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The proliferation of the ever-increasing number of highly heterogeneous smart devices and the emerging of a wide range of diverse applications in 5G mobile network ecosystems impose to tackle new set of raising challenges related to agile and automated service orchestration and management. Fully leveraging key enablers technologies such as software defined network, network function virtualization and machine learning capabilities in such environment is of paramount importance to address service function chaining (SFC) orchestration issues according to user requirements and network constraints. To meet these challenges, we propose in this paper a deep reinforcement learning (DRL) approach to investigate online quality of experience (QoE)/quality of service (QoS) aware SFC orchestration problem. The objective is to fulfill intelligent, elastic and automated virtual network functions deployment optimizing QoE while respecting QoS constraints. We implement DRL approach through Double Deep-Q-Network algorithm. We investigate experimental simulations to apprehend agent behavior along a learning phase followed by a testing and evaluation phase for two physical substrate network scales. The testing phase is defined as the last 100 runs of the learning phase where agent reaches on average QoE threshold score ( Q o E T h - S c ). In a first set of experiments, we highlight the impact of hyper-parameters (Learning Rate (LR) and Batch Size (BS)) tuning on better solving sequential decision problem related to SFC orchestration for a given Q o E T h - S c . This investigation leads us to choose the more suitable pair (LR, BS) enabling acceptable learning quality. In a second set of experiments we examine DRL agent capacity to enhance learning quality while meeting performance-convergence compromise. This is achieved by progressively increasing Q o E T h - S c . [ABSTRACT FROM AUTHOR]

5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via satellite to IoT cellular devices. Technological motivation tends to increase the satellites day by day for supporting most of global applications. These applications highly relay on satellite data for processing users request and giving appropriate outcome to the users. World grows very fastly with new technologies which makes demand for fastest data communication. Handling the satellite IoT data is worthiest research problem and it must be paid with more attention. At present inter satellite communication face high delay with lower data utilization rate. The effective utilization of data generated by satellite IoT is processed using our proposed intelligent model called smart edge computing (SEC-5G) for 5G. The SEC-5G embeds with satellite for reducing the data transfer limitation and delay in inter satellite communication. In this research we highly concentrate on satellite IoT data and its problem. Our proposed system reduces the limitation in inter satellite data communication rate which makes higher delay in data processing and utilization. In this article, smart edge computing is designed for satellite IoT using SDN/NFV and deep convolutional neural network (DCNN) with logical ring construction. The task uses SDN/NFV model to choose edge node, cloud node in the smart edge computing. Based on training data, DCNN works on SEC-5G software model. Smart architecture helps to increase the performance, scalability, reliability of satellite edge computing model. This architecture works with machine learning model and helps to improve the future satellite speed on data processing. The performance of the proposed is compared with existing Ground 5G. Evaluated outcome shows proposed embedded satellite outperforms in data communication. [ABSTRACT FROM AUTHOR]

Software Defined Network (SDN) and Network Function Virtualization (NFV) are bringing many advantages to optimize and automatize security management at the network edge, enabling the deployment of virtual network security functions (VSFs) in MEC nodes, to strengthen the end-to-end security in IoT environments. The benefits could exploit in mobile MEC nodes on-boarded in Unmanned Aerial Vehicles (UAV), as the UAVs would carry on-demand VSFs to particular physical locations. To that aim, this paper proposes a novel NFV/SDN-based zero-touch security management framework for automatic orchestration, configuration and deployment of lightweight VSF in MEC-UAVs, that considers diverse contextual factors, related to both physical and virtual conditions, to optimize the security orchestration. Our solution aims to deploy on-demand VSFs, such as virtual Firewalls (vFirewalls), vProxies, vIDS (Intrusion Detection Systems) and vAAA, to assist during emerging situations in particular physical locations, protecting and optimizing the managed IoT network, as well as replacing or supporting compromised physical devices like IoT gateways. The proposed solution has been implemented, deployed and evaluated in a real testbed with real drones, showing its feasibility and performance.

Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and intra-datacentre (DC) network and computational resources into a single converged 5G network infrastructure. The present paper overviews the main achievements obtained in the ALLIANCE project. This project ambitiously aims at architecting a converged 5G-enabled network infrastructure satisfying those needs to effectively realise the envisioned upcoming Digital Society. In particular, we present two networking solutions for 5G and beyond 5G (B5G), such as Software Defined Networking/Network Function Virtualisation (SDN/NFV) on top of an ultra-high-capacity spatially and spectrally flexible all-optical network infrastructure, and the clean-slate Recursive Inter-Network Architecture (RINA) over packet networks, including access, metro, core and DC segments. The common umbrella of all these solutions is the Knowledge-Defined Networking (KDN)-based orchestration layer which, by implementing Artificial Intelligence (AI) techniques, enables an optimal end-to-end service provisioning. Finally, the cross-layer manager of the ALLIANCE architecture includes two novel elements, namely the monitoring element providing network and user data in real time to the KDN, and the blockchain-based trust element in charge of exchanging reliable and confident information with external domains. [ABSTRACT FROM AUTHOR]

Software defined networking (SDN) and network function virtualization (NFV) as new technologies have shown great potential in improving the flexibility of resource management for network service provisioning. As traffic dynamics may cause violation of rigid service requirements, especially for ultra-reliability and low-latency communication (URLLC) service, it is essential yet challenging to dynamically allocate an appropriate amount of resources (including computation, transmission, and energy) to network functions (NFs) in softwarization-based networks. Meanwhile, with the explosion of high resource-demanding applications, the energy efficiency of communication networks deserves significant attention. In this paper, we investigate the dynamic network function resource allocation (NFRA) problem with aim to minimize long-term energy consumption while guaranteeing the requirements of URLLC services in softwarization-based networks. To cater for efficient on-line NFRA decisions, we design a distributed dynamic NF resource allocation (DDRA) algorithm based on dynamic value iteration (DVI). The convergence of the DDRA algorithm is proved. We conduct simulation experiments based on real-world data traces for performance evaluation. The numerical results demonstrate that the proposed DDRA algorithm achieves around 25% and 20% energy consumption reduction when compared with two benchmark algorithms, respectively. [ABSTRACT FROM AUTHOR]

Evolving the legacy network to SDN/NFV network is the strategy of carrier network re-architecture.Based on large-scale cases,multi-tier data centers architecture,application-driven telecom cloud infrastructure,vBRAS pool and C-U separation solutions were proposed.Session-consumed services and IPTV are the first several services that can be implemented by the new solution in MAN.And in those usecases,the carriers’ operators really combine the IT and CT operation teams into one virtual team,and push the evolution gradually.

The hardware acceleration mechanism for VNF (virtual network function) is recently a hot research topic in SDN/NFV architecture because of the low processing performance of VNF.Once hardware acceleration resources have been plugged into the network,how to optimally mange and orchestrate these resources under service requirements remains a question to be solved.Firstly,a unified management architecture based on separated control for hardware acceleration resources was proposed.Then,traditional network topology together with hardware acceleration resources were modeled into a unified network model and then the hardware acceleration resource orchestration problem was transferred into a multi-objective linear programming problem.Finally,a hardware-accelerator-card-prior’ heuristic algorithm was designed.Experimental results show that compared with existing methods,the proposed orchestration mechanism can efficiently manage hardware acceleration resources and reduce the processing latency by 30%.

In this paper, we address the issue of resource provisioning as an enabler for end-to-end dynamic slicing in software defined networking/network function virtualization (SDN/NFV)-based fifth generation (5G) networks. The different slices’ tenants (i.e. logical operators) are dynamically allocated isolated portions of physical resource blocks (PRBs), baseband processing resources, backhaul capacity as well as data forwarding elements (DFE) and SDN controller connections. By invoking massive key performance indicators (KPIs) datasets stemming from a live cellular network endowed with traffic probes, we first introduce a low-complexity slices’ traffics predictor based on a soft gated recurrent unit (GRU). We then build—at each virtual network function—joint multi-slice deep neural networks (DNNs) and train them to estimate the required resources based on the traffic per slice, while not violating two service level agreement (SLA), namely, violation rate-based SLA and resource bounds-based SLA. This is achieved by integrating dataset-dependent generalized non-convex constraints into the DNN offline optimization tasks that are solved via a non-zero sum two-player game strategy. In this respect, we highlight the role of the underlying hyperparameters in the trade-off between overprovisioning and slices’ isolation. Finally, using reliability theory, we provide a closed-form analysis for the lower bound of the so-called reliable convergence probability and showcase the effect of the violation rate on it. [ABSTRACT FROM AUTHOR]

