Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.Peer ReviewedPostprint (author's final draft

Importance of Fifth Generation Wireless Systems

Fifth generation wireless communications are denoted by 5G technology. 5G schemes are coming from first generation analog communication, 2G of Global System for Mobile communication (GSM), then 3G of Code Division Multiple Access (CDMA), after that fourth generation of long-term evaluation (LTE), and now fifth generation World Wide Wireless Web (WWWW). This research investigation presents issues, challenges, and the importance of 5G Wifi communication. In the 5G digital cellular network, the coverage area of the service providers is separated into small area called cells. All the audio, video, and image files are digitized and converted by an ADC (Analog to Digital Converter) and transmitted through stream of bits. 5G wireless devices are communicated using radio waves in a geographically reusable common pool of frequency band. Using wireless backhaul connection, the local antennas are connected with the internet/telephone network. Spectrum speed is substantially higher in millimeter wave. Hence, this was considered in this work

Resilient networking in wireless sensor networks

This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR)

A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

Architecture landscape

The network architecture evolution journey will carry on in the years ahead, driving a large scale adoption of 5th Generation (5G) and 5G-Advanced use cases with significantly decreased deployment and operational costs, and enabling new and innovative use-case-driven solutions towards 6th Generation (6G) with higher economic and societal values. The goal of this chapter, thus, is to present the envisioned societal impact, use cases and the End-to-End (E2E) 6G architecture. The E2E 6G architecture includes summarization of the various technical enablers as well as the system and functional views of the architecture

La seguridad en redes SDN y sus aplicaciones

Introduction: The review article is the product of the research on Security in SDN networks and their applications, developed at the District University in 2020, presenting the latest advances, that have been made in security. Problem: The security weaknesses that SDN networks have had, due to being a new architecture. This has not allowed traditional networks to be replaced.   Objective: To carry out a review of the state of the art of SDN networks, focusing research on the security of the control layer and its advances. Methodology: The descriptive method is implemented, consulting databases such as Scopus, IEEE and ScienceDirect, using the following search criteria: SDN networks, security in SDN networks, applications with SDN networks and OpenFlow protocol. It is shown as a research sample: the Asian, European and American continents with years of research from 2014 to 2020. Results: Great advances have been made in terms of security for SDN networks, which allows us to see an early solution to the weaknesses that it currently faces.   Conclusion: SDN networks will solve all the challenges they face and will be consolidated as a solid and reliable architecture.   Originality: an important focus is taken on the security of SDN networks and the great development that has occurred in this regard is evident.   Limitations: SDN networks are a new architecture, so their development has been very little and advances in security have been significantly affected.Introducción: El artículo de revisión es producto de la investigación Seguridad en redes SDN y sus aplicaciones, desarrollada en la Universidad Distrital en el año 2020, presentando los últimos avances que se han logrado en seguridad. Problema: Las debilidades en seguridad que han tenido las redes SDN debido a ser una arquitectura nueva, esto no ha permitido que se reemplacen las redes tradicionales. Objetivo: realizar una revisión del estado del arte de las redes SDN enfocando la investigación la seguridad de la capa de control y sus avances. Metodología: se emplea el método descriptivo, se consultaron bases de datos como Scopus, IEEE y ScienceDirect, utilizando los siguientes criterios de búsqueda: SDN networks, security in SDN networks, applications with SDN networks y OpenFlow protocol, se tomó como muestra de investigación a los continentes asiático, europeo y americano con años de investigación desde el año 2014 hasta el año 2020. Resultados: se han desarrollado grandes avances en seguridad para las redes SDN, lo que permite ver una pronta solución a las debilidades que afronta en la actualidad. Conclusión: las redes SDN lograran resolver todos los retos a los que se enfrentan y se consolidara como una arquitectura sólida y confiable. Originalidad: se realiza un enfoque importante en la seguridad de las redes SDN y se evidencia el gran desarrollo que se ha presentado en este aspecto. Limitaciones: las redes SDN son una arquitectura nueva por lo que su desarrollo ha sido muy poco y los avances en seguridad se vieron afectados significativamente

Security Enhancement by Identifying Attacks Using Machine Learning for 5G Network

