Chapter 1

Network Control Based on Smart Communication Paradigm

The increasing demand for customized and personalized services opened a new overall challenge to find scalable and sustainable solutions for the ever growing smart communications field, which supports different kinds of services, for a wide variety of future next-generation networks applications and cloud computing technologies. To address this challenge, new and cross-disciplinary approaches are required to optimize the distribution of media data which needs to explore how smart communications, built from user perception and feedback, affect protocols, global design, equipment, algorithms, paradigms, power consumption, etc., for a large family of applications using different network technologies. The key observation behind this chapter is that the addressed problem raises many interesting challenges when considered from a control theoretic perspective. First, the general framework is presented. Then, the main inter-disciplinary views are described in detail.

1.1. Motivation

The last two last decades of the 20th Century were driven by the emergence and evolution of the Internet and its use for human communications. There is no doubt that in the 21st Century, the concept of Internet of Things (IoT) and its applications will have a key role in the way we understand our society. The IoT describes the trend for environments, buildings, vehicles, clothing, portable devices and other objects to have a digital representation and the ability to sense, use or exchange information. IoT makes things more interesting by connecting real-world objects, places and people through the digital world. Small objects connected together as part of the IoT today are considered one of the main challenges and the business revolution for the coming years. A widespread use of such connected objects will influence people, societies and businesses. IoT will transform how we live in our cities, how we travel, how we manage our lives sustainably, how we age and how we engage with services and entertainment.

Over the years, the continuous technological evolution and the development of new applications and services have steered networking research toward new problems, which have emerged as the network evolves with new features towards what is usually referred to as the future internet, which has become one of the basic infrastructures that supports the world economy nowadays. In fact, there is a strong need to build a new network scenario, where networked computer devices are proliferating rapidly, supporting new types of services, usages and applications: from wireless sensor networks and new optical network technologies to cloud computing, high-end mobile devices supporting high-definition (HD) media, high-performance computers, peer-to-peer networks and various platforms and applications. This new network scenario is fueling research in the area of new network architectures that consider both the requirements and demands of key emerging applications and services, such as cloud computing and Internet video, and the currently deployed network infrastructures.

Conversely, media distribution over the networks is now growing at a pace that will very soon threaten to change networks to a degree at which the perceived quality will no longer be acceptable. Also, users are switching from operator-controlled IPTV services to uncontrolled over-the-top media applications. High-quality delivery platforms increase the user expectation of quality, equivalent to the quality of traditional broadcast distribution. Furthermore, live TV, for example during sports events, may have a large impact on the amount of traffic in small geographic areas. Various distribution formats, delivery platforms and methods for protecting material leads to many copies of the same material that must be produced and distributed in parallel. Transcoding of content to different formats requires a lot of energy for both calculation and cooling, which is at odds with modern standards of energy efficiency and long-term durability. Also, users become connected to the Internet through different devices (mobile, PCs, HD displays, etc.) and networks (3G/4G/UMTS, ADSL, VDSL, etc.). Devices and networks can vary a lot in their features and capabilities. Hence, each user has a specific context. This situation produces a very heterogeneous environment where an increasing demand for customized and personalized services exists.

Therefore, the overall challenge is to find scalable and sustainable solutions for the ever growing smart communications field, which supports different kinds of services, for a wide variety of future next-generation network applications and cloud computing technologies. To address this challenge, new and cross-disciplinary approaches are required to optimize the distribution of media data. One approach is to introduce and combine methods for more effective storage of the data close to the consumer and various types of peer-supported distribution mechanisms. Decisions on when and where data are temporarily stored should be based both on estimates of expected demand and the final consumer demands on perceived quality. Also, statistical methods for online estimation of consumer demands will be crucial. Many of these issues are complex and can, in the short term, hardly be solved by any single approach. We need to find solutions to deliver network services in the most efficient way to provide users with the best perception while taking into consideration scarce network resources.

We also need to explore how smart communications, built from user perception and feedback, affect protocols, global design, equipment, algorithms, paradigms, power consumption, etc., for a large family of applications (healthcare, subaquatic, vehicular, robotic, economics, etc.) using different network technologies (Sensor Networks, MANET, VANET, Ubiquitous, Virtualization, Data centers, etc.). Indeed, autonomous applications embedded in complex configurations and dynamic environments have experienced a rapid expansion from classical applications where different modular devices, actuators and sensors interact closely. This expansion has considerably impacted the control of a given system in a centralized manner. Current research trends propose new autonomic architecture schemes that manage and control future emerging networks: Sky of clouds, IoT, Smart Grids, Smart Cities, etc. In parallel, the evolution of Internet usage appeals for higher quality guarantees in order to support stringent services. In this context, for example, healthcare and wellness applications such as helping elderly people, assisting dependent people or habitat monitoring in a smart environment, constitute some of the potential scenarios of convergence between autonomous systems and smart network technologies. These applications, which are based on high-level commands, accomplish some specific tasks, reveal new challenges regarding mechanic design, portability, acceptability, power support and efficiency, control theory, etc. In addition to achieving portability and low-power systems, major challenges that substantially limit the efficiency of any autonomous system must be addressed. This new vision will highlight the overlapping of two domains, namely autonomous systems and smart network technologies, devoted to different applications and a large variety of domains.

1.2. General framework

Our vision of a new paradigm is to make interactions first-class objects from the perspective of the user, the application and the network components. This is achieved by analyzing the interaction between the user and the application with quality perception metrics that are used to fix the control/command chain in network components. The idea here is how to integrate these metrics into a control/command chain in order to construct a network system. The key idea is to design an adaptive loop for improving the service quality of a network system by taking into account the end-user feedback. In this model, the perception measurement module evaluates the user feedback and sends the result to the control module. The latter analyzes the received results, makes a decision and sends it to the command module that initiates the chosen action onto the network system. This loop model refers to an adaptive system based on the end-to-end user’s perception and results in smart communications between equipment.

The key observation behind this vision is that the addressed problem raises many interesting challenges when considered from a control theoretic perspective. The characteristics of multimedia contents and the network resources vary over time. There are propagation delays in networks and the quality of offered services is still difficult to evaluate. For example, multimedia contents are strongly linked to the observed rate distortion. In fact, techniques borrowed from control theory, ranging from stability and controllability techniques, can be applied to adaptive, predictive, or stochastic control in both centralized and distributed multimedia delivery architectures. Unexplored challenges in control techniques for efficient multimedia delivery will be emphasized.

The use of artificial intelligence tools together with biologically inspired techniques, to control network behavior in real time so as to provide users with the Quality-of-Service (QoS) that they request, and to improve network robustness and resilience, is necessary. The key idea is based on control theory and machine learning techniques in order to support smart communications driven from user’s perception to avoid any complete interruption in the whole chain of service treatment.

This is not the first attempt to get rid of the notion of technical control mechanisms in network...