Trust and reputation management for securing collaboration in 5G access networks: the road ahead

Trust represents the belief or perception of an entity, such as a mobile device or a node, in the extent to which future actions and reactions are appropriate in a collaborative relationship. Reputation represents the network-wide belief or perception of the trustworthiness of an entity. Each entity computes and assigns a trust or reputation value, which increases and decreases with the appropriateness of actions and reactions, to another entity in order to ensure a healthy collaborative relationship. Trust and reputation management (TRM) has been investigated to improve the security of traditional networks, particularly the access networks. In 5G, the access networks are multi-hop networks formed by entities which may not be trustable, and so such networks are prone to attacks, such as Sybil and crude attacks. TRM addresses such attacks to enhance the overall network performance, including reliability, scalability, and stability. Nevertheless, the investigation of TRM in 5G, which is the next-generation wireless networks, is still at its infancy. TRM must cater for the characteristics of 5G. Firstly, ultra-densification due to the exponential growth of mobile users and data traffic. Secondly, high heterogeneity due to the different characteristics of mobile users, such as different transmission characteristics (e.g., different transmission power) and different user equipment (e.g., laptops and smartphones). Thirdly, high variability due to the dynamicity of the entities’ behaviors and operating environment. TRM must also cater for the core features of 5G (e.g., millimeter wave transmission, and device-to-device communication) and the core technologies of 5G (e.g., massive MIMO and beamforming, and network virtualization). In this paper, a review of TRM schemes in 5G and traditional networks, which can be leveraged to 5G, is presented. We also provide an insight on some of the important open issues and vulnerabilities in 5G networks that can be resolved using a TRM framework

Metrics for Broadband Networks in the Context of the Digital Economies

In a transition to automated digital management of broadband networks, communication service providers must look for new metrics to monitor these networks. Complete metrics frameworks are already emerging whereas majority of the new metrics are being proposed in technical papers. Considering common metrics for broadband networks and related technologies, this chapter offers insights into what metrics are available, and also suggests active areas of research. The broadband networks being a key component of the digital ecosystems are also an enabler to many other digital technologies and services. Reviewing first the metrics for computing systems, websites and digital platforms, the chapter focus then shifts to the most important technical and business metrics which are used for broadband networks. The demand-side and supply-side metrics including the key metrics of broadband speed and broadband availability are touched on. After outlining the broadband metrics which have been standardized and the metrics for measuring Internet traffic, the most commonly used metrics for broadband networks are surveyed in five categories: energy and power metrics, quality of service, quality of experience, security metrics, and robustness and resilience metrics. The chapter concludes with a discussion on machine learning, big data and the associated metrics

Demystifying Usability of Open Source Computational Offloading Simulators : Performance Evaluation Campaign

Along with analysis and practical implementation, simulations play a key role in wireless networks and computational offloading research for several reasons. First, the simulations provide the ability to easily obtain the data for a complex system’s model evaluation. Secondly, simulated data provides a controlled environment for experimentation, allowing models and algorithms to be tested for robustness and identifying potential limitations before deploying them in real-world applications. Choosing the most appropriate tool for simulation might be challenging and depends on several factors, such as the main purpose, complexity of data, researcher skills, community support, and available budget. As of the time of the present analysis, several system-level open-source tools for modeling computational offloading also cover the systems’ communications side, such as CloudSim , CloudSim Plus , IoTSim-Edge , EdgeCloudSim , iFogSim2 , PureEdgeSim , and YAFS . This work presents an evaluation of those based on the unique features and performance results of intensive workload- and delay-tolerant scenarios: XR with an extremely high data rate and workload; remote monitoring with a low data rate with moderate delays and workload requirements; and data streaming as a general human traffic with a relatively high bit rate but moderate workload. The work concludes that CloudSim provides a reliable environment for virtualization on the host resources, while YAFS shows minimal hardware usage, while IoTSim-Edge , PureEdgeSim , and EdgeCloudSim have fewer implemented features.Peer reviewe

From serendipity to sustainable Green IoT: technical, industrial and political perspective

Recently, Internet of Things (IoT) has become one of the largest electronics market for hardware production due to its fast evolving application space. However, one of the key challenges for IoT hardware is the energy efficiency as most of IoT devices/objects are expected to run on batteries for months/years without a battery replacement or on harvested energy sources. Widespread use of IoT has also led to a largescale rise in the carbon footprint. In this regard, academia, industry and policy-makers are constantly working towards new energy-efficient hardware and software solutions paving the way for an emerging area referred to as green-IoT. With the direct integration and the evolution of smart communication between physical world and computer-based systems, IoT devices are also expected to reduce the total amount of energy consumption for the Information and Communication Technologies (ICT) sector. However, in order to increase its chance of success and to help at reducing the overall energy consumption and carbon emissions a comprehensive investigation into how to achieve green-IoT is required. In this context, this paper surveys the green perspective of the IoT paradigm and aims to contribute at establishing a global approach for green-IoT environments. A comprehensive approach is presented that focuses not only on the specific solutions but also on the interaction among them, and highlights the precautions/decisions the policy makers need to take. On one side, the ongoing European projects and standardization efforts as well as industry and academia based solutions are presented and on the other side, the challenges, open issues, lessons learned and the role of policymakers towards green-IoT are discussed. The survey shows that due to many existing open issues (e.g., technical considerations, lack of standardization, security and privacy, governance and legislation, etc.) that still need to be addressed, a realistic implementation of a sustainable green-IoT environment that could be universally accepted and deployed, is still missing

