.

Introduction

      Thanks to the advent of the long‐awaited fifth‐generation (5G) mobile networks, mobile data and online services are becoming widely accessible. Discussions of this new standard have taken place in both industry and academia to design this emerging architecture. The main near future objective is to ensure the capability to respond to the different applications needs such as videos, games, web searching, etc., while ensuring a higher data rate and an enhanced Quality of Service (QoS). While no official standardization is yet delivered for 5G, experts assure that, the impressive proliferation of smart devices will lead to the explosion of traffic demand. Billions of connected users are expected to deploy a myriad of applications.

      In this respect, recent statistics elaborated by CISCO Visual Networking Index (VNI) highlight that the annual global IP traffic will roughly triple over the next 5 years and will reach 2.3 zettabytes by 2020. More specifically, it is expected that smart phones traffic will impressively increase from

      To cope with this unprecedented traffic explosion, the service providers are urged to rethink their network architectures. In fact, efficient scalable physical infrastructures, e.g., Data Centers (DCs), are required to support the drastically increasing number of both online services and users.

      To manage their DCs infrastructure, many of giant service tenants are resorting to virtualization technologies making use of Software Defined Networking (SDN) and Network Functions Virtualization (NFV).

On the one hand, SDN controllers offer the opportunity to implement more powerful algorithms thanks to a real‐time centralized control leveraging an accurate view of the network. Indeed, thanks to the separation of the forwarding and the control planes, the managements' complexity of the network infrastructure is considerably reduced while providing tremendous computational power compared to legacy devices. On the other hand, thanks to NFV paradigm, network functions and communication services are first softwarized and then cloudified, so that they can be on demand orchestrated and managed as cloud‐native IT applications. It is straightforward to see that these approaches are complimentary. They offer a new way to design and manage data centers while guaranteeing a high level of flexibility and scalability. The new emerging SDN and NFV technologies requires scalable infrastructures. To that end, a great deal of efforts have been devoted to the design of efficient DC architectures. Indeed, Internet giants ramped up their investment in data centers/IT infrastructures and poured in billions of dollars to widen their global presence and improve their competitiveness in the Cloud market.

      In this context, the latest Capital Expenditure (CAPEX) of the five largest‐scale Internet operators, Apple, Google, Microsoft, Amazon, and Facebook, increased by

To deal with these challenges, we investigate, in this book, a radically new methodology changing the design of traditional Data Center Network (DCN) while ensuring scalability and enhancing performance. First, in Chapter 1, we will overview the Data Center network architecture. Then, in Chapter 2, we will summarize the main related DC networks routing strategies at layer‐2, layer‐3, and up layers. Besides, an overview of Traffic Engineering (TE) techniques from link‐state while considering TCP fairness models. Next, in Chapter 3, we will overview the related work addressing intra‐data center resource allocation and routing in both wired and/or wireless (i.e., hybrid) data center networks. Afterwards, in Chapter 4, we will summarize the main reliable virtual network embedding strategies connecting geographically distributed data centers. Thanks to network function virtualization, CAPEX and OPEX are deeply reduced while ensuring the requested quality of service is more complex. Finally, in Chapter 5, we will provide a methodology to evaluate the energy cost reduction in DC brought by proactive management, while keeping a high level of user satisfaction.