Research Area:  Cloud Computing

Abstract:

Cloud Computing is the new style of computing in the field of IT. Cloud computing is being vital on the internet as it shares various computing resources instead having personal devices to manage data and applications over internet. There is a lot of data stored on cloud and various resources requests for the same. The data and applications are maintained in the cloud computing by making the use of internet. It requires computing facilities on a large scale that depends on usage and to provide services in a very adjustable manner which may move up and down according to user demand. For cloud service providers, to provide the resources to the users in time is one of the tedious tasks. To comply this reason a proper node is to be selected that can complete the tasks for the users while maintaining quality of service. This paper proposed a hybrid algorithm by merging the gravitational search concept in ant colony optimization algorithm. The main idea behind proposed algorithm is its unique search approach that is being used for achieving task scheduling in cloud computing by allocating the incoming tasks to the virtual machines, thereby decreasing the makespan. The CloudSim toolkit package is used to simulate the algorithm and the results revealed better performance than the basic ant colony optimization and basic gravitational search algorithm.

Keywords:  

Author(s) Name:  Sunita Rani & P. K. Suri

Publisher name:  Springer

DOI:  10.1007/s41870-018-0175-3

Volume Information:  volume 12, pages 1451–1457 (2020)

Paper Link:   https://link.springer.com/article/10.1007/s41870-018-0175-3