December 2025
Intermediate to advanced
656 pages
16h 47m
English
Content preview from Edge Artificial Intelligence
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5Network Optimization in Edge Computing
Gargee Thakur1, Vaibhav Singh1, Riddhima Ghule1, Anish Dey1, Preeti Agarwal1* and Anchit Bijalwan2
1School of Technology Management & Engineering, Narsee Monjee Institute of Management Studies (Deemed to-be University), Navi, Mumbai, Maharastra, India
2School of Computing and Innovative Technologies, British University Vietnam, Hanoi, Vietnam
Abstract
Edge computing has emerged as a transformative model, bringing computation and storage closer to data sources to enhance performance, reduce latency, and optimize network efficiency. This paper delves into the critical role of edge computing in network optimization, addressing strategies such as edge caching, advanced routing techniques, software-defined networking, and network function virtualization. By employing these methods, edge computing reduces bandwidth consumption, improves real-time data processing, and supports scalable and secure frameworks for diverse applications, including IoT, autonomous systems, and smart cities. However, challenges such as programmability, data abstraction, and privacy are highlighted, requiring innovative solutions for sustainable implementation. Future trends, including integration with 5G networks, edge AI, and federated learning, promise to revolutionize network optimization further, enabling dynamic, resilient, and efficient systems for the next generation of applications. This study provides a comprehensive overview of the current advancements, ...
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