A Novel Approach for Resource Allocation with Efficient Load Balancing in Cloud Environment

Authors(1) :-G. Sowjanya

Our framework depends on a monetary way to deal with overseeing shared server resources, in which services offer for resources as a component of conveyed performance. The plan and performance of resource service in a facilitating focus working framework, with an accentuation on energy as a driving resource service issue for huge server groups. A cloud application because of a demand steady with the service level agreements (SLA). Scaling is the way toward dispensing extra resources to a demand predictable with the SLA. So this task proposing, an energy-optimal activity demonstrates utilized for load balancing and application scales on a cloud. Our approach is planning an energy ideal task service and endeavoring to boost the quantity of servers working in this service. The objectives are to arrangement server resources for services in a way that naturally adjusts to offered stack, enhance the energy effectiveness of server by powerfully resizing the dynamic server set, and react to control supply interruptions or warm occasions by corrupting service.

Authors and Affiliations

G. Sowjanya
Department of MCA QIS College of Engineering Techology, Ongole, Andhra Pradesh, India

Cloud Service Providers (CSP), load balancing, FCFS, and SLA

  1. A Gandhi, M. Harchol-Balter, R. Raghunathan, and M.Kozuch. “AutoScale: dynamic, robust capacity management for multi-tier data centers.” ACM Trans. on Computer Systems, 30(4):1–26, 2012.
  2. A Gandhi, M. Harchol-Balter, R. Raghunathan, and M.Kozuch. “Are sleep states effective in data centers?” Proc. Int. Conf. on Green Comp., pp. 1–10, 2012.
  3. D Gmach, J. Rolia, L. Cherkasova, G. Belrose, T. Tucricchi, and A. Kemper. “An integrated approach to resource pool management: policies, efficiency, and quality metrics.” Proc. Int. Conf. on Dependable Systems and Networks, pp. 326–335, 2008.
  4. Google. “Google’s green computing: efficiency at scale.” http://static.googleuse-rcontent.com/external content/ untrusted dlcp/www.google.com/en/us/green/pdfs/google -green-computing.pdf (Accessed on August 29, 2013).
  5. V Gupta and M. Harchol-Balter. “Self-adaptive admission control policies for resource-sharing systems.” Proc. 11th Int. Joint Conf. Measurement and Modeling Computer Systems (SIGMETRICS’09), pp. 311–322, 2009.
  6. K Hasebe, T. Niwa, A. Sugiki, and K. Kato. “Powersaving in large-scale storage systems with data migration.” Proc IEEE 2nd Int. Conf. on Cloud computing.
  7. D Ardagna, B. Panicucci, M. Trubian, and L. Zhang. “Energy-aware autonomic resource allocation in multitier virtualized environments.” IEEE Trans. on Services Computing, 5(1):2–19, 2012.
  8. J Baliga, R.W.A. Ayre, K. Hinton, and R.S. Tucker. “Green cloud computing: balancing energy in processing, storage, and transport.” Proc. IEEE, 99(1):149-167, 2011.
  9. L A. Barroso and U. H¨ozle. “The case for energyproportional computing.” IEEE Computer, 40(12):33– 37, 2007.
  10. L. A. Barossso, J. Clidaras, and U.H¨ozle. The Datacenter as a Computer; an Introduction to the Design of Warehouse-Scale Machines. (Second Edition). Morgan & Claypool, 2013.
  11. A. Beloglazov, R. Buyya “Energy efficient resource management in virtualized cloud data centers.” Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Comp., 2
  12. A. Beloglazov, J. Abawajy, R. Buyya. “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing.” Future Generation Computer Systems, 28(5):755-768, 2012.
  13. A. Beloglazov and R. Buyya. “Managing overloaded hosts for dynamic consolidation on virtual machines in cloud centers under quality of service constraints.” IEEE Trans. on Parallel and Distributed Systems, 24(7):1366- 1379, 2013.
  14. M. Blackburn and A. Hawkins. “Unused server survey results analysis.” www.thegreengrid.org/media/White Papers/Unused%20Server%20Study WP 101910 v1. ashx?lang=en (Accessed on December 6, 2013).
  15. M. Elhawary and Z. J. Haas. “Energy-efficient protocol for cooperative networks.” IEEE/ACM Trans. on Networking, 19(2):561–574, 2011.