Need of security enhancement for 5G network has been increased in last decade. Data transmitted over network need to be secure from external attacks. Thus there is need to enhance the security during data transmission over 5G network. There remains different security system that focus on identification of attacks. In order to identify attack different machine learning mechanism are considered. But the issue with existing research work is limited security and performance issue. There remains need to enhance security of 5G network. To achieve this objective hybrid mechanism are introduced. Different treats such as Denial-of-Service, Denial-of-Detection, Unfair use or resources are classified using enhanced machine learning approach. Proposed work has make use of LSTM model to improve accuracy during decision making and classification of attack of 5G network. Research work is considering accuracy parameters such as Recall, precision and F-Score to assure the reliability of proposed model. Simulation results conclude that proposed model is providing better accuracy as compared to conventional model

Mobilfunknetzmanagement im Kontext von Realistischen Heterogenen Szenarien

Every generation of mobile radio communication standards leads to a new level of complexity in the cellular systems. Moreover, due to the ever-increasing data traffic demands of mobile users as well as declining revenues in recent years, the operators of such networks have to deal with all those network administration difficulties in the most efficient manner. One promising approach that shall relieve the operator from time-consuming manual tasks is to use so-called Self-Organising Network (SON) functionalities. SON functions monitor the performance of the network and change the (radio) parameters accordingly, based on internal algorithms that focus on dedicated optimisation goals. This work investigates whether SON functions can be used to enforce Key Performance Indicator (KPI) targets demanded by the operators. Therefore, the impact of SON on the network manageability and performance is studied by using SON functions that consider multiple technologies (i.e. LTE and WLAN) and different cell layers (macro and small cells). The evaluations are based on sophisticated system-level simulations that rely on an in-house developed platform called ``SiMoNe'' (Simulator for Mobile Networks). Moreover, the foundations of the scenarios used are realistically planned mobile networks on the one hand, and advanced mobility models with a particular emphasis on realistic movements and behaviours, on the other hand. As a preparatory step, the newly introduced mobility models are investigated regarding the handover performance. The results show that the behaviour and nature of the movements have a profound impact on the overall network performance. After that, three well-known SON functions are tested that operate in the domain of self-optimisation. This is done by varying SON algorithm parameterisation values in three distinct network environments. The insights gained into the behaviour of the SON functions are then used to manage a complex heterogeneous cellular network by setting appropriate SON parametrisation values that alter the behaviour of SON functions accordingly. By that, the formulated KPI goals can be achieved. However, the evaluations show that the implementations of the objectives are only doable to some extent in realistic settings due to the compound and inhomogeneous nature of the network scenarios.Jede neue Mobilfunk-Generation sorgt dafür, dass die Komplexität in den Netzen zunimmt. Außerdem führt die immer weiter steigende Nachfrage nach mobilem Datenverkehr sowie sinkende Einnahmen dazu, dass die Betreiber solcher Netze mit administrativen Aufgaben in möglichst effizienter Weise umgehen müssen. Eine Möglichkeit stellen sogenannte Selbst-Organisierende Netze (engl. Self-Organising Network (SON)) dar, um den Betreiber von zeitaufwendigen manuellen Arbeiten zu befreien. SON Funktionen überwachen Kenngrößen im Netz und ändern, je nach Zielfunktion des Algorithmus, entsprechende (Radio-)Parameter im Netz. Diese Dissertation untersucht, ob SON Funktionen geeignet sind um ein Mobilfunknetz zu steuern und somit vorgegebene Zielvorgaben der Netzbetreiber umzusetzen. Die verwendeten SON Funktionen arbeiten hierbei mit unterschiedlichen Technologien (z.B. LTE und WLAN) und auf mehreren Zellschichten (Makro- bis Femtozellen). Als Simulationsumgebung wird auf die leistungsfähige Plattform ``SiMoNe'' (engl. Simulator for Mobile Networks) zurückgegriffen. Die Simulationsgrundlagen bilden einerseits realistisch geplante Mobilfunknetze und anderseits fortschrittliche Mobilitätsmodelle, wobei eine besondere Betonung auf die realistische Umsetzung von Bewegung und Verhalten der Nutzer gelegt wird. In einem vorbereitenden Schritt werden neuartige Mobilitätsmodelle auf ihr Handover-Verhalten untersucht. Die Ergebnisse zeigen hierbei, dass das Verhalten und die Bewegung einen entscheidenden Einfluss auf die Netzperformance haben können. Im Anschluss werden drei bekannte SON Funktionen in drei unterschiedlichen Netzumgebungen getestet. Dies geschieht durch eine Variation der Parameterwerte der SON Algorithmen, welche das Verhalten der Funktionen verändern und somit auch die Netzperformances entscheidend beeinflussen kann. Die über das Verhalten der SON Funktionen gesammelten Erkenntnisse werden letztendlich genutzt, um Zielvorgaben an ein komplexes heterogenes Mobilfunknetzwerk zu realisieren. Die Auswertungen zeigen, dass dies nur in einem gewissen Maße geschehen kann. Die hohe Komplexität und die inhomogene Topologie der Netze beeinträchtigen eine zielgenaue Veränderung der Netzperformance entscheidend