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions

Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart services and innovative applications. Such a context urges a heavy usage of Machine Learning (ML) techniques, particularly Deep Learning (DL), to foster innovation and ease the deployment of intelligent network functions/operations, which are able to fulfill the various requirements of the envisioned 6G services. Specifically, collaborative ML/DL consists of deploying a set of distributed agents that collaboratively train learning models without sharing their data, thus improving data privacy and reducing the time/communication overhead. This work provides a comprehensive study on how collaborative learning can be effectively deployed over 6G wireless networks. In particular, our study focuses on Split Federated Learning (SFL), a technique recently emerged promising better performance compared with existing collaborative learning approaches. We first provide an overview of three emerging collaborative learning paradigms, including federated learning, split learning, and split federated learning, as well as of 6G networks along with their main vision and timeline of key developments. We then highlight the need for split federated learning towards the upcoming 6G networks in every aspect, including 6G technologies (e.g., intelligent physical layer, intelligent edge computing, zero-touch network management, intelligent resource management) and 6G use cases (e.g., smart grid 2.0, Industry 5.0, connected and autonomous systems). Furthermore, we review existing datasets along with frameworks that can help in implementing SFL for 6G networks. We finally identify key technical challenges, open issues, and future research directions related to SFL-enabled 6G networks

Digital Agriculture and Intelligent Farming Business Using Information and Communication Technology: A Survey

Adopting new information and communication technology (ICT) as a solution to achieve food security becomes more urgent than before, particularly with the demographical explosion. In this survey, we analyze the literature in the last decade to examine the existing fog/edge computing architectures adapted for the smart farming domain and identify the most relevant challenges resulting from the integration of IoT and fog/edge computing platforms. On the other hand, we describe the status of Blockchain usage in intelligent farming as well as the most challenges this promising topic is facing. The relevant recommendations and researches needed in Blockchain topic to enhance intelligent farming sustainability are also highlighted. It is found through the examination that the adoption of ICT in the various farming processes helps to increase productivity with low efforts and costs. Several challenges are faced when implementing such solutions, they are mainly related to the technological development, energy consumption, and the complexity of the environments where the solutions are implemented. Despite these constraints, it is certain that shortly several farming businesses will heavily invest to introduce more intelligence into their management methods. Furthermore, the use of sophisticated deep learning and Blockchain algorithms may contribute to the resolution of many recent farming issues

Softwarization of Large-Scale IoT-based Disasters Management Systems

The Internet of Things (IoT) enables objects to interact and cooperate with each other for reaching common objectives. It is very useful in large-scale disaster management systems where humans are likely to fail when they attempt to perform search and rescue operations in high-risk sites. IoT can indeed play a critical role in all phases of large-scale disasters (i.e. preparedness, relief, and recovery). Network softwarization aims at designing, architecting, deploying, and managing network components primarily based on software programmability properties. It relies on key technologies, such as cloud computing, Network Functions Virtualization (NFV), and Software Defined Networking (SDN). The key benefits are agility and cost efficiency. This thesis proposes softwarization approaches to tackle the key challenges related to large-scale IoT based disaster management systems. A first challenge faced by large-scale IoT disaster management systems is the dynamic formation of an optimal coalition of IoT devices for the tasks at hand. Meeting this challenge is critical for cost efficiency. A second challenge is an interoperability. IoT environments remain highly heterogeneous. However, the IoT devices need to interact. Yet another challenge is Quality of Service (QoS). Disaster management applications are known to be very QoS sensitive, especially when it comes to delay. To tackle the first challenge, we propose a cloud-based architecture that enables the formation of efficient coalitions of IoT devices for search and rescue tasks. The proposed architecture enables the publication and discovery of IoT devices belonging to different cloud providers. It also comes with a coalition formation algorithm. For the second challenge, we propose an NFV and SDN based - architecture for on-the-fly IoT gateway provisioning. The gateway functions are provisioned as Virtual Network Functions (VNFs) that are chained on-the-fly in the IoT domain using SDN. When it comes to the third challenge, we rely on fog computing to meet the QoS and propose algorithms that provision IoT applications components in hybrid NFV based - cloud/fogs. Both stationary and mobile fog nodes are considered. In the case of mobile fog nodes, a Tabu Search-based heuristic is proposed. It finds a near-optimal solution and we numerically show that it is faster than the Integer Linear Programming (ILP) solution by several orders of magnitude

