Autonomic Computing in Cloud Resource Management in Industry 4.0

ISBN-13: 9783030717551 / Angielski / Twarda / 2021 / 411 str.

Tanupriya Choudhury; Bhupesh Kumar Dewangan; Ravi Tomar

Spis treści

Introduction.-  Introduction to Cloud Resource Management.- Autonomic Computing in Cloud.- Model, and Applications.- Issues and challenges in Autonomic computing and resource management.- The architecture of Autonomic Cloud Resource Management.- A self-adaptable framework to find best optimization techniques.- Healing application against resource failure.- Modelling re-installation components to adapt system configuration.- Self-protection application to defend the malicious request.- Resource management system for scheduling.- Comparative Analysis of various autonomic management systems in the cloud.- Applicability of Autonomic computing in resource management.- Conclusion.

O autorze

Dr. Tanupriya Choudhury received his bachelor’s degree in CSE from West Bengal University of Technology, Kolkata, India, and master’s Degree in CSE from Dr. M.G.R University, Chennai, India.He has received his PhD degree in the year 2016. He has Ten years experience in teaching as well as in Research. Currently he is working as an Associate Professor in dept. of CSE at UPES Dehradun. Recently he has received Global Outreach Education Award for Excellence in  best Young researcher Award in GOECA 2018  His areas of interests include Human computing,Soft computing,Cloud computing,Data Mining etc.He has filed 14 patents till date and received 16 copyrights from MHRD for his own softwares.He has been associated with many conferences in India and abroad.He has authored more than 85 research papers till date.He has delivered invited talk and guest lecture in Jamia Millia Islamia University  , Maharaja Agersen college of Delhi University , Duy Tan University  Vietnam etc.  He has been associated with many conferences throughout India as TPC member and session chair etc. He is a lifetime member of IETA, member of IEEE, and member of IET(UK) and other renowned technical societies. He is associated with Corporate and he is Technical Adviser of DeetyaSoft Pvt. Ltd. Noida , IVRGURU ,and Mydigital360 etc.He is holding the post of Secretary in IETA (Indian Engineering Teacher’s Association-India), He is also holding the Advisor Position in INDO-UK Confederation of Science, Technology and Research Ltd.,London, UK and International Association of Professional and Fellow Engineers-Delaware-USA.

 

Dr. Bhupesh Kumar Dewangan pursued Bachelor of Technology form Pt Ravi Shankar Shukla University (STATE UNIVERSITY), Raipur and Master of Technology from Chhattisgarh Swami Vivekananda Technical University (STATE TECHNICAL UNIVERSITY), Bhilai in computer science and engineering. Currently he is pursuing PhD in computer science and engineering and Assistant Professor, Department of Informatics, at University of Petroleum and Energy Studies. He has more than 40 research publications in various international journals and conferences with SCI/SCOPUS/UGC indexing. His research interests in Autonomic Cloud Computing, Resource Scheduling, Software Engineering, and Testing. He is a member of various organizations like ISTE, IAPFE, etc.

 

Dr. Ravi Tomar is currently working in the capacity of Assistant Professor (Selection Grade) in School of Computer Science at University of Petroleum & Energy Studies, Dehradun, India. He is an Experienced Academician with a demonstrated history of working in the higher education industry. Skilled in Programming, Computer Networking, Python, Oracle Database, C++, Core Java, J2EE, RPA and CorDApp. A true believer in hard work and an Indian by heart. His research interests include Wireless Sensor networks, Image Processing, Data Mining and Warehousing, Computer Networks and VANET.  He has authored more than 30 papers in different research areas, filled one patent and have authored 2 books. He has Delivered Trainings to corporates nationally and Internationally on RPA, Blockchain, CordaApp, J2EE and IoT to clients like Union Bank of Philippines, Ernst and Young, Deloitte. He is currently working on two consultancy projects on Irrigation and Book ATM. He has conducted International conferences in Paris and Kathmandu.

 

Dr.Bhupesh Kumar Singh is a Professor in “Faculty computing and software engineering” at the university of Arba Minch University, Arba Minch Ethiopia, He received his Ph.D. Degree in computer science for Birla Institute of Technology, Ranchi Mesra, India in 2013 for his dissertation on “Designing of Agent and Debugger for complex Sketch Recognition”. He also holds B.E in computer Engineering for Government college of engineering Tirunelveli, India in 1999. He is having a rich experience of teaching and research along with academic administration. He is also h He is member of the Association for the Association for the Advancement of Artificial Intelligence (AAAI) and board member for several university. Most of his research centres around sketch recognition and intelligent system (focusing on eye, body, and sketch motions), haptics, and human computer interaction. He guided number of students at Master and Doctorate level for their research. Dr.Bhupesh’s  publications on the subjects widely cited. He is dedicated to diversity. He focuses a significant amount of his efforts in improving the diversity of in computer science. 

Dr. Teoh Teik Toe is currently the Senior Lecturer in NBS, NTU. Prior to this, he is the Associate Director in SUTD and Fellow in SUTD Academy. He has more than 25 years of research experience including Big Data, Deep Learning, Cyber-security, Artificial Intelligence, Machine Learning and Software Development. He also has more than 15 years of teaching experience in AI, Data Science and Analytics, Statistic, Business, Finance, Accounting and Law. In addition, he has 14 years of experience as a listed company director (NTPM Berhad) including Audit Committee Member. He has obtained PhD in Computer Engineering from NTU, Doctor of Business Administration and MBA from University of Newcastle, Master of Law from NUS, LLB and LLM from UoL. He also holding professional certifications include CFA, ACCA, CIMA, Chartered Accountant Singapore, Chartered Accountant Malaysia and CPA Australia.

Dr. Nguyen Gia Nhu received the PhD degree in Mathematical for Computer Science from Ha Noi University of Science- Viet Nam National University, Vietnam. Currently, he is Dean of Graduate School- Duy Tan University, Viet Nam. He has a total academic teaching experience of 19 years with more than 60 publications in reputed international conferences, journals and online book chapter contributions (Indexed By: SCI, SCIE, SSCI, Scopus, ACM DL, DBLP). His area of research includes: Healthcare Informatics, Network Performance Analysis and Simulation, Computational Intelligence.Recently, he has been the Technical program committee, review committee, track chair for international conferences: FICTA 2014, ICICT 2015, INDIA 2015, IC3T 2015, INDIA 2016, FICTA 2016, IC3T 2016, IUKM 2016, INDIA 2017, FICTA 2017, FICTA 2018, INISCOM 2018, INISCOM 2019 under Springer-ASIC/LNAI Series.  6 Computer Science books published in Springer, IGI Global, CRC, Wiley Publication. Presently he is Associate Editor of the IGI-Global: International Journal of Synthetic Emotions (IJSE).

Blurb

This book describes the next generation of industry—Industry 4.0—and how it holds the promise of increased flexibility in manufacturing, along with automation, better quality, and improved productivity. The authors discuss how it thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. The authors posit that intelligent cloud services and resource sharing play an important role in Industry 4.0 anticipated Fourth Industrial Revolution. This book serves the different issues and challenges in cloud resource management CRM techniques with proper propped solution for IT organizations. The book features chapters based on the characteristics of autonomic computing with its applicability in CRM.  Each chapter features the techniques and analysis of each mechanism to make better resource management in cloud.

• Describes self-adaptable framework to find the best optimization techniques automatically based on issues and platforms;
• Presents a self-optimized model to find the optimal resource from the resource pool;
• Includes applications to diagnose and heal the system failure, and protect from malicious attacks.