Hybrid Nature-inspired algorithm for efferent cloud resource utilization

  • Authors

    • Monika .
    • Vivek Jaglan
    • Jugnesh Kumar
    • Akshat Agrawal
    2018-03-10
    https://doi.org/10.14419/ijet.v7i2.4.10036
  • Cloud computing, genetic algorithm, load balancing, fitness value, load percentage.
  • Cloud computing has come up as a standout amongst the most encouraging &reliable advancements in the IT part. However by and by there exists a noteworthy issue of load adjusting in the distributed computing condition. This paper comprises of an answer for streamlining the heap utilizing hereditary calculation. Hereditary calculation which takes after the transformative system can build up an answer near ideal arrangement. The proposed calculation is produced by consolidating two existing calculations by considering cost an incentive as the wellness work. The workload is adjusted by the considering the mix of both the heap rate and cost estimation of the assets. Allotment of assets is performed by taking the best fit esteem and lessening the reaction time and general cost. Reenactment comes about are indicated utilizing the cloud examiner test system.

  • References

    1. [1] F. Shahzad, Best in class Survey on Cloud Computing Security Challenges Approaches and Solutions, Proc The sixth International Symposium on Adhoc and sensor systems Procedia Science, 3 (2014), 150-156.

      [2] Q. Zhang, L. Cheng, R. Boutaba, Cloud Computing: a Perspective Study, Journal of Internet Services and Applications 10 (2010) 7– 18.

      [3] N. Antonopoulos, L. Gillam, Distributed computing Principles, Systems and Applications, Springer International Edition 12 (2010) 1598-1610.

      [4] K. Chandrasekaran, U. Divakarla, Load Balancing of Virtual Machine Resources in Cloud Using Genetic Algorithm, ICCN , 7 (2013), 156– 168

      [5] G. Joshi, S. Verma, Load adjusting approach in distributed computing utilizing extemporized Genetic Algorithm: A delicate Computing Approach, International Journal of Computer applications,122 (2015) 24-28.

      [6] G. Portalwi, A power proficient Genetic Algorithm for asset assignment on distributed computing server farms, Proc. IEEE third International Conference on Cloud Networking(Cloudnet) 7, (2014) 58-63.

      [7] K. Dasgupta, B. Mandala, A Genetic Algorithm (GA) based Load Balancing Strategy for Cloud Computing, Proc. Global Conference on Computational Intelligence: Modeling Techniques and Applications Procedia Technology, 10 (2013) 341-347.

      [8] M. Shahjahan, K. Mohaimenul Kabir. Dr. Rabiul Islam. (2015). Procedure of Load Balancing In Cloud Computing utilizing Genetic Algorithm. Electrical and Computer Engineering: An International Journal 4, 2, (2015). 57-65 ,

      [9] C. Cheng, H. Chin, Dynamic Multiservice stack adjusting in cloud based mixed media framework. IEEE frameworks diary, 8, (2014) 1-10.

      [10] A. Jain. S.Chaudari, Hereditary Algorithm based idea configuration to upgrade arrange adjust. ICTAT Journal on delicate registering. 2, 4 (2012) 357-360

      [11] S. Kaur, A. Verma. An effective way to deal with hereditary calculation for undertaking planning for distributed computing condition. Global Journal of Informational Technology and software engineering. 15 (2012) 74-79.

      [12] S. Suraj. R Natchadalingam.). Versatile Genetic Algorithm for productive Resource administration in distributed computing. Global Journal of Emerging Technology and Advanced designing 4, 2 (2014) 21-25.

      [13] R. Malhotra. N. Singh. Y. Singh. Hereditary Algorithms: Concepts, Design for Optimization of Process Controllers. PC and Information Science. 4, 2 (2011) 39-54.

      [14] J. Zhao, K. Yang. (2016). A Heuristic Clustering-Based Task Deployment Approach for Load Balancing Using Bayes Theorem in Cloud Environment. IEEE Transactions on Parallel And Distributed Systems. 27(2), pp 305-316.

      [15] A. Nahir, Replication-Based Load Balancing. IEEE Transactions on Parallel and conveyed Systems 27, 2, (2016). 494-507.

      [16] J. Zhao, K. Yang, A Heuristic Clustering-Based Task Deployment Approach for Load Balancing Using Bayes Theorem in Cloud Environment. IEEE Transactions on Parallel And Distributed Systems, 27, 2 (2016) 305-316.

  • Downloads

  • How to Cite

    ., M., Jaglan, V., Kumar, J., & Agrawal, A. (2018). Hybrid Nature-inspired algorithm for efferent cloud resource utilization. International Journal of Engineering & Technology, 7(2.4), 26-29. https://doi.org/10.14419/ijet.v7i2.4.10036