CFP last date
20 May 2024
Reseach Article

From Concept to Algorithmic Implementation: Optimized Sharing of Resources in Cloud Computing Environment

by P. K. Suri, Himanshi Goyal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 9
Year of Publication: 2014
Authors: P. K. Suri, Himanshi Goyal
10.5120/17210-7435

P. K. Suri, Himanshi Goyal . From Concept to Algorithmic Implementation: Optimized Sharing of Resources in Cloud Computing Environment. International Journal of Computer Applications. 98, 9 ( July 2014), 6-16. DOI=10.5120/17210-7435

@article{ 10.5120/17210-7435,
author = { P. K. Suri, Himanshi Goyal },
title = { From Concept to Algorithmic Implementation: Optimized Sharing of Resources in Cloud Computing Environment },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 9 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number9/17210-7435/ },
doi = { 10.5120/17210-7435 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:25:45.093127+05:30
%A P. K. Suri
%A Himanshi Goyal
%T From Concept to Algorithmic Implementation: Optimized Sharing of Resources in Cloud Computing Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 9
%P 6-16
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing environment is referred as a collection of services which are delivered via the Internet. It depends upon sharing of resources to maximize the utilization of shared resources, and to achieve consistency and economies of scale. Resource management is very important for every system. Performance, functionality and cost are the three basic factors that are affected by resource management for system evaluation. Cloud resource management means to allocate and schedule computing resources. In this paper, various resource allocation and scheduling strategies are considered that helps in achieving high resource utilization and users demands. Various resource allocation strategies that are discussed in this paper are based on various parameters such as: location, time, topology, applications, hardware, priority, QoS etc. to meet the needs of cloud application. Similarly, scheduling strategies are based on parameters: cost, time, location, Qos, priority, load-balancing etc. to achieve high performance computing and best system throughput.

