International Journal of Recent Trends in Engineering & Research

online ISSN

HABC: Hybrid Optimization Method Based Resource Allocation for Improving the Energy Efficiency in Green Cloud

Publication Date : 09/11/2020

DOI : 10.23883/IJRTER.2020.6061.PSAIN


Author(s) :

Jeevitha.J.K , G.Athisha.


Volume/Issue :
Volume 6
,
Issue 11
(11 - 2020)



Abstract :

Cloud computing is one of the most important and plays a significant role in computing world. It makes all the cloud users happy in providing various kinds of services under SAAS, PAAS, and IAAS. Due to the increased number of customer and customer demands on services the number of services deployed in the cloud is also getting increased. Services accessed by the customers by Pay-N-Use. The resources allocated related to the user's request virtually by considering the numbers of cloud users and resources. But actual resource allocation in heterogeneous cloud environments is complicated, and the accuracy is less, so that, these problems are leads to the high level of energy consumptions. Various methods, potential experiments, and algorithms are proposed in the earlier research works to increase the efficiency of the resource allocation with QoS. This paper discourse the problem of optimum resource allocation to a user with improved Quality of Service (QoS) using HABC (Hybrid Artificial Bee Colony) method and identify the better influencing parameters using Design of Experiment (DoE) tool. Initially, the user requests and the resources are validated, then map the scheduled resources and finally choose the best and allocate the right resources using HABC algorithm. The simulation is conducted using CloudSim tool. The obtained results verified and the performance is evaluated by comparing the results to different evolutionary algorithms. The parameters such as energy, time, cost, valid request, optimum number resources, accurate mapping, and allocation considered as the QoS parameters which are calculated from the simulation and presented here. Keywords: Cloud Computing, Resource Allocation, Resource Mapping, Request Validation, Scheduling, Quality of Service. Nomenclature QoS: Quality of Service DoE: Design of Experiment SaaS: Software as a Service PaaS: Platform as a Service


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