowd is Driving the Future of Business, 1st edn. Crown Publishing Group, New York (2008)Google Scholar
  11. 11.
    Liu, N., Yang, G., Wang, Y., Guo, D.: Security analysis and configuration of SSL protocol. In: 2008 2nd International Conference on Anti-Counterfeiting, Security and Identification, pp. 216–219 (2008)Google Scholar
  12. 12.
    Liu, X., Lu, M., Ooi, B.C., Shen, Y., Wu, S., Zhang, M.: CDAS: a crowdsourcing data analytics system. Proc. VLDB Endow. 5(10), 1040–1051 (2012)CrossRefGoogle Scholar
  13. 13.
    Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system. Freely available on the web (2008)Google Scholar
  14. 14.
    Nature: Big data. Nature (2008)Google Scholar
  15. 15.
    Nickolls, J., Buck, I., Garland, M., Skadron, K.: Scalable parallel programming with CUDA. Queue 6(2) (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Nunziato Cassavia
    • 1
    • 2
  • Sergio Flesca
    • 1
  • Michele Ianni
    • 1
  • Elio Masciari
    • 2
  • Giuseppe Papuzzo
    • 2
  • Chiara Pulice
    • 3
  1. 1.DIMESUniversity of CalabriaRendeItaly
  2. 2.ICAR-CNRRendeItaly
  3. 3.UMIACSUniversity of MarylandCollege ParkUSA

Personalised recommendations