Fuzzy-based Security-Driven Optimistic Scheduling of Scientific Workflows in Cloud Computing

ABSTRACT

Cloud computing is a new computing paradigm which is gaining wide acceptance among scientific fraternity in the recent years. The services of cloud could be effectively used for running large-scale data and computation-intensive scientific workflow applications. Finding the optimal schedule for such workflows has been a major concern among the cloud users. In the present work, a novel approach of combining both optimization of the schedule along with the allocation of the virtual machines (VMs) based on security requirements is envisaged. This paper focuses on generating an optimized schedule for the complex workflow structures. The main objective of the schedule is to minimize the makespan of the schedule. In this paper, we design the scheduling heuristic based on the cost prediction matrix (CPM) for optimized cost calculation. The CPM will estimate the execution cost by considering the child’s child task also. This leads to a prophetic estimation on the available VMs. In addition to this, we have used a fuzzy-based decision model for deciding the selection of the VMs based on security constraints in the cloud. This fuzzy model is combined with the optimized cost calculation from CPM for each and every task of the workflow. The proposed secured cost prediction-based scheduling (SCPS) algorithm then schedules the task in the best possible VM, so that the makespan is minimized. Our results show that the newly developed SCPS algorithm yields efficient schedule compared to other existing scheduling models in spite of the inclusion of security constraints besides scheduling. Nevertheless, this secured scheduling is done without much increase in the time complexity.

KEYWORDS:

• Cloud computing
• Fuzzy model
• Workflow scheduling

ORCID

J. Angela Jennifa Sujana http://orcid.org/0000-0002-8161-1967

Additional information

Notes on contributors

J. Angela Jennifa Sujana

J Angela Jennifa Sujana is currently working with Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India. She has completed her BE and MTech with specialization in information technology and PhD in the area of cloud computing. Her research interest includes scheduling in cloud computing, distributed computing, and optimization with soft computing techniques. She is an EMC² certified Associate on Cloud Infrastructure and Services.

T. Revathi

T Revathi is currently working as Sr Professor in Department of Information Technology, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India. She has completed her PhD in the area of computer networks. She is an expert in the field of networks. She has guided many research works. Her research interest includes security in cloud computing, congestion control in networks. Email: [email protected]

S. Joshua Rajanayagam

S Joshua Rajanayagam has completed his engineering degree in Karunya University. Later he worked in TCS as Software Engineer. He completed his masters in the information technology discipline at Mepco Schlenk Engineering College. His areas of interest include cloud computing and data analytics. He is an expert in Hadoop and Java programming domain and has worked on many product developments. At present, he is working in Tata Consultancy Services as Senior Software Associate. Email: [email protected]