Open AccessA Review of Dynamic Resource Allocation Framework for Large Amount of Cloud Enterprises
Author(s) -
B Vijaya Laxmi
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i2.1191
Subject(s) - cloud computing , computer science , resource allocation , task (project management) , scheduling (production processes) , service (business) , resource (disambiguation) , homogeneous , distributed computing , dynamic priority scheduling , computer security , resource management (computing) , business , computer network , quality of service , operations management , engineering , physics , marketing , thermodynamics , operating system , systems engineering
Cloud computing is an on-demand service because it offers dynamic flexible resource allocation for reliable and guaranteed services in pay as-you-use manner. Because of the consistently increasing demands of the clients for services or resources, it gets hard to allocate resources accurately to the client demands to satisfy their solicitations and also to take care of the Service Level Agreements (SLA) gave by the service suppliers. Dynamic resource allocation problem is one of the most challenging problems in the resource management problems. The dynamic resource allocation in cloud computing has attracted attention of the research network in the last couple of years. Many researchers around the world have thought of new ways of facing this challenge. Ad-hoc parallel data handling has arisen to be one of the executioner applications for Infrastructure-as-a-Service (IaaS) cloud. Number of Cloud supplier companies has started to incorporate frameworks for parallel data handling in their item which making it easy for clients to access these services and to convey their programs. The handling frameworks which are at present utilized have been intended for static and homogeneous bunch arrangements. So the allocated resources may be inadequate for large parts of the submitted tasks and unnecessarily increase preparing cost and time. Again because of opaque nature of cloud, static allocation of resources is conceivable, yet the other way around in dynamic situations. The proposed new generic data handling framework is expected to expressly misuse the dynamic resource allocation in cloud for task scheduling and execution.