An Adaptive Approach To Optimizing Qos Throughputs In Software Defined Networks
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An Adaptive Approach to Optimizing QoS Throughputs in Software-defined Networks
Maximizing bandwidth availability to critical science data flows is a key strategy in guaranteeing that current infrastructure can keep pace with the increasing demands of distributed science workflows across multiple facilities. Much of the research in this area has gone into developing parallel file transfer protocols such as GridFTP and leveraging circuit-based reservation systems like ESnets OSCARS. Software Defined Networks (SDN) is a recent development that presents a programmable approach to networking that moves routing logic out of the network fabric and abstracts the physical network behind a unified API. While SDN has gained significant traction in the data center, its potential is just beginning to garner attention in the scientific computing space and much investigation has yet to be done. In this study we examine an adaptive, priority-driven algorithm that leverages SDN capabilities to monitor flows, enforce per-application bandwidth guarantees and reallocate unutilized bandwidth between virtual circuits in real time. Trials were conducted on a simplified, six-switch topology with a single bottleneck link to demonstrate the correct behavior of the algorithm and compare it to competing traffic management techniques. We show that by intelligently adjusting throughput limits---effectively loaning out bandwidth from flows that are under-utilizing reserved bandwidth to flows that can make better use of the extra bandwidth---more optimal throughputs can be achieved for priority applications at a minimal cost to total bandwidth usage compared to such classic policing schemes as Differentiated Services queues.
Quality of Service (QoS) - Challenges and Solutions
Author: Yaseein Hussein
language: en
Publisher: BoD – Books on Demand
Release Date: 2025-01-08
Quality of Service (QoS) - Challenges and Solutions offers a comprehensive guide to understanding and advancing QoS in communication networks, essential for maintaining high performance and user satisfaction. It delves into the dynamic nature of QoS, exploring its significance across fields like telecommunications, computer networks, and new technologies, especially in the 5G era. This book covers foundational concepts, implementation strategies, practical applications, common challenges, and innovative solutions to enhance QoS, emphasizing adaptive approaches that respond to evolving network needs. It introduces readers to the latest developments, such as network slicing, edge computing, machine learning, and service orchestration, all crucial for future-ready communication systems. A significant focus of the book is the integration of QoS with 5G and beyond, highlighting methods like QoS-aware machine learning for resource optimization, dynamic resource allocation through predictive analytics, and traffic routing algorithms for real-time network improvements. It also addresses security as a core component of QoS, discussing virtualized and cloud-based infrastructures that bolster network resilience and performance. With these advanced strategies, the book provides insights into creating secure, high-performance networks that can handle increased traffic and complexity. The authors aim to equip researchers, practitioners, and students with a detailed QoS understanding, emphasising current and future innovations. By examining the impact of 5G, adaptive methodologies, and emerging technologies, the book positions itself as a crucial resource for those invested in the future of communication networks. In a digitally reliant world, mastering QoS is essential, and this guide presents a roadmap for navigating its complexities, ensuring top-tier network services, and enhancing user experiences across rapidly evolving digital landscapes. This book presents advanced QoS techniques applicable to various domains, including 5G networks, B5G networks, machine learning applications, QoS optimization, and network slicing.
Proceedings of the 14th International Conference on Computer Engineering and Networks
This conference proceedings is a collection of papers accepted for CENet2024 - the 14th International Conference on Computer Engineering and Networks, held in Kashi, China, 18-21 October 2024. The topics covered include Internet of Things and Smart Systems, Artificial Intelligence and Applications, Detection, Analysis and Application of Communication Systems, Cloud Computing and Security, and Medical Engineering and Information Systems. Each section of this book can serve as an excellent reference for industry practitioners, university faculty, research fellows, undergraduate and graduate students who wish to build a knowledge base of the latest advances and state-of-the-art practices in the topics covered. Using this knowledge, they will be able to design, implement and manage systems that are both complex and trustworthy. We would like to thank the authors for their hard work and dedication, and the reviewers for their efforts in ensuring that only the highest quality papers were selected. Without their contributions, the proceedings would not have been possible.