A New Adaptive Fault Tolerant Framework in the Cloud

Abstract

The of robustness in cloud computing is becoming mainstream due to unprecedented growth in the cloud. In order to enhance cloud service reliability, various fault tolerance techniques have been suggested in the literature. Many cloud service reliability and availability issues are arising due to the failure of virtual machines (VMs). Therefore, this study contributes a new Threshold-Based Adaptive Fault Tolerance (TBAFT) approach in the cloud by amalgamating proactive and reactive approaches. Furthermore, in this paper, VM migration and replication are being utilized in the proactive approach, whereas retry is used as a reactive approach. Additionally, experimental validation is performed by comparing three benchmark fault tolerance approaches by incorporating the first fit and least full host selection policies. The obtained experimental results of the proposed approach are presented in terms of different metrics such as failure rate, throughput, migration, and execution time using CloudSim simulator.

Keywords:

• Adaptive
• CloudSim
• Fault tolerance
• Migration
• Replication
• Retry
• VM failure

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Ajay Rawat

Ajay Rawat has over 16 years of experience in academics and industry in India and abroad. He is an official instructor of Google and Confluent. He received an MS degree from BITS Pilani, India, and presently he is pursuing PhD from the Department of Computer Science and Engineering, Uttarakhand Technical University, Uttarakhand, India. Also, currently, he is working in the capacity of assistant professor(SG) with the School of Computer Science, UPES, Uttarakhand, India. He had worked with the Department of Computer Science, Graphic Era University, Uttarakhand, India, as assistant professor. He is also having industry experience as software engineer in NIIT Technologies, New Delhi, India. His area of interest includes cloud computing, fault tolerance, big data. He has acquired various international certifications such as Google Professional Data Engineer, Google Professional Architecct, Confluent Developer, Confluent Operation, Databricks Apache Spark, RedHat OpenStack. He has published various papers in national and international journals. He conducted many training sessions in Google Singapore and other countries.

Rama Sushil

Rama Sushil is currently working as a professor in the Department of Information Technology, School of Computing, DIT University, Uttarakhand, India. She has received PhD from IIT, Roorkee, and has total teaching and research experience for more than 20 years. She published many research papers in SCI/ESCI/Scopus/ peer-reviewed reputed journals. She has authored chapters also in the book of IGI Global and books of Indian publications. Her research interests include algorithms, cloud computing, WSN, machine learning, deep learning, and image processing. Email: [email protected]

Amit Agarwal

Amit Agarwal is currently working as director at Dr A P J Abdul Kalam Government Institute of Technology, Tanakpur, Uttarakhand, India. He received PhD (CSE) from IIT Roorkee. He is having more than 20 Years of academic, administrative, and research experience from reputed organizations. He has published more than 80 research articles indexed in SCI, Scopus, IEEE Xplore, and Springer. Email: [email protected]

Afzal Sikander

Afzal Sikander is working as an assistant professor with the Department of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, Punjab, India. Dr Sikander has over 10 years of teaching and research experience in the diverse field of control engineering. He is serving as Editorial board member and guest editor of numerous reputed journals. His areas of interest include control theory and applications, circuit design, model order reduction, optimization, robotics and renewable energy. He is actively involved in various research projects funded by CSIR, ISRO, and MHRD, etc. He has guided 8 MTech students whereas guidance to 2 PhD research scholars, 1 JRF and 1 MTech student is undergoing. He has published 65 research articles in reputed national and international journals and conferences. Email: [email protected]

Robin Singh Bhadoria

Robin Singh Bhadoria is currently working as an associate professor with the Department of Computer Science and Engineering, Birla Institute of Applied Sciences, Bhimtal, Uttarakhand, India. He earned his PhD degree from IIT Indore, Madhya Pradesh, India with a specialization in service oriented architecture and wireless sensor network in the January 2018. Dr Bhadoria has more than 10 years of teaching and research experience. He has published more than 75 research articles in reputed national and international journals and conferences which includes book chapters. He has edited more than 6 books on big data, internet of things, enterprise service bus, biometric computing and wireless networks with publishers like CRC Press (Taylor & Francis), Springer and IGI Global Inc (USA). Email: [email protected]