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

Contributing to the pathway towards 5G experimentation with an SDN-controlled network box

Καθώς η απαίτηση σε ευρυζωνικές υπηρεσίες κινητών επικοινωνιών αυξάνεται ραγδαία, τα υπάρχοντα δίκτυα κινητών επικοινωνιών πλησιάζουν τα όριά τους κάνοντας επιτακτική την ανάγκη εξέλιξής τους η οποία θα επέλθει με την τεχνολογική άφιξη της επόμενης γενιάς κινητών επικοινωνιών, ευρέως γνωστής ως 5G. Το 5G μεταφέρει όλες εκείνες τις δυνατότητες οι οποίες είναι απαραίτητες για να καλυφθούν οι συνεχώς αυξανόμενες ανάγκες σε ευρυζωνικές υπηρεσίες, να υποστηρίξουν το Internet of Things καθώς και να ενοποιήσουν ετερογενείς υπηρεσίες σε διαφορετικές βιομηχανίες. Η παρούσα διπλωματική εργασία στοχεύει να παρουσιάσει το “Network in a box”, ένα καινοτόμο εργαλείο που αναπτύξαμε στο εργαστήριο, το οποίο βασίζεται επάνω στους θεμέλιους λίθους του 5G, το SDN και το NFV. Με το SDN να είναι η νέα προσέγγιση στα δίκτυα κινητών επικοινωνιών, ο έλεγχος διαχωρίζεται από τα δεδομένα παρέχοντας τη δυνατότητα οποιεσδήποτε αποφάσεις ελέγχου, να λαμβάνονται κεντρικά, μετατρέποντας έτσι τις κλασικές δικτυακές συσκευές σε απλά προωθητικά στοιχεία του δικτύου. Η συγκεκριμένη διάταξη μιμείται ένα πραγματικό δίκτυο, το οποίο διαθέτει δυνατότητες αυτο-οργάνωσης και αυτο-βελτίωσης, προσομοιώνοντας τη λειτουργία του 5G δικτύου. Το συγκεκριμένο εργαλείο είναι επίσης ικανό να παράσχει KPI μετρικές του 5G δικτύου κάτω από πραγματικές συνθήκες ενόσω αληθινές δικτυακές συσκευές είναι συνδεδεμένες σε αυτό. Η δομή της παρούσας διπλωματικής εργασίας αναλύεται σε πέντε κεφάλαια. Το πρώτο κεφάλαιο παρουσιάζει τις προκλήσεις που σύντομα θα κληθούν να αντιμετωπίσουν τα δίκτυα κινητών επικοινωνιών και πώς αυτές μπορούν να καλυφθούν με την τεχνολογία του 5G. Το δεύτερο κεφάλαιο εισάγει την τάση στην αγορά των κινητών επικοινωνιών που διαφένεται πίσω από την επερχόμενη άφιξη του 5G, αποκαλύπτοντας το επιχειρηματικό πλαίσιο για επιχειρήσεις, καταναλωτές και συνεργασίες όπως επίσης και κάποιες περιπτώσεις χρήσης που αντικατοπτρίζουν την διαρκή εξέλιξη στις ευρυζωνικές υπηρεσίες κινητών επικοινωνιών. Το τρίτο κεφάλαιο εμπεριέχει μια μικρή επισκόπηση των τρέχοντων έργων πάνω στο 5G, τα οποία ξεκίνησαν υπό την αιγίδα της Ευρωπαϊκής Επιτροπής με τη συνεργασία προμηθευτών τεχνολογίας επικοινωνιών, παρόχων υπηρεσιών, μικρομεσαίων επιχειρήσεων και πανεπιστημίων. Γίνεται επίσης αναφορά στις βασικές τεχνολογίες του 5G και στις δραστηριότητες προτυποποίησής του. Προχωρώντας στο τέταρτο κεφάλαιο, περιγράφουμε σε βάθος την αρχιτεκτονική του 5G δικτύου, αναλύοντας τα SDN, NFV, MANO και εξετάζουμε πώς αυτά συνεισφέρουν στη βιωσιμότητα του δικτύου. Τέλος, στο πέμπτο κεφάλαιο εισάγουμε μια καινοτόμο ιδέα που αναπτύξαμε στο εργαστήριο δικτύων του πανεπιστημίου μας, ένα πλήρως αυτόνομο δικτυακό εργαλείο, το “Network in a box”. Παρουσιάζουμε σε βάθος πώς αυτός ο server μπορεί να εγκατασταθεί και να λειτουργήσει καθώς και τις δυνατότητές του κάτω από πραγματικές συνθήκες λειτουργίας του δικτύου, ενώ λαμβάνουν χώρα υποβάθμιση ποιότητας ή μη-διαθεσιμότητα στις δικτυακές ζεύξεις, παρέχοντας