Resource Management in Distributed Systems [E-Book] / edited by Anwesha Mukherjee, Debashis De, Rajkumar Buyya.
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 The book presents a collection of original, unpublished, and high-quality research works, which report the latest research advances on resource discovery, allocation, scheduling, etc., in cloud, fog, and edge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 t...
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| Personal Name(s): | Buyya, Rajkumar, editor |
| De, Debashis, editor / Mukherjee, Anwesha, editor | |
| Edition: |
1st edition 2024. |
| Imprint: |
Singapore :
Springer,
2024
|
| Physical Description: |
XII, 314 pages 88 illustrations, 75 illustrations in color (online resource) |
| Note: |
englisch |
| ISBN: |
9789819726448 |
| DOI: |
10.1007/978-981-97-2644-8 |
| Series Title: |
Studies in Big Data ;
151 |
| Subject (LOC): |
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| 490 | |a Studies in Big Data ; |v 151 | ||
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| 505 | 0 | |a 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. | |
| 520 | |a 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 The book presents a collection of original, unpublished, and high-quality research works, which report the latest research advances on resource discovery, allocation, scheduling, etc., in cloud, fog, and edge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. | ||
| 650 | 0 | |a Cloud Computing. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Internet of things. | |
| 700 | 1 | |a Buyya, Rajkumar, |e editor | |
| 700 | 1 | |a De, Debashis, |e editor | |
| 700 | 1 | |a Mukherjee, Anwesha, |e editor | |
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