Satellite–terrestrial integrated networks (STINs) are regarded as a promising solution to meeting the demands of global high-speed seamless network access in the future. Software-defined networking and network function virtualization (SDN/NFV) are two complementary technologies that can be used to ensure that the heterogeneous resources in STINs can be easily managed and deployed. Considering the dual mobility of satellites and ubiquitous users, along with the dynamic requirements of user requests and network resource states, it is challenging to maintain service continuity and high QoE performance in STINs. Thus, we investigate the service migration and reconfiguration scheme, which are of great significance to the guarantee of continuous service provisioning. Specifically, this paper proposes a dynamic service reconfiguration method that can support flexible service configurations on integrated networks, including LEO satellites and ground nodes. We first model the migration cost as an extra delay incurred by service migration and reconfiguration and then formulate the selection processes of the location and migration paths of virtual network functions (VNFs) as an integer linear programming (ILP) optimization problem. Then, we propose a fuzzy logic and quantum genetic algorithm (FQGA) to obtain an approximate optimal solution that can accelerate the solving process efficiently with the benefits of the high-performance computing capacity of QGA. The simulation results validate the effectiveness and improved performance of the scheme proposed in this paper.

Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and intra-datacentre (DC) network and computational resources into a single converged 5G network infrastructure. The present paper overviews the main achievements obtained in the ALLIANCE project. This project ambitiously aims at architecting a converged 5G-enabled network infrastructure satisfying those needs to effectively realise the envisioned upcoming Digital Society. In particular, we present two networking solutions for 5G and beyond 5G (B5G), such as Software Defined Networking/Network Function Virtualisation (SDN/NFV) on top of an ultra-high-capacity spatially and spectrally flexible all-optical network infrastructure, and the clean-slate Recursive Inter-Network Architecture (RINA) over packet networks, including access, metro, core and DC segments. The common umbrella of all these solutions is the Knowledge-Defined Networking (KDN)-based orchestration layer which, by implementing Artificial Intelligence (AI) techniques, enables an optimal end-to-end service provisioning. Finally, the cross-layer manager of the ALLIANCE architecture includes two novel elements, namely the monitoring element providing network and user data in real time to the KDN, and the blockchain-based trust element in charge of exchanging reliable and confident information with external domains.

Remote code execution attacks against network devices become major challenges in securing networking environments. In this paper, we propose a detection framework against remote code execution attacks for closed source network devices using virtualization technologies. Without disturbing a target device in any way, our solution deploys an emulated device as a virtual machine (VM) instance running the same firmware image as the target in a way that ingress packets are mirrored to the emulated device. By doing so, remote code execution attacks mounted by maliciously crafted packets will be captured in memory of the VM. This way, our solution enables successful detection of any kind of intrusions that leaves memory footprints. [ABSTRACT FROM AUTHOR]

5G is considered to be the technology that will accommodate the development and management of innovative services with stringent and diverse requirements from end users, calling for new business models from the industry. In this context, the development and efficient management of Network Services (NS) serving specific vertical industries and spanning across multiple administrative domains and heterogeneous infrastructures is challenging. The main challenges regard the efficient provision of NSs considering the Quality of Service (QoS) requirements per vertical industry along with the optimal usage of the allocated resources. Towards addressing these challenges, this paper details an innovative approach that we have developed for managing and orchestrating such NSs, called SONATA, and compare it with OSM and Cloudify, which are two of the most known open-source Management and Orchestration (MANO) frameworks. In addition to examining the supported orchestration mechanisms per MANO framework, an evaluation of main operational and functional KPIs is provided based on experimentation using a real testbed. The final aim is the identification of their strong and weak points, and the assessment of their suitability for serving diverse vertical industry needs, including of course the Internet of Things (IoT) service ecosystem.

The challenges for mobile communication network raised by new requirements in 5G were analyzed, and then the necessity of researching 5G network technologies was explained. After that, the research situation of global research organizations was introduced, such as NGMN, 5GPPP, IMT-2020 and so on, regarding 5G network technologies, moreover, the standardization status of global standards development organizations on 5G network technologies were introduced. According to the analysis on new requirements and new challenges in 5G network, and current research of 5G network technologies, the development trend of 5G network technologies was predicted and some specific network technologies for the future network were provided. At last, the development of 5G network was concluded and forecasted.