Cognitive virtual ad hoc mobile cloud-based networking architecture

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThis thesis proposed cognitive techniques and intelligent algorithms that offered adaptive and advanced facilities to cloud-based networking by using Virtual Ad Hoc Mobile Cloud Computing Networks architecture (VAMCCNs). This is presented as a working case to address their global network challenges and to add cognitive support to the network design and implementation for better meeting traffic management and application requirements in mission objectives. The thesis concentrates on three main contributions. Firstly, an adaptive model, namely: a Heterogeneous Mobile Cloud Computing Network (HMCCN), was proposed to integrate different cloud networks architectures into one workflow. The cognitive data offloading task and the routing decision methods were applied using two different approaches: Fuzzy Analytic Hierarchy system (FAH) as a first approach and cognitive Software Defined Network (SDN) model as a second centralised approach. Experimental results show improvement in network reliability and throughputs, minimised in both nodes’ energy consumption and network latency with efficient intelligent data load balance and network resources allocation with best cloud model selection. Secondly, based on a virtual Ad Hoc cloud network with a realistic Random Waypoint Motion (RWM) model, an innovative cognitive routing algorithm was presented to improve efficient and reliable route selection among multiple possible routes. Routing protocols based on conventional, Fuzzy logic used important parameters with two data collections and decisions techniques and a new adaptive Intelligent Hybrid Fuzzy-Neural routing protocol (IHFN) that included prior knowledge to the network of the underlying motion and energy parameters were all proposed and compared. Results with the new hybrid algorithm shown a significant improvement to solve the network end-to-end performance degradation problem. The new hybrid protocol improved network throughput with an average of 20% higher than traditional Ad Hoc On-Demand Distance Vector (AODV) Routing protocol, improved the usage of network resources and reduced the maintenance process in adynamic topologies network. Finally, based on datasets collected from a realistic motion RWM model in a virtual Ad Hoc cloud network, the performance behaviour of six selected deep learning algorithms to predict the next steps of positions, speed and residual battery energy values of these mobile nodes have been evaluated and compared. This work goes further by presenting two algorithm's training techniques to predict the next 300-time steps of position, speed, and energy. Results and dissuasion show the differences concerning prediction accuracy between using the single node dataset model or Multiple node's dataset model

Les opérateurs sauront-ils survivre dans un monde en constante évolution? Considérations techniques conduisant à des scénarios de rupture

Le secteur des télécommunications passe par une phase délicate en raison de profondes mutations technologiques, principalement motivées par le développement de l'Internet. Elles ont un impact majeur sur l'industrie des télécommunications dans son ensemble et, par conséquent, sur les futurs déploiements des nouveaux réseaux, plateformes et services. L'évolution de l'Internet a un impact particulièrement fort sur les opérateurs des télécommunications (Telcos). En fait, l'industrie des télécommunications est à la veille de changements majeurs en raison de nombreux facteurs, comme par exemple la banalisation progressive de la connectivité, la domination dans le domaine des services de sociétés du web (Webcos), l'importance croissante de solutions à base de logiciels et la flexibilité qu'elles introduisent (par rapport au système statique des opérateurs télécoms). Cette thèse élabore, propose et compare les scénarios possibles basés sur des solutions et des approches qui sont technologiquement viables. Les scénarios identifiés couvrent un large éventail de possibilités: 1) Telco traditionnel; 2) Telco transporteur de Bits; 3) Telco facilitateur de Plateforme; 4) Telco fournisseur de services; 5) Disparition des Telco. Pour chaque scénario, une plateforme viable (selon le point de vue des opérateurs télécoms) est décrite avec ses avantages potentiels et le portefeuille de services qui pourraient être fournisThe telecommunications industry is going through a difficult phase because of profound technological changes, mainly originated by the development of the Internet. They have a major impact on the telecommunications industry as a whole and, consequently, the future deployment of new networks, platforms and services. The evolution of the Internet has a particularly strong impact on telecommunications operators (Telcos). In fact, the telecommunications industry is on the verge of major changes due to many factors, such as the gradual commoditization of connectivity, the dominance of web services companies (Webcos), the growing importance of software based solutions that introduce flexibility (compared to static system of telecom operators). This thesis develops, proposes and compares plausible future scenarios based on future solutions and approaches that will be technologically feasible and viable. Identified scenarios cover a wide range of possibilities: 1) Traditional Telco; 2) Telco as Bit Carrier; 3) Telco as Platform Provider; 4) Telco as Service Provider; 5) Telco Disappearance. For each scenario, a viable platform (from the point of view of telecom operators) is described highlighting the enabled service portfolio and its potential benefitsEVRY-INT (912282302) / SudocSudocFranceF