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      Figure 1.1. Virtualization of three routers. For a color version of the figure, see www.iste.co.uk/pujolle/software2.zip

      Energy consumption is another argument in favor of virtualization. While, to begin with, consumption would rise because we are adding an extra piece of software (the hypervisor or container), it is possible to share the resources more effectively, and move those resources, grouping them together on physical machines, and put other machines, which have become idle, on standby.

      A physical machine can accommodate virtual machines if, as mentioned above, we add a hypervisor or a container manager, which is a software program that enables multiple containers, hence multiple virtual machines, to run simultaneously. In fact, the word “simultaneously” implies a macroscopic scale: on a microscopic scale, the virtual machines are executed sequentially one after another. In the context of virtual servers, this serial execution is not a problem. In the area of networks, it may become a problem for real-time applications, which require a very short response time. Each virtual machine’s processing time must be sufficiently short to give the impression that all the virtual machines are being executed in parallel. Figure 1.2 shows the architecture of virtualization.

      Figure 1.2. A virtualized machine. For a color version of the figure, see www.iste.co.uk/pujolle/software2.zip

      In this section, we will go over the two solutions to obtain virtual machines, as shown in Figure 1.2. The hypervisor is a virtual machine monitor (VMM), which is often open source. Hypervisors operate on standard hardware platforms. In addition to the VMM, running directly on the physical hardware, the architecture generally comprises a number of domains running simultaneously. These domains execute virtual machines isolated from one another. Each virtual machine may have its own operating system and applications. The VMM controls access to the hardware from the various domains, and manages the sharing of the resources between the different domains. Thus, one of the VMM’s main tasks is to isolate the different virtual machines, so that the execution of one virtual machine does not affect the performances of the others.

      All peripheral drivers are kept in an isolated domain specific to them. Known as “domain zero” (dom0), it offers a reliable and effective physical support. Dom0 has special privileges in comparison to other domains, known as “user domains” (domU) and, for example, has unfettered access to the hardware of the physical machine. User domains have virtual drivers and operate as though they have direct access to the hardware. However, in reality, those virtual drivers communicate with the dom0 in order to access the physical hardware.

      The hypervisor virtualizes a single physical network interface, de-multiplexing the incoming packets from the physical interface to the user domains and, conversely, multiplexing the outgoing packets generated by those user domains. In this procedure, known as virtualization of the network input/output, the domain 0 directly accesses the input/output peripherals, using their native drivers, and performs input/output operations on behalf of the domUs.

      We will go back to hypervision techniques later in this chapter. Before this, let us introduce the second solution to support virtual machines, which seems to take the lead thanks to its simplicity and efficiency while offering a little less functionality. This solution is based on a unique operating system supporting containers that host the virtual machines. More precisely, a container is an abstract data structure, class or type that makes it possible to collect objects. The container technique is more flexible and simpler than that embedding an operating system for each virtual machine. Containers can migrate from one hardware to another, thus performing virtual machine migrations. The open source software called Kubernetes, which we will study later in this chapter, makes it possible to orchestrate migrations from one hardware’s containers to another hardware in the same cluster. The Kubernetes orchestrator seems to become standard to implement virtual machines in the new generation of networks.

      Virtual machines, in turn, can be used to create virtual networks, which are also known as software networks. For this purpose, we need to link virtual machines together in the same way as we would connect different physical machines. Of course, the communication links must be shared between the different software networks. A set of software networks are represented in Figure 1.3.

      Figure 1.3. A set of software networks. For a color version of the figure, see www.iste.co.uk/pujolle/software2.zip

      Each software network may have its own architecture and its own characteristics. One software network could be devoted to a VoIP service, another to an IPTV service, a third to a highly secure application, a fourth to support professional applications, a fifth for asynchronous applications such as electronic messaging, etc. We could, in fact, practically create a software network for each user. The personalized software network is set up at the moment when the user connects. It is eliminated when the user signs out. However, this solution does not scale up, and today, we are limited to a number of software networks suited to the hardware capacity of the underlying physical infrastructure. Each software network receives resources allocated to it on the basis of the user demands. However, resources remain shared by different techniques that allow virtual networks to recover resources from other unused virtual networks.

      It should be noted that, in general, the virtual nodes are found in datacenters, which may be of varying size and importance: enormous central datacenters, regional datacenters, local datacenters and small datacenters such as femto-datacenters. We will come back later on to the choices which may be made in this field.

      One of the characteristics of software networks is that the virtual machines can be migrated from one physical machine to another. This migration may be automated based on whether a node is overloaded or out of order.

      Isolation is, of course, a crucial property, because it is essential to prevent a problem on one software network from having repercussions for the other networks. The handover of streams from one software network to another must take place via a secure

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