επίσης μετρικές από τη λειτουργία του δικτύου σε πραγματικό χρόνο.As the demand in mobile broadband is tremendously increased and the heterogeneity of the services to be covered is growing rapidly, current mobile networks are close to their limits imposing the need of an evolution which is going to be introduced by the next generation technology, the ITU IMT-2020, well known as 5G. 5G brings all those capabilities required to cover the increased mobile broadband needs, support the Internet of Things and bind heterogeneous services in different industries. This diploma thesis aims at presenting the “Network in a box”, an innovative tool we developed which is based on the key 5G principles, SDN and NFV. With Software Defined Networking (SDN) being the new approach in mobile networks, control and data plane are decoupled providing the ability to make any control related decisions centrally and transform legacy network devices to simple forwarding elements. This testbed is a portable emulated network device which is self-managed and self-optimised and can be connected between any real network devices, emulating how the 5G network will perform. This plug & play black-box testbed is also capable of providing KPI metrics of the 5G network under real circumstances when real network devices are connected to it. The structure of this diploma thesis is decomposed in five chapters. Chapter 1 presents the challenges mobile networks will shortly face due to the growing heterogeneous demands in communications towards the year 2020 and beyond and how these can be met with the upcoming 5G technology. Chapter 2 introduces the market trend behind the new era of 5G, revealing the business context for enterprises, consumers, verticals and partnerships as well as some use cases which reflect the continuous mobile broadband evolution. Chapter 3 includes a short overview of the ongoing 5G projects, initiated under the umbrella of the European Commission, with the collaboration of communications technology vendors, telecommunications operators, service providers, small and medium-sized enterprises (SMEs) and universities. There is also a reference in 5G key enabling technologies and standardisation activities as we move towards the next generation mobile networks technology. Moving forward, chapter 4 describes in detail the technological components of 5G network architecture such as SDN, NFV, MANO and examines how these 5G key enabling technologies contribute to the overall networks’ sustainability. Finally, in chapter 5 we introduce an innovative idea developed in our university’s communications network research laboratory, an autonomous emulated portable network testbed, the “Network in a box”. We present in-depth how this portable server is deployed, operates and demonstrate the way it can be connected to real network elements emulating a real 5G end-to-end customer network. Moreover, in this last chapter we present “Network in a box” capabilities under real network circumstances when link degradations or failures take place, providing also real-time network metrics