Resource Management in Distributed Systems

Herausgegeben:Mukherjee, Anwesha; De, Debashis; Buyya, Rajkumar

• Gebundenes Buch

Produktbeschreibung

This book focuses on resource management in distributed computing systems. The book presents a collection of original, unpublished, and high-quality research works, which report the latest research advances on resource discovery, allocation, scheduling, etc., in cloud, fog, and edge computing. The topics covered in the book are resource management in cloud computing/edge computing/fog computing/dew computing, resource management in Internet of things, resource allocation, scheduling, monitoring, and orchestration in distributed computing systems, resource management in 5G network and beyond, latency-aware resource management, energy-efficient resource management, interoperability and portability, security and privacy in resource management, reliable resource management, trustworthiness in resource management, fault tolerance in resource management, and simulation related to resource management.

Produktdetails

• Studies in Big Data 151
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-97-2643-1
• 2024
• Seitenzahl: 328
• Erscheinungstermin: 1. Juni 2024
• Englisch
• Abmessung: 241mm x 160mm x 23mm
• Gewicht: 661g
• ISBN-13: 9789819726431
• ISBN-10: 9819726433
• Artikelnr.: 70210099

Autorenporträt

Anwesha Mukherjee received B.Tech. in Information Technology from Kalyani Govt. Engineering College in 2009. She received M.Tech. in Information Technology from the West Bengal University of Technology in 2011. She stood first class first in M. Tech., and received Inspire Fellowship from the Department of Science & Technology, Govt. of India to pursue her Ph.D. She received Ph.D. in Computer Science and Engineering from the West Bengal University of Technology in 2018. She worked as a Research Associate in the Department of Computer Science and Engineering, IIT Kharagpur. She is currently working as an Assistant Professor in the Department of Computer Science at Mahishadal Raj College, West Bengal, India. She has published more than 75 research papers in International journals, conference proceedings, book chapters, etc., and two edited books. Her research areas include Internet of Things (IoT), fog computing, mobile network, geospatial informatics, and cloud computing.  Debashis De is a Professor in the Department of Computer Science and Engineering at the Maulana Abul Kalam Azad University of Technology, West Bengal, India. He received M.Tech from the University of Calcutta, in 2002 and a Ph.D. from Jadavpur University in 2005. He is a Senior Member-IEEE, Fellow IETE, and Life member CSI. He was awarded the prestigious Boyscast Fellowship by the Department of Science and Technology, Government of India, to work at the Heriot-Watt University, Scotland, UK. He received the Endeavour Fellowship Award from 2008-2009 by DEST Australia to work at the University of Western Australia. He received the Young Scientist award in 2005 at New Delhi and in 2011 in Istanbul, Turkey, from the International Union of Radio Science, Belgium. In 2016 he received the JC Bose research award from IETE, New Delhi. In 2019 he received the Shiksha-Ratna Award from the Govt. of West Bengal. He established the Center of Mobile Cloud Computing (CMCC) for IoT applications. He published in 390 journals and 200 conference papers, Fifteen books, and filed 10 patents and 4 granted. He has projects sponsored by AICTE, UGC, WBDST, DST, WBDST, World Bank, AWS, and MeitY. His h index is 43, the citation is 8700. He supervised 20 Ph.D. students. His research interest is Mobile Cloud Computing, AI, IoT, and Quantum Computing. Rajkumar Buyya is Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He is also serving as the founding CEO of Manjrasoft, a spin-off company of the University, commercializing its innovations in Cloud Computing. He served as Future Fellow of the Australian Research Council during 2012-2016. He has authored over 625 publications and seven textbooks including "Mastering Cloud Computing" published by McGraw Hill, China Machine Press, and Morgan Kaufmann for Indian, Chinese, and international markets, respectively. He also edited several books including "Cloud Computing: Principles and Paradigms" (Wiley Press, USA, Feb 2011).  He is one of the highly cited authors in computer science and software engineering worldwide (h-index=166, g-index=360, 160,000+ citations).   

Inhaltsangabe

Resource Management in Distributed Computing.- Cloud Computing Resource Management.- Resource Allocation and Placement in Multi-access Edge Computing.- Resource Scheduling in Integrated IoT and Fog Computing Environments: A Taxonomy, Survey and Future Directions.- Trusted task offloading and resource allocation strategy in MEC environment.- Resource Management in Edge Clouds: Latency-aware Approaches for Big Data Analysis.- FSRmSTS - An Optimized Task Scheduling with a Hybrid Approach: Integrating FCFS, SJF, and RR with Median Standard Time Slice.- Container Orchestration in Heterogeneous Edge Computing Environments.- Resource targeted cybersecurity attacks in cloud computing environments.- Load balancing using Swarm intelligence in cloud Environment.- Interoperability and Portability in Big Data Analysis based Cloud-Fog-Edge-Dew Computing.- Cyber attack victim separation: new dimensions to minimize attack effects by resource management.- eBPF and XDP Technologies as Enablers for Ultra-Fast and Programmable Next-Gen Network Infrastructures.- Deep Reinforcement Learning (DRL)-based Methods for Serverless Stream Processing Engines: A Vision, Architectural Elements, and Future Directions.

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Resource Management in Distributed Computing.- Cloud Computing Resource Management.- Resource Allocation and Placement in Multi-access Edge Computing.- Resource Scheduling in Integrated IoT and Fog Computing Environments: A Taxonomy, Survey and Future Directions.- Trusted task offloading and resource allocation strategy in MEC environment.- Resource Management in Edge Clouds: Latency-aware Approaches for Big Data Analysis.- FSRmSTS – An Optimized Task Scheduling with a Hybrid Approach: Integrating FCFS, SJF, and RR with Median Standard Time Slice.- Container Orchestration in Heterogeneous Edge Computing Environments.- Resource targeted cybersecurity attacks in cloud computing environments.- Load balancing using Swarm intelligence in cloud Environment.- Interoperability and Portability in Big Data Analysis based Cloud-Fog-Edge-Dew Computing.- Cyber attack victim separation: new dimensions to minimize attack effects by resource management.- eBPF and XDP Technologies as Enablers for Ultra-Fast and Programmable Next-Gen Network Infrastructures.- Deep Reinforcement Learning (DRL)-based Methods for Serverless Stream Processing Engines: A Vision, Architectural Elements, and Future Directions.