Management of Data Center Networks. Nadjib Aitsaadi
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In this context, the latest Capital Expenditure (CAPEX) of the five largest‐scale Internet operators, Apple, Google, Microsoft, Amazon, and Facebook, increased by
in 2016 in order to invest in designing their DCs. Over the past years, these companies have spent, in total, a capital of 115 $ billions, to build out their DCs. For instance, Google has invested millions of dollars in expanding its data centers spread all over the world: Taiwan, Latin America, Singapore, etc. Facebook has started, since 2010, building out its own DCs in Altoona, Iowa, and North Carolina. In this regard, efficiently designing data centers is a crucial task to ensure scalability required to meet today's massive workload of Cloud applications. Moreover, it is mandatory to deploy the proper mechanisms for routing and resource allocation to communication flows in DCs.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.
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