A Big Data and machine learning approach for network monitoring and security

In the last decade the performances of 802.11 (Wi-Fi) devices skyrocketed. Today it is possible to realize gigabit wireless links spanning across kilometers at a fraction of the cost of the wired equivalent. In the same period, mesh network evolved from being experimental tools confined into university labs, to systems running in several real world scenarios. Mesh networks can now provide city-wide coverage and can compete on the market of Internet access. Yet, being wireless distributed networks, mesh networks are still hard to maintain and monitor. This paper explains how today we can perform monitoring, anomaly detection and root cause analysis in mesh networks using Big Data techniques. It first describes the architecture of a modern mesh network, it justifies the use of Big Data techniques and provides a design for the storage and analysis of Big Data produced by a large-scale mesh network. While proposing a generic infrastructure, we focus on its application in the security domain

WIP: Analysis of feasible topologies for backhaul mesh networks

Mesh backhauls are getting attention for 5G networks, but not only. A backhaul mesh is attractive due to its multiple potential paths that grants redundancy and robustness. The real topology and its properties, however, is heavily influenced by the characteristics of the place where it is deployed, a fact that is rarely taken into account by scientific literature, mainly due to the lack of detailed topographic data. This WIP analyzes the impact of true topography on small backhaul meshes in nine different locations in Italy. Initial results stress how true data influence results and can help designing better networks and better services

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

A Mini Review of Peer-to-Peer (P2P) for Vehicular Communication

In recent times, peer-to-peer (P2P) has evolved, where it leverages the capability to scale compared to server-based networks. Consequently, P2P has appeared to be the future distributed systems in emerging several applications. P2P is actually a disruptive technology for setting up applications that scale to numerous concurrent individuals. Thus, in a P2P distributed system, individuals become themselves as peers through contributing, sharing, and managing the resources in a network. In this paper, P2P for vehicular communication is explored. A comprehensive of the functioning concept of both P2P along with vehicular communication is examined. In addition, the advantages are furthermore conversed for a far better understanding on the implementation

Secure Communication in Disaster Scenarios

Während Naturkatastrophen oder terroristischer Anschläge ist die bestehende Kommunikationsinfrastruktur häufig überlastet oder fällt komplett aus. In diesen Situationen können mobile Geräte mithilfe von drahtloser ad-hoc- und unterbrechungstoleranter Vernetzung miteinander verbunden werden, um ein Notfall-Kommunikationssystem für Zivilisten und Rettungsdienste einzurichten. Falls verfügbar, kann eine Verbindung zu Cloud-Diensten im Internet eine wertvolle Hilfe im Krisen- und Katastrophenmanagement sein. Solche Kommunikationssysteme bergen jedoch ernsthafte Sicherheitsrisiken, da Angreifer versuchen könnten, vertrauliche Daten zu stehlen, gefälschte Benachrichtigungen von Notfalldiensten einzuspeisen oder Denial-of-Service (DoS) Angriffe durchzuführen. Diese Dissertation schlägt neue Ansätze zur Kommunikation in Notfallnetzen von mobilen Geräten vor, die von der Kommunikation zwischen Mobilfunkgeräten bis zu Cloud-Diensten auf Servern im Internet reichen. Durch die Nutzung dieser Ansätze werden die Sicherheit der Geräte-zu-Geräte-Kommunikation, die Sicherheit von Notfall-Apps auf mobilen Geräten und die Sicherheit von Server-Systemen für Cloud-Dienste verbessert

Mobility-aware Software-Defined Service-Centric Networking for Service Provisioning in Urban Environments

Disruptive applications for mobile devices, such as the Internet of Things, Connected and Autonomous Vehicles, Immersive Media, and others, have requirements that the current Cloud Computing paradigm cannot meet. These unmet requirements bring the necessity to deploy geographically distributed computing architectures, such as Fog and Mobile Edge Computing. However, bringing computing close to users has its costs. One example of cost is the complexity introduced by the management of the mobility of the devices at the edge. This mobility may lead to issues, such as interruption of the communication with service instances hosted at the edge or an increase in communication latency during mobility events, e.g., handover. These issues, caused by the lack of mobility-aware service management solutions, result in degradation in service provisioning. The present thesis proposes a series of protocols and algorithms to handle user and service mobility at the edge of the network. User mobility is characterized when user change access points of wireless networks, while service mobility happens when services have to be provisioned from different hosts. It assembles them in a solution for mobility-aware service orchestration based on Information-Centric Networking (ICN) and runs on top of Software-Defined Networking (SDN). This solution addresses three issues related to handling user mobility at the edge: (i) proactive support for user mobility events, (ii) service instance addressing management, and (iii) distributed application state data management. For (i), we propose a proactive SDN-based handover scheme. For (ii), we propose an ICN addressing strategy to remove the necessity of updating addresses after service mobility events. For (iii), we propose a graph-based framework for state data placement in the network nodes that accounts for user mobility and latency requirements. The protocols and algorithms proposed in this thesis were compared with different approaches from the literature through simulation. Our results show that the proposed solution can reduce service interruption and latency in the presence of user and service mobility events while maintaining reasonable overhead costs regarding control messages sent in the network by the SDN controller

Design and development of an SDN robotic system with intelligent openflow IOT testbeds for power assessment, prediction and fault management

This thesis was submitted for the award of Docctor of Philosophy and was awarded by Brunel University LondonCurrent wind turbine and power grid industry have relatively little research and development with regards to implementing novel communication network and intel- ligent system to overcome issues that pertain to network failure and lack of monitor- ing. Wind turbine location could be a big concern when it comes to identifying an efficient location for future wind turbine and the impact of a site with non-efficient meteorological parameters can result in relocation of a wind turbine and revenue- loss. Unplanned wind turbine shutdowns that are considered to be one of the major revenue-loss factors of a modern wind farm business. Typically, the unplanned wind turbine shutdown is a result of sensors fail due to harsh environment challenges that prevent hardware status from being available on the monitoring system. The above mentioned research problems pertain to wind turbine site assessment and predic- tion of power. In this thesis, a novel programmable software-defined robotics and IoT testbeds are proposed with the fusion of Artificial Intelligence and optimiza- tion methods to solve specific problems related to wind turbine site assessment and fault management. The site selection process is implemented using proposed aerial and ground robotic systems that are incorporated with Software-Defined Networks and OpenFlow switching capabilities. A second stage development of the system is proposing a prediction platform that run on the aerial robot cluster using neural net- works optimization regression techniques. To overcome the unplanned wind turbine network outage, an IoT micro cloud cluster system is proposed that act as immedi- ate fail-over platform to provide continuous health readings of the wind turbine to ensure the turbine in question will not get shutdown unnecessarily. The proposed system help in minimizing revenue-loss caused by stopping a wind turbine from op- eration and help maintain generated power stability on the grid. Additionally, since large wind farms require an agile and scalable management of selecting the most efficient wind turbine location install. Thus, a softwarized cognitive routing proto- col is proposed. The group of quadcopters is a redundant failover Software-Defined Network/OpenFlow system that can cover every single way point of the farm land. Although, power consumption is essential for the continuity the service, a Software- Defined charging system testbed is proposed that uses inductive power transfer wit