References
  1. Brijender Kahanwal and Tejinder Pal Singh, "The Distributed Computing Paradigms: P2P, Grid, Cluster, Cloud, and Jungle", International Journal of Latest Research in Science and Technology, Vol. 1, No. 2, pp. 183-187 , 2012.
  2. Sagar Girase, Rahul Samant, Mayank Sohani, and Suraj Patil, "Review on: Resource Provisioning in Cloud Computing Environment", International Journal of Science and Research, Vol. 2, No. 11, 2013.
  3. V. Vinothina, Dr. R. Sridaran, and Dr. Padmavathi Ganapathi, "A Survey on Resource Allocation Strategies in Cloud Computing", International Journal of Advanced Computer Science and Applications, Vol. 3, No. 6, 2012.
  4. Pinal Salot, "A Survey of Various Scheduling Algorithm in Cloud Computing Environment", International Journal of Research in Engineering and Technology, Vol. 2, No. 2, 2013.
  5. Gunho Lee, Niraj Tolia, Parthasarathy Ranganathan, and Randy H. Katz, "Topology-Aware Resource Allocation for Data-Intensive Workloads", ACM SIGCOMM Computer Communication Review, Vol. 41, No. 1, pp. 120-124, 2011.
  6. Zhen Kong et. al, "Mechanism Design for Stochastic Virtual Resource Allocation in Non-Cooperative Cloud Systems", IEEE 4th International Conference on Cloud Computing, pp. 614-621, 2011.
  7. Abirami S. P. and Shalini Ramanathan, "Linear Scheduling Strategy for Resource Allocation in Cloud Environment", International Journal on Cloud Computing: Services and Architecture, Vol. 2, No. 1, pp. 9-17, 2012.
  8. Kuo-Chan Huang and Kuan-Po Lai, "Processor Allocation Policies for Reducing Resource Fragmentation in Multi Cluster Grid and Cloud Environments", IEEE, pp. 971-976, 2010.
  9. Daniel Warneke and Odej Kao, "Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud", IEEE Transactions on Parallel and Distributed Systems, 2011.
  10. FetahiWuhib and Rolf Stadler, "Distributed Monitoring and Resource Management for Large Cloud Environments", IEEE, pp. 970-975, 2011.
  11. K C Gouda, Radhika T V, and Akshatha M, "Priority Based Resource Allocation Model for Cloud Computing", International Journal of Science, Engineering and Technology Research, Vol. 2, No. 1, 2013.
  12. Wei-Yu Lin et al, "Dynamic Auction Mechanism for Cloud Resource Allocation", IEEE/ACM 10th International Conference on Cluster, Cloud and Grid Computing, pp. 591-592, 2010.
  13. Xindong YOU, Xianghua XU, Jian Wan, and Dongjin YU, "RAS-M :Resource Allocation Strategy based on Market Mechanism in Cloud Computing", IEEE,pp. 256-263, 2009.
  14. Tram Truong Huu and John Montagnat, "Virtual Resource Allocations Distribution on a Cloud Infrastructure", IEEE, pp. 612-617, 2010.
  15. Satyanarayana . A, Dr. P. Suresh Varma, Dr. M. V. Rama Sundari, and Dr. P Sarada Varma, "Performance Analysis of Cloud Computing under Non Homogeneous Conditions", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 5, 2013.
  16. Christopher Clark, Keir Fraser, Steven Hand, Jacob Gorm Hanseny, Eric July, Christian Limpach, Ian Pratt, and Andrew Warfield, "Live Migration of Virtual Machines", 2nd Symposium on Networked Systems Design and Implementation, 2005.
  17. Bo An, Victor Lesser, David Irwin, and Michael Zink, "Automated Negotiation with Decommitment for Dynamic Resource Allocation in Cloud Computing", Proceedings of 9th International Conference on Autonomous Agents and Multi-agent Systems, Vol. 1, 2010.
  18. Gihun Jung and Kwang Mong Sim, "Location-Aware Dynamic Resource Allocation Model for Cloud Computing Environment", International Conference on Information and Computer Applications, Vol. 24, 2012.
  19. Nilabja Roy, Abhishek Dubey and Aniruddha Gokhale, "Efficient Autoscaling in the Cloud using Predictive Models for Workload Forecasting", Cloud Computing IEEE International Conference, pp. 500-507, 2011.
  20. HadiGoudaezi and MassoudPedram, "Multidimensional SLA-based Resource Allocation for Multi-tier Cloud Computing Systems", IEEE 4th International conference on Cloud Computing, pp. 324-331, 2011.
  21. Hien Nguyen et al, "SLA-Aware Virtual Resource Management for Cloud Infrastructures", IEEE 9th International Conference on Computer and Information Technology, pp. 357-362, 2009.
  22. Stephen S. Yau and Ho G. , "An Adaptive Resource Allocation for Service-Based Systems", International Journal of Software and Informatics, Vol. 3, No. 4, pp. 483–499, 2009.
  23. Griva I, Nash SG, and Sofer A. , "Linear and Nonlinear Optimization", 2nd Education Society for Industrial Mathematics, 2008.
  24. HadiGoudarzi and MassoudPedram, "Maximizing Profit in Cloud Computing System Via Resource Allocation", IEEE 31st International Conference on Distributed Computing Systems Workshops, pp. 1-6, 2011.
  25. Patricia Takako Endo et al. , "Resource Allocation for Distributed Cloud: Concept and Research Challenges", IEEE, pp. 42-46, 2011.
  26. Upendra Bhoi, "Enhanced Max-min Task Scheduling Algorithm in Cloud Computing", International Journal of Application or Innovation in Engineering and Management, Vol. 2, No. 4, 2013.
  27. Shamsollah Ghanbari, and Mohamed Othman, "A Priority based Job Scheduling Algorithm in Cloud Computing", International Conference on Advances Science and Contemporary Engineering, 2012.
  28. Wieczorek M. , Prodan R. and Fahringer T. , ''Scheduling of Scientific Workflows in ASKALON Grid Environment'', SIGMOD Rec. , Vol. 34, No. 3, pp. 56–62, 2005.
  29. Shaminder Kaur and Amandeep Verma, "An Efficient Approach to Genetic Algorithm for Task Scheduling in Cloud Computing Environment, International Journal of Information Technology and Computer Science, Vol. 10, pp. 74-79, 2012.
  30. Salim Bitam, "Bees Life Algorithm for Job Scheduling in Cloud Computing", 2nd International Conference on Communications and Information Technology, 2012.
  31. Mrs. S. Selvarani and Dr. G. Sudha Sadhasivam, "Improved Cost-Based Algorithm for Task Scheduling in Cloud Computing", IEEE, 2010.
  32. Poonam Devi, "Implementation of Cloud Computing By Using Short Job scheduling", International Journal of Advanced Research in Computer Science and Software Engineering, 2013.
  33. Laiping Zhao, Yizhi Ren, and Sakurai, K. , "A Resource Minimizing Scheduling Algorithm with Ensuring the Deadline and Reliability in Heterogeneous Systems", IEEE, 2011.
  34. M. Singh and P. K. Suri, "QPSMAX-MIN<>MIN-MIN: A Qos Based Predictive Max-Min, Min-Min Switcher Algorithm for Job Scheduling in a Grid", International Journal of Information and Technology, Vol. 7, No. 8, pp. 1176-1181, 2008.
  35. Dr. Amit Agarwal and Saloni Jain, "Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment", International Journal of Computer Trends and Technology, Vol. 9, No. 7, 2014.
  36. Jayadivya S K and S. Mary Saira Bhanu, "QoS Based Scheduling of Workflows in Cloud Computing", International Journal of Computer Science and Electrical Engineering, Vol. 1, No. 1, 2012.
  37. Huankai Chen, Professor Frank Wang, Dr Na Helian, and Gbola Akanmu, "User-Priority Guided Min-Min Scheduling Algorithm for Load Balancing in Cloud Computing", Parallel Computing Technologies National Conference, pp. 1-8, 2013.
  38. Shuo Liu, Gang Quan, and Shangping Ren, "On-Line Scheduling of Real-Time Services for Cloud Computing", IEEE, 2010.
  39. Dr. V. Vaithiyanathan, R. Arvindh Kumar, S. Vignesh, B. Thamotharan, and B. Karthikeyan, "An Efficient TPD Scheduling Algorithm for Cloud Environment", International Journal of Engineering and Technology, Vol. 5, No. 3, 2013.
  40. Jiahui Jin, Junzhou Luo, Aibo Song, Fang Dong and Runqun Xiong, "BAR: An Efficient Data Locality Driven Task Scheduling Algorithm for Cloud Computing", 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Resource Management Resource Allocation Strategies Scheduling Strategies