Highlights • Virtual Medical Devices as a mechanism to provide dynamism and security in MCPS. • Fog computing architecture to manage in real time the security of MCPS. • Security policies oriented to detect and mitigate different cyberattacks. • Realistic use case to demonstrate the usefulness of the proposed solution. Abstract Over the last years, solutions based on Information and Communications Technologies (ICT) have opted for the deployment of eHealth services to provide a higher level of quality and safety to medical processes, with which to mitigate human errors. As a result, Medical Cyber-Physical Systems (MCPS) is a new disruptive approach oriented to enable smart healthcare systems to monitor, process and make autonomous decisions without the need to involve doctors and caregivers. Yet, current MCPS pose several open challenges, the security of medical devices being one of the most critical ones because of its close relationship with patients' safety. To deal with these issues, mobile edge cloud computing – or fog computing – can be used to improve the security of MCPS by enabling the deployment and management of efficient resources into the network edge. In this context, we propose the novel concept of Virtual Medical Device as a sustainable and efficient mechanism deployed in the network edge to ease and provide dynamism and low latency for achieving security in MCPS. Additionally, we also propose a fog computing-oriented framework to enable real-time and dynamic management of physical and virtual medical devices as well as network infrastructure composing MCPS. To show our solution feasibility, we designed a reactive and proactive use case depicting security concerns of current MCPS. We also describe how our framework arranges MCPS with management policies that consider patients' vital signs, network communications, and location of medical devices and patients. [ABSTRACT FROM AUTHOR]

The SELFNET project provides an autonomic network management framework for 5G networks with a high degree of automation, self-healing and self-optimization. These capabilities are achieved through a layered architecture and a use-case driven approach. A differentiating feature on SELFNET is its competence when creating and customizing new use cases and their related virtual functions. In this way, the use case operators are able to introduce new rules and parameters that will be taken into account in the analysis and decision-making tasks. Due these characteristics, the orchestration of its analytical functions poses an important challenge in terms of configurability, synchronization and management of resources. In order to contribute to their resolution, this paper aims to lay the groundwork for implement the design and specification of the SELFNET Analyzer orchestration. To this end, several key issues related with the internal coordination of the analytics are introduced, among them initial assumptions, design principles, limitations, partitioning of the analysis process, data persistency and optimization. The proposed orchestration strategy has been implemented with different uses cases within the SELFNET Project. [ABSTRACT FROM AUTHOR]

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In recent years, the applicability of network function virtualization and software-defined networks to optical access systems has been studied for reducing capital expenditure/operating expense and quickly responding to various service requests.We are aiming at expanding the footprint of software-defined functionality in optical line terminals by focusing on physical (PHY) layer functions as one key part of the flexible access system architecture. Utilization of common graphic processing units (GPUs) with a large amount of computation resources is promising for softwarizing PHY-layer functions that have high computation complexity. However, conventional studies do not consider sequential signal input and realize only Mbps-class processing. This paper proposes CPU control for GPU direct transfer in order to directly transfer an external signal input to GPU, and kernel startup scheduling so as to handle a sequential signal at 10 Gbps. For Reed--Solomon decoding, whose PHY-layer functions have high computation complexity, we demonstrate real-time performance from a generalpurpose server with standard optical modules by implementing on it. The proposed configuration is evaluated using an optical system compliant with IEEE 802.3av. Evaluations show that the proposed GPU configuration realizes, for the first time, 10-Gbps real-time error correction. [ABSTRACT FROM AUTHOR]

Improving the performance for VNF (Virtualized Network Function) by hardware acceleration is a hot research topic in SDN/NFV architecture. After introducing the acceleration resource for VNF, how to implement uniform deployment and allocation of the acceleration resources is an urgent problem to be solved. Thus in this paper, a unified deployment architecture of acceleration resource for VNF is proposed firstly. On the basis of architecture, the problem of acceleration resource allocation is modeled. By analyzing the influence of acceleration resource for VNF on deployment of service chains, we propose the evaluation index of acceleration resource allocation algorithm for VNF. Finally, we design a two-stage acceleration resource allocation algorithm to solve the problem. The experimental results show that the proposed algorithm can rationally allocate acceleration resources to nodes in the entire network and improve the efficiency of acceleration resource utilization. [ABSTRACT FROM AUTHOR]

Today, the overloaded networks increasingly entail high operational costs but may not generate new revenues accordingly. Legacy network elements are reaching end-of-life and packet-based transport networks are not efficiently optimized. Thus, an efficient migration plan towards an End-to-End Integrated-Optical-Packet-Network (E2-IOPN) is emerging for service providers in access, metro and core networks. This paper reviews various empirical challenges faced by a Service Provider ( SP ) during the transformation process towards E2-IOPN as well as in the implementation of an as-built plan and high-level design for migrating towards GPON, MPLS-TP, OTN and next-generation DWDM. Then, we propose a SP longer-term strategy based on SDN and NFV approach that will offer rapid end-to-end service provisioning and centralized network control. Such strategy helps SP maintain good profit margin and best customer experience. A cost comparative study shows the benefit and financial impact of introducing new low-cost packet-based technologies to carry legacy as well as new services traffic. [ABSTRACT FROM AUTHOR]

Remote code execution attacks against network devices become major challenges in securing networking environments. In this paper, we propose a detection framework against remote code execution attacks for closed source network devices using virtualization technologies. Without disturbing a target device in any way, our solution deploys an emulated device as a virtual machine (VM) instance running the same firmware image as the target in a way that ingress packets are mirrored to the emulated device. By doing so, remote code execution attacks mounted by maliciously crafted packets will be captured in memory of the VM. This way, our solution enables successful detection of any kind of intrusions that leaves memory footprints.

