Models and Methods for Network Selection and Balancing in Heterogeneous Scenarios

The outbreak of 5G technologies for wireless communications can be considered a response to the need for widespread coverage, in terms of connectivity and bandwidth, to guarantee broadband services, such as streaming or on-demand programs offered by the main television networks or new generation services based on augmented and virtual reality (AR / VR). The purpose of the study conducted for this thesis aims to solve two of the main problems that will occur with the outbreak of 5G, that is, the search for the best possible connectivity, in order to offer users the resources necessary to take advantage of the new generation services, and multicast as required by the eMBMS. The aim of the thesis is the search for innovative algorithms that will allow to obtain the best connectivity to offer users the resources necessary to use the 5G services in a heterogeneous scenario. Study UF that allows you to improve the search for the best candidate network and to achieve a balance that allows you to avoid congestion of the chosen networks. To achieve these two important focuses, I conducted a study on the main mathematical methods that made it possible to select the network based on QoS parameters based on the type of traffic made by users. A further goal was to improve the computational computation performance they present. Furthermore, I carried out a study in order to obtain an innovative algorithm that would allow the management of multicast. The algorithm that has been implemented responds to the needs present in the eMBMS, in realistic scenarios

Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-iot integrated deployment environments

Traditionally, hybrid optical-wireless networks (Fiber-Wireless - FiWi domain) and last-mile Internet of Things edge networks (Edge IoT domain) have been considered independently, with no synergic management solutions. On the one hand, FiWi has primarily focused on high-bandwidth and low-latency access to cellular-equipped nodes. On the other hand, Edge IoT has mainly aimed at effective dispatching of sensor/actuator data among (possibly opportunistic) nodes, by using direct peer-to-peer and base station (BS)-assisted Internet communications. The paper originally proposes a model and an architecture that loosely federate FiWi and Edge IoT domains based on the interaction of FiWi and Edge IoT software defined networking controllers: The primary idea is that our federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of end-to-end quality-aware packet management. To show the applicability and the effectiveness of the approach, our original proposal is applied to the notable example of multimedia stream provisioning from surveillance cameras deployed in the Edge IoT domain to both an infrastructure-side server and spontaneously interconnected mobile smartphones; our solution is able to tune the BS behavior of the FiWi domain and to reroute/prioritize traffic in the Edge IoT domain, with the final goal to reduce latency. In addition, the reported application case shows the capability of our solution of joint and coordinated exploitation of resources in FiWi and Edge IoT domains, with performance results that highlight its benefits in terms of efficiency and responsiveness

Quality of Service improvements for real time multimedia applications using next generation network architectures and blockchain in Internet Service Provider cooperative scenario

Real time communications are becoming part of our daily life, requiring constrained requisites with the purpose of being enjoyed in harmony by end users. The factors ruling these requisites are Quality of Service parameters of the users' Internet connections. Achieving a satisfactory QoS level for real time communications depends on parameters that are strongly influenced by the quality of the network connections among the Internet Service Providers, which are located in the path between final users and Over The Top service providers that are supplying them with real time services. Final users can be: business people having real time videoconferences, or adopting crytpocurrencies in their exchanges, videogamers playing online games together with others residing in other countries, migrants talking with their relatives or watching their children growing up in their home countries, people with disabilities adopting tecnologies to help them, doctors performing remote surgeries, manufacturers adopting augmented reality devices to perform dangerous tasks. Each of them performing their daily activities are requiring specific QoS parameters to their ISPs, that nowadays seem to be unable to provide them with a satisfactory QoS level for these kinds of real time services. Through the adoption of next generation networks, such as the Information Centric Networking, it would be possible to overcome the QoS problems that nowadays are experienced. By adopting Blockchain technologies, in several use cases, it would be possible to improve those security aspects related to the non-temperability of information and privacy. I started this thesis analyzing next generation architectures enabling real time multimedia communications. In Software Defined Networking, Named Data Networking and Community Information Centric Networking, I highlighted potential approaches to solve QoS problems that are affecting real time multimedia applications. During my experiments I found that applications able to transmit high quality videos, such as 4k or 8k videos, or to directly interact with devices AR/VR enabled are missing for both ICN approaches. Then I proposed a REST interface for the enforcing of a specific QoS parameter, the round trip time (RTT) taking into consideration the specific use case of a game company that connects with the same telecommunication company of the final user. Supposing that the proposed REST APIs have been deployed in the game company and in the ISP, when one or more users are experiencing lag, the game company will try to ask the ISP to reduce the RTT for that specific user or that group of users. This request can be done by performing a call to a method where IP address(es) and the maximum RTT desired are passed. I also proposed other methods, through which it would be possible to retrieve information about the QoS parameters, and exchange, if necessary, an exceeding parameter in change of another one. The proposed REST APIs can also be used in more complex scenarios, where ISPs along the path are chained together, in order to improve the end to end QoS among Over The Top service provider and final users. To store the information exchanged by using the proposed REST APIs, I proposed to adopt a permissioned blockchain, analizying the ISPs cooperative use case with Hyperledger Fabric, where I proposed the adoption of the Proof of Authority consensus algorithm, to increase the throughput in terms of transactions per second. In a specific case that I examined, I am proposing a combination of Information Centric Networking and Blockchain, in an architecture where ISPs are exchanging valuable information regarding final Users, to improve their QoS parameters. I also proposed my smart contract for the gaming delay use case, that can be used to rule the communication among those ISPs that are along the path among OTT and final users. An extension of this work can be done, by defining billing costs for the QoS improvements

A Survey of Deep Learning for Data Caching in Edge Network

The concept of edge caching provision in emerging 5G and beyond mobile networks is a promising method to deal both with the traffic congestion problem in the core network as well as reducing latency to access popular content. In that respect end user demand for popular content can be satisfied by proactively caching it at the network edge, i.e, at close proximity to the users. In addition to model based caching schemes learning-based edge caching optimizations has recently attracted significant attention and the aim hereafter is to capture these recent advances for both model based and data driven techniques in the area of proactive caching. This paper summarizes the utilization of deep learning for data caching in edge network. We first outline the typical research topics in content caching and formulate a taxonomy based on network hierarchical structure. Then, a number of key types of deep learning algorithms are presented, ranging from supervised learning to unsupervised learning as well as reinforcement learning. Furthermore, a comparison of state-of-the-art literature is provided from the aspects of caching topics and deep learning methods. Finally, we discuss research challenges and future directions of applying deep learning for cachin

Digital Twin-Driven Network Architecture for Video Streaming

Digital twin (DT) is revolutionizing the emerging video streaming services through tailored network management. By integrating diverse advanced communication technologies, DTs are promised to construct a holistic virtualized network for better network management performance. To this end, we develop a DT-driven network architecture for video streaming (DTN4VS) to enable network virtualization and tailored network management. With the architecture, various types of DTs can characterize physical entities' status, separate the network management functions from the network controller, and empower the functions with emulated data and tailored strategies. To further enhance network management performance, three potential approaches are proposed, i.e., domain data exploitation, performance evaluation, and adaptive DT model update. We present a case study pertaining to DT-assisted network slicing for short video streaming, followed by some open research issues for DTN4VS.Comment: 8 pages, 5 figures, submitted to IEEE Network Magazin