Könyv QoS-Aware Virtual Network Embedding Peiying Zhang

QoS-Aware Virtual Network Embedding

Szerző: Peiying Zhang
Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
57 894 Ft
As an important future network architecture, virtual network architecture has received extensive att...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2021
oldal
412
EAN
9789811652202
ISBN
9811652201
Enbook ID
36653904
Súly
781
Méretek
160 x 241 x 28

Teljes leírás

As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet.At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources.In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.

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