  16. L. Popa, G. Kumar, M. Chowdhury, A. Krishnamurthy, S. Ratnasamy, and I. Stoica, “Faircloud: sharing the network in cloud computing.” in Proc. of SIGCOMM, 2012, pp. 187–198.
  17. M. Lin, A. Wierman, L. L. H. Andrew, and E. Thereska, “Dynamic right-sizing for power-proportional data centers.” in Proc. of INFOCOM, 2011, pp. 1098–1106.
  18. S. T. Maguluri, R. Srikant, and L. Ying, “Stochastic models of load balancing and scheduling in cloud computing clusters.” in Proc. Of INFOCOM, 2012, pp. 702–710.
  19. A Gandhi, M. Harchol-Balter, R. Raghunathan, and M.Kozuch. “AutoScale: dynamic, robust capacity management for multi-tier data centers.” ACM Trans. on Computer Systems, 30(4):1–26, 2012.
  20. A Gandhi, M. Harchol-Balter, R. Raghunathan, and M.Kozuch. “Are sleep states effective in data centers?” Proc. Int. Conf. on Green Comp., pp. 1–10, 2012.
  21. D Gmach, J. Rolia, L. Cherkasova, G. Belrose, T. Tucricchi, and A. Kemper. “An integrated approach to resource pool management: policies, efficiency, and quality metrics.” Proc. Int. Conf. on Dependable Systems and Networks, pp. 326–335, 2008.
  22. Google. “Google’s green computing: efficiency at scale.” http://static.googleuse-rcontent.com/external content/ untrusted dlcp/www.google.com/en/us/green/pdfs/google -green-computing.pdf (Accessed on August 29, 2013).
  23. V Gupta and M. Harchol-Balter. “Self-adaptive admission control policies for resource-sharing systems.” Proc. 11th Int. Joint Conf. Measurement and Modeling Computer Systems (SIGMETRICS’09), pp. 311–322, 2009.
  24. K Hasebe, T. Niwa, A. Sugiki, and K. Kato. “Powersaving in large-scale storage systems with data migration.” Proc IEEE 2nd Int. Conf. on Cloud computing.
  25. D Ardagna, B. Panicucci, M. Trubian, and L. Zhang. “Energy-aware autonomic resource allocation in multitier virtualized environments.” IEEE Trans. on Services Computing, 5(1):2–19, 2012.
  26. J Baliga, R.W.A. Ayre, K. Hinton, and R.S. Tucker. “Green cloud computing: balancing energy in processing, storage, and transport.” Proc. IEEE, 99(1):149-167, 2011.
  27. L A. Barroso and U. H¨ozle. “The case for energyproportional computing.” IEEE Computer, 40(12):33– 37, 2007.
  28. L. A. Barossso, J. Clidaras, and U.H¨ozle. The Datacenter as a Computer; an Introduction to the Design of Warehouse-Scale Machines. (Second Edition). Morgan & Claypool, 2013.
  29. A. Beloglazov, R. Buyya “Energy efficient resource management in virtualized cloud data centers.” Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Comp., 2
  30. A. Beloglazov, J. Abawajy, R. Buyya. “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing.” Future Generation Computer Systems, 28(5):755-768, 2012.
  31. A. Beloglazov and R. Buyya. “Managing overloaded hosts for dynamic consolidation on virtual machines in cloud centers under quality of service constraints.” IEEE Trans. on Parallel and Distributed Systems, 24(7):1366- 1379, 2013.
  32. M. Blackburn and A. Hawkins. “Unused server survey results analysis.” www.thegreengrid.org/media/White Papers/Unused%20Server%20Study WP 101910 v1. ashx?lang=en (Accessed on December 6, 2013).
  33. M. Elhawary and Z. J. Haas. “Energy-efficient protocol for cooperative networks.” IEEE/ACM Trans. on Networking, 19(2):561–574, 2011.
  34. L. Popa, G. Kumar, M. Chowdhury, A. Krishnamurthy, S. Ratnasamy, and I. Stoica, “Faircloud: sharing the network in cloud computing.” in Proc. of SIGCOMM, 2012, pp. 187–198.
  35. M. Lin, A. Wierman, L. L. H. Andrew, and E. Thereska, “Dynamic right-sizing for power-proportional data centers.” in Proc. of INFOCOM, 2011, pp. 1098–1106.
  36. S. T. Maguluri, R. Srikant, and L. Ying, “Stochastic models of load balancing and scheduling in cloud computing clusters.” in Proc. Of INFOCOM, 2012, pp. 702–710.

Publication Details

Published in : Volume 4 | Issue 2 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 365-369
Manuscript Number : CSEIT184171
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Sowjanya, "A Novel Approach for Resource Allocation with Efficient Load Balancing in Cloud Environment", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 2, pp.365-369, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT184171

Follow Us

Contact Us