Workflow Scheduling Under Secure Cloud Environment Using MPSO-SA
Babita Bhagat1, P.Sanyasi Naidu2

1Babita Bhagat, Department of Computer Engineering Pillai HOC College of Engineering & Technology Rasayani, Maharashtra, India.
2P.Sanyasi Naidu, Department of Computer Science & Engineering, GITAM University, Visakhapatnam, Andhra Pradesh, India.

Manuscript received on 02 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 7440-7446 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4689098319/2019©BEIESP | DOI: 10.35940/ijrte.C4689.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: In the distributed data-intensive computing environment, relegating certain assignments to specific machines in a protected way is a major test for the employment planning issue. The unpredictability of this issue increments with the size of the activity and it is hard to understand viably. A few metaheuristic calculations including particle swarm optimization (PSO) strategy and variable neighborhood particle swarm optimization VNPSO) system are utilized to tackle the employment planning issue in distributed computing. While allocating assignments to the machines, to fulfill the security requirements and to limit the cost capacity, we proposed an altered PSO with a scout adjustment (MPSO-SA) calculation which utilized a cyclic term called change administrator to get the best cost capacity. The exhibition of the proposed MPSO-SA booking component is contrasted and the Genetic calculation (GA), PSO and VNPSO systems and the exploratory outcome demonstrate that the proposed technique diminishes the likelihood of hazard with security requirements and it has preferable intermingling property over the current conventions.
Keywords— Cloud Computing, Metaheuristic, GA, PSO and VNPSO.

Scope of the Article:
Cloud Computing