Raffaele Bolla

In order to fulfill the stringent requirements and fast advancements of 5G and beyond applications, it is inevitable to develop research/industrial testbeds to examine the different proposed innovative features of 5G and beyond. In this paper, we propose a testbed including 5G and beyond technologies by combining open-source solutions and our developed Network Services/Functions to enhance the ETSI-NFV MANO framework. Our testbed contains an automation framework to reduce both run time and setup complexity. It provides various services: Metal as a Service (MaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS), different Network Functions (NFs), and Network Services (NSs), under the context of full automation of End-to-End (E2E) NSs on top of the services provided by ETSI.

Today, the digital economy is pushing new business models, based on the creation of value chains for data processing, through the interconnection of processes, products, services, software, and things across different domains and organizations. Despite the growing availability of communication infrastructures, computing paradigms, and software architectures that already effectively support the implementation of distributed multi-domain value chains, a comprehensive architecture is still missing that effectively fulfills all related security issues: mutual trustworthiness of entities in partially unknown topologies, identification and mitigation of advanced multi-vector threats, identity management and access control, management and propagation of sensitive data. In order to fill this gap, this work proposes a new methodological approach to design and implement heterogeneous security services for distributed systems that combine together digital resources and components from multiple domains. The framework is designed to support both existing and new security services, and focuses on three novel aspects: (i) full automation of the processes that manage the whole system, i.e., threat detection, collection of information and reaction to attacks and system anomalies; (ii) dynamic adaptation of operations and security tasks to newest attack patterns, and (iii) real-time adjustment of the level of detail of inspection and monitoring processes. The overall architecture as well as the functions and relationships of its logical components are described in detail, presenting also a concrete use case as an example of application of the proposed framework.

Network Functions Virtualization (NFV) has recently gained much popularity in the research scene for the flexibility and programmability that it will bring with the software implementation of network functions on commercial off-the-shelf (COTS) hardware. To substantiate its roll out, a number of issues (e.g., COTS’ inherent performance and energy efficiency, virtualization overhead, etc.) must be addressed, in a scalable and sustainable manner. Numerous works in the scientific literature manifest the strong correlation of network key performance indicators (KPIs) with the burstiness of the traffic. This paper proposes a novel model-based analytics approach for profiling virtualized network function (VNF) workloads, towards real-time estimation of network KPIs (specifically, power and latency), based on an MX/G/1/SET queueing model that captures both the workload burstiness and system setup times (caused by interrupt coalescing and power management actions). Experimental results show good estimation accuracies for both VNF workload profiling and network KPI estimation, with respect to the input traffic and actual measurements, respectively. This demonstrates that the proposed approach can be a powerful tool for scalable and sustainable network/service management and orchestration.=-1.

Edge computing is an effective paradigm for proximity in computation, but must inexorably face mobility issues and traffic fluctuations. While software orchestration may provide effective service handover between different edge infrastructures, seamless operation with negligible service disruption necessarily requires pre-provisioning and the need to leave some network functions idle for most of the time, which eventually results in large energy waste and poor efficiency. Existing consolidation algorithms are largely ineffective in these conditions because they lack context, i.e., the knowledge of which resources are effectively used and which ones are just provisioned for other purposes (i.e., redundancy, resilience, scaling, migration). Though the concept is rather straightforward, its feasibility in real environments must be demonstrated. Motivated by the lack of energy-efficiency mechanisms in cloud management software, we have developed a set of extensions to OpenStack for power management and Quality of Service, explicitly targeting the introduction of more context for applications. In this paper, we briefly describe the overall architecture and evaluate its efficiency and effectiveness. We analyze performance metrics and their relationship with power consumption, hence extending the analysis to specific aspects that cannot be investigated by software simulations. We also show how the usage of context information can greatly improve the effectiveness of workload consolidation in terms of energy saving.

The papers in this special section focus on green communications, computing, and systems engineering. Computing technologies are used extensively in network systems, such as cloud computing and grid computing, and the Internet is the most well-known and widely used network infrastructure for computing. Networked software and hardware applications, especially wireless and mobile ones, have been made remarkable and fast increasing impacts on society development and human lives. They touch a great number of the human population in the world through ubiquitous mobile phones and devices. Computing and communications are indispensable components in many diverse systems. All these systems have energy issues. Their increasing spread, particularly with the emergence of the Internet of Things, is a great challenge to a world seeking to reduce its reliance on fossil fuels and address global climate changes. At the same time, although energy concerns are one of the dominant “green” topics, the green issues could be more generally defined as those making the world and the components of man-made systems both sustainable and friendly in an environmental, economic, social, and/or technical sense. In this sense, the word “green,” includes not only the sustainability objectives but also the “most positive and friendly” characteristics concerning human environments and societies.

The Network Functions Virtualization (NFV) paradigm is undoubtedly a key technological advancement in the Information and Communication Technology (ICT) community, especially for the upcoming 5G network design. While most of its promise is quite straightforward, the implied reduction of the power consumption/carbon footprint is still debatable, and not in line with the energy efficiency perspective forecasted by the ETSI NFV working group (WG). In this paper, we provide an estimate of the possible future requirements of this upcoming technology when deployed according to the virtual Evolved Packet Core (vEPC) use case specified by the ETSI NFV WG. Our estimation is based on real performance levels, certified by independent third-party laboratories, and datasheet values provided by existing commercial products for both the legacy and NFV network architectures, under different deployment scenarios. Obtained results show that a massive deployment of the current NFV technologies in the EPC may lead to a minimum increase of 106 % in the carbon footprint/energy consumption with respect to the Business As Usual (BAU) network solutions. Moreover, these values tend to increase at a very high pace when the most suitable software/hardware combination is not applied, or when packet processing latency is taken into account.

The idea of proxying network connectivity has been proposed as an efficient mechanism to maintain network presence on behalf of idle devices, so that they can "sleep". The concept has been around for many years; alternative architectural solutions have been proposed to implement it, which lead to different considerations about capability, effectiveness and energy efficiency. However, there is neither a clear understanding of the potential for energy saving nor a detailed performance comparison among the different proxy architectures. In this paper, we estimate the potential energy saving achievable by different architectural solutions for proxying network connectivity. Our work considers the tradeoff between the saving achievable by putting idle devices to sleep and the additional power consumption to run the proxy. Our analysis encompasses a broad range of alternatives, taking into consideration both implementations already available in the market and prototypes built for research purposes. We remark that the main value of our work is the estimation under realistic conditions, taking into consideration power measurements, usage profiles, and proxying capabilities.

Overcoming the typical ossification of the traditional TCP/IP-based Internet infrastructure will allow opening the way for more flexible and energy efficient paradigms, able to provide a sustainable support to the constantly increasing number of devices and services. To this goal, the INPUT Project will overcome current limitations by introducing computing and storage capabilities to edge network devices in order to allow users/telecom operators to create/manage private clouds "in the network". In addition, these new capabilities will allow replacing smart devices, such as network-attached storage servers, set-top-boxes, video sensors etc. with their virtual images. Although this virtualization process can clearly bring to a reduction of the emissions, along with the lowering of capital (CAPEX) and operational (OPEX) expenditures, on the other hand it requires more computational capacity at server level, which may erase the savings produced by virtualization in the absence of a thorough management and planning. In this respect, this paper presents a mathematical model that analyzes the impact of different levels of virtualization on the overall energy efficiency by thoroughly outlining how the carbon footprint varies depending on the virtualization level of a device.