Prosper Chemouil

Mission critical solutions are essential for providing communications and services in the case of the troubles with connectivity that are often found in infrastructure-based solutions. Such solutions are typically used in the case of disasters, lack of energy, etc. There exist several narrowband solutions that provide countrywide coverage in certain countries. In recent years, the activities related to creating mission-critical broadband solutions based on Long Term Evolution (LTE) have led to the definition of LTE Mission Critical (LTE-MC). Both solutions ignore virtualization and require dedicated mobile terminals as a part of the mission-critical communication solution. This paper describes the opportunities, open issues and a proposal of a solution that exploits Unmanned Aerial Vehicles (UAVs) and network virtualization for mission-critical services. The presented approach combines Cloud/Edge and Fog orchestration to efficiently use all the available resources, including virtualized resources of the end-user devices.

The term “SDN” represents a significant evolution in networking technology and draws attention and support from network operators, vendors, researchers and industry regulators. Contrary to popular belief that SDN is a recent invention, or is related only to IP technologies, the concept of network programmability and control/data plane separation has its roots in the 1960s and 1970s when the telephone network started its transition to digital. Many iterations followed, leading to applications in packet networks and today’s Internet. In this article, we review a number of early works on network programmability that illustrate how several features of SDN emerged progressively over several decades. Our review starts from the early concepts of network control in the telephone network and continues to examine a prolific period of research advancements in the 1990s and early 2000s that led to a number of startup companies that followed, IEEE’s own efforts in standardizing network programmability, and finally the arrival of the OpenFlow standard. We study the importance of this architectural transformation and its influences on modern cloud computing and next-generation networking.

Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged in the networking domain with great expectation. They can be broadly divided into AI/ML techniques for network engineering and management, network designs for AI/ML applications, and system concepts. AI/ML techniques for networking and management improve the way we address networking. They support efficient, rapid, and trustworthy engineering, operations, and management. As such, they meet the current interest in softwarization and network programmability that fuels the need for improved network automation in agile infrastructures, including edge and fog environments. Network design and optimization for AI/ML applications addresses the complementary topic of supporting AI/ML-based systems through novel networking techniques, including new architectures and algorithms. The third topic area is system implementation and open-source software development.

Research in large-scale networking systems has been shaped and will continue to be guided by specific characteristics of applications and the underlying platforms and infrastructures. On the one hand, applications are growing at an accelerated pace, which is fundamentally unpredictable in both breadth and depth. On the other hand, the underlying networking has been the focus of a huge transformation enabled by new models resulting from virtualization and cloud computing. This has led to a number of novel architectures supported by emerging technologies such as Software-Defined Networking (SDN), Network Function Virtualization (NFV), and more recently, edge cloud and fog networking, or network slicing [1] , [2] . This evolution towards enhanced design opportunities along with increasing complexity in networking and its applications has fueled the need for improved network automation in agile infrastructures. At the same time, their complexity has dramatically increased. The networking dynamics have had the effect of making it even more important and challenging to design scalable network measurement and analysis techniques and associated tools. Critical applications such as resource allocation, network monitoring, security enforcement, or dynamic network management require real-time mechanisms for online analysis as well as efficient techniques for offline deep analysis of massive historical data.

There is currently a strong interest in both industry and academia in the softwarization of telecommunication networks and cloud computing infrastructures. This evolution is enabled by three paradigms. First, Software-Defined Networking (SDN) allows network control to be separated from the forwarding plane and allows for a flexible management of the network resources. Second, Network Virtualization (NV) brings virtualization concepts to the network, similar to cloud computing, which was enabled by virtualization of servers. Third, Network Function Virtualization (NFV) focuses on virtualization of software-based network functions. Instead of installing and managing dedicated hardware devices for these functions, they are implemented as software components and deployed on commodity hardware infrastructures, in most cases operated by a network operator or cloud infrastructure provider. Service Function Chaining (SFC) consists of building services using virtual network functions (VNFs). These three paradigms are synergetic and reinforce each other when used together. Several initial SDN, NV and NFV deployments are already operational in providers’ networks.

In Part I of the special issue, the main reported research contributions were: efficient resource allocation and management of softwarized network functions, design of highperformance platforms to allow network function virtualization on commodity machines, and enabling efficient collaboration between providers in softwarized networks. From the twenty six submitted papers, four papers had been selected for Part I of the special issue. An additional set of four more papers have been accepted for this Part II, after a thorough revision by the authors to take into account the detailed comments from the reviewers. The four selected papers in Part II of the special address three very important topics for the efficient management of Software-Defined Networking/Virtualized Network Functions-based (SDN/NFV-based) telecommunication systems: (i) optimizations to flow-based software-defined networks to address the scalability and energy consolidation requirements, (ii) programming abstractions in wireless software-defined networks, and (iii) improved network virtualization to more efficiently support latency sensitive applications.

Information-centric networking (ICN) has received significant attention in recent years, mainly driven by the fact that distributing and manipulating information has become the major function of the Internet today. Unlike the traditional host-centric networking paradigm where information is obtained by contacting specified named hosts, ICN is aimed at providing native network primitives for efficient information retrieval by directly naming and operating on information objects. Foreseeing the need and benefits of developing the future Internet with ICN concepts as a key ingredient, many leading research groups, both industrial and academic, have created a sizable community devoting their efforts to information- centric future Internet designs and prototype implementations.