The fifth generation mobile network, or 5G, moves towards bringing solutions to deploying faster networks, with hundreds of thousands of simultaneous connections and massive data transfer. For this purpose, several emerging technologies are implemented, resulting in virtualization and self-organization of most of their components, which raises important challenges related to safety. In order to contribute to their resolution, this paper proposes a novel architecture for incident management on 5G. The approach combines the conventional risk management schemes with the Endsley Situational Awareness model, thus improving effectiveness in different aspects, among them the ability to adapt to complex and dynamical monitoring environments, and countermeasure tracking or the role of context when decision-making. The proposal takes into account all layers for information processing in 5G mobile networks, ranging from infrastructure to the actuators responsible for deploying corrective measures. [ABSTRACT FROM AUTHOR]

Implementing the security of a network consists in individually configuring several network functions. Network functions are configured by means of a policy composed of a set of rules, but their actual behaviour is influenced by the other policies implemented by all the other network functions around them. This paper proposes a formal model that can be used to detect inter-function anomalies, which are defined as the interferences between two or more functions deployed in the same network. We have proved with experiments that the proposed model is fast and scalable. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The fifth generation mobile network, or 5G, moves towards bringing solutions to deploying faster networks, with hundreds of thousands of simultaneous connections and massive data transfer. For this purpose, several emerging technologies are implemented, resulting in virtualization and self-organization of most of their components, which raises important challenges related to safety. In order to contribute to their resolution, this paper proposes a novel architecture for incident management on 5G. The approach combines the conventional risk management schemes with the Endsley Situational Awareness model, thus improving effectiveness in different aspects, among them the ability to adapt to complex and dynamical monitoring environments, and countermeasure tracking or the role of context when decision-making. The proposal takes into account all layers for information processing in 5G mobile networks, ranging from infrastructure to the actuators responsible for deploying corrective measures.

Satellite–terrestrial integrated networks (STINs) are regarded as a promising solution to meeting the demands of global high-speed seamless network access in the future. Software-defined networking and network function virtualization (SDN/NFV) are two complementary technologies that can be used to ensure that the heterogeneous resources in STINs can be easily managed and deployed. Considering the dual mobility of satellites and ubiquitous users, along with the dynamic requirements of user requests and network resource states, it is challenging to maintain service continuity and high QoE performance in STINs. Thus, we investigate the service migration and reconfiguration scheme, which are of great significance to the guarantee of continuous service provisioning. Specifically, this paper proposes a dynamic service reconfiguration method that can support flexible service configurations on integrated networks, including LEO satellites and ground nodes. We first model the migration cost as an extra delay incurred by service migration and reconfiguration and then formulate the selection processes of the location and migration paths of virtual network functions (VNFs) as an integer linear programming (ILP) optimization problem. Then, we propose a fuzzy logic and quantum genetic algorithm (FQGA) to obtain an approximate optimal solution that can accelerate the solving process efficiently with the benefits of the high-performance computing capacity of QGA. The simulation results validate the effectiveness and improved performance of the scheme proposed in this paper. [ABSTRACT FROM AUTHOR]

5G is considered to be the technology that will accommodate the development and management of innovative services with stringent and diverse requirements from end users, calling for new business models from the industry. In this context, the development and efficient management of Network Services (NS) serving specific vertical industries and spanning across multiple administrative domains and heterogeneous infrastructures is challenging. The main challenges regard the efficient provision of NSs considering the Quality of Service (QoS) requirements per vertical industry along with the optimal usage of the allocated resources. Towards addressing these challenges, this paper details an innovative approach that we have developed for managing and orchestrating such NSs, called SONATA, and compare it with OSM and Cloudify, which are two of the most known open-source Management and Orchestration (MANO) frameworks. In addition to examining the supported orchestration mechanisms per MANO framework, an evaluation of main operational and functional KPIs is provided based on experimentation using a real testbed. The final aim is the identification of their strong and weak points, and the assessment of their suitability for serving diverse vertical industry needs, including of course the Internet of Things (IoT) service ecosystem. [ABSTRACT FROM AUTHOR]