65 research outputs found

    Constructing Dynamic Ad-hoc Emergency Networks using Software-Defined Wireless Mesh Networks

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    Natural disasters and other emergency situations have the potential to destroy a whole network infrastructure needed for communication critical to emergency rescue, evacuation, and initial rehabilitation. Hence, the research community has begun to focus attention on rapid network reconstruction in such emergencies; however, research has tried to create or improve emergency response systems using traditional radio and satellite communications, which face high operation costs and frequent disruptions. This thesis proposes a centralized monitoring and control system to reconstruct ad-hoc networks in emergencies by using software-defined wireless mesh networks (SDWMN). The proposed framework utilizes wireless mesh networks and software-defined networking to provide real-time network monitoring services to restore Internet access in a targeted disaster zone. It dispatches mobile devices including unmanned aerial vehicles and self-driving cars to the most efficient location aggregation to recover impaired network connections by using a new GPS position finder (GPS-PF) algorithm. The algorithm is based on density-based spatial clustering that calculates the best position to deploy one of the mobile devices. The proposed system is evaluated using the common open research emulator to demonstrate its efficiency and high accessibility in emergency situations. The results obtained from the evaluation show that the performance of the emergency communication system is improved considerably with the incorporation of the framework

    FlowQoS: Per-Flow Quality of Service for Broadband Access Networks

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    Research areas: Computer NetworksIn broadband access networks, one application may compete for the bandwidth of other applications, thus degrading overall performance. One solution to this problem is to allocate bandwidth to competing flows based on the application type at the gateway of the home network. Unfortunately, application-based quality of service (QoS) on a home network gateway faces significant constraints, as commodity home routers are not typically powerful enough to perform application classification, and many home users are not savvy enough to configure QoS parameters. This paper describes FlowQoS, an SDN-based approach for application-based bandwidth allocation where users can allocate upstream and downstream bandwidths for different applications at a high level, offloading application identification to an SDN controller that dynamically installs traffic shaping rules for application flows. FlowQoS has two modules: a flow classifier and an SDNbased rate limiter. We design a custom DNS-based classifier to identify different applications that run over common web ports; a second classifier performs lightweight packet inspection to classify non-HTTP traffic flows. We implement FlowQoS on OpenWrt and demonstrate that it can improve the performance of both adaptive video streaming and VoIP in the presence of active competing traffic

    A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

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    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

    Enforcing network policy in heterogeneous network function box environment

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    Data center operators deploy a variety of both physical and virtual network functions boxes (NFBs) to take advantages of inherent efficiency offered by physical NFBs with the agility and flexibility of virtual ones. However, such heterogeneity faces great challenges in correct, efficient and dynamic network policy implementation because, firstly, existing schemes are limited to exclusively physical or virtual NFBs and not a mix, and secondly, NFBs can co-exist at various locations in the network as a result of emerging technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). In this paper, we propose a Heterogeneous netwOrk pOlicy enforCement scheme (HOOC) to overcome these challenges. We first formulate and model HOOC, which is shown be to NP-Hard by reducing from the Multiple Knapsack Problem (MKP). We then propose an efficient online algorithm that can achieve optimal latency-wise NF service chaining amongst heterogenous NFBs. In addition, we also provide a greedy algorithm when operators prefer smaller run-time than optimality. Our simulation results show that HOOC is efficient and scalable whilst testbed implementation demonstrates that HOOC can be easily deployed in the data center environments

    Intelligent management and control for Wi-Fi small cells

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    In order to face the exponential growth of mobile data transmissions, it has been long since the concept of small cells is in the table, which provides high density deployments of small cells so as to provide a high capacity to a large number of users. The SENSEFUL project, being directed by a research team in the I2CAT foundation, studies the use of small cells with Wi-Fi technology, where both the access network and the backhaul share the same radio resource. The deployment of this new paradigm requires a deep study of improvements on the performance of access networks in terms of mobility while, at the same time, trying to improve the behaviour of the backhaul network by means of new techniques to access the shared medium. SENSEFUL has been granted the funding of the WiSHFUL open call, started up by a collective of entities and universities, of which we have mainly worked with the Technische Universität Berlin, due to the use we have made of their testbed, the TWIST. Using new techniques and technologies, such as the Software Defined Networking paradigm, an intelligent network is deployed, which can manage the network resources dynamically according to the requirements of the system. Regarding both of the fronts of SENSEFUL, the performance in the backhaul network and the mobility in the access network, the techniques that were applied are the following: For the backhaul network, an innovative proposal of a shared medium access mechanism has been studied. It is not yet standardized, because there are many research teams trying to achieve a functional system that can be applied to multiple scenarios. In this thesis, the Hybrid TDMA is studied, a Wi-Fi radio medium access protocol that uses a hybrid of carrier sense (CSMA) and time division (TDMA) in order to benefit from both systems. The main advantages that HTDMA brings are a better management of the quality of service in wireless networks, while solving some of the endemic problems of Wi-Fi, such as the hidden node or the exposed node. So as to work in this direction, first of all, a precise synchronization among the devices that will use this medium access mechanism is required; that is why the usual synchronisation mechanisms in Wi-Fi networks is one of the main topics that this thesis deals with. Regarding mobility in the access network, a new technique is used, which, despite being out of the scope of this thesis, it is indeed interesting and innovative. The BigAP unifies several access points under a shared BSSID, providing a seamless handover for the clients by making only a change on the transmission channel. Working in different environments and scenarios, this project studies the best synchronisation mechanisms for this field. Moreover, the HTDMA system is installed in a small test scenario so as to begin with the analysis of the operation of this hybrid mechanism and its performance under different conditions, as compared to the legacy CSMA

    A Multi-Site NFV Testbed for Experimentation With SUAV-Based 5G Vertical Services

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    [EN] With the advent of 5G technologies, vertical markets have been placed at the forefront, as fundamental drivers and adopters of technical developments and new business models. Small Unmanned Aerial Vehicles (SUAVs) are gaining traction in multiple vertical sectors, as key assets to generate, process, and distribute relevant information for the provision of value-added services. However, the enormous potential of SUAVs to support a exible, rapid, and cost-effective deployment of vertical applications is still to be exploited. In this paper, we leverage our prior work on Network Functions Virtualization (NFV) and SUAVs to design and build a multi-site experimentation testbed based on open-source technologies. The goal of this testbed is to explore synergies among NFV, SUAVs, and vertical services, following a practical approach primarily governed by experimentation. To verify our testbed design, we realized a reference use case where a number of SUAVs, cloud infrastructures, and communication protocols are used to provide a multi-site vertical service. Our experimentation results suggest the potential of NFV and SUAVs to exibly support vertical services. The lessons learned have served to identify missing elements in our NFV platform, as well as challenging aspects for potential improvement. These include the development of speci c mechanisms to limit processing load and delays of service deployment operations.This work was supported in part by the European Commission under the European Union's Horizon 2020 program (5GRANGE Project, grant agreement number 777137), and in part by the 5GCity Project funded by the Spanish Ministry of Economy and Competitiveness under Grant TEC2016-76795-C6-1R, Grant TEC2016-76795-C6-3R, and Grant TEC2016-76795-C6-5R

    Context-based security function orchestration for the network edge

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    Over the last few years the number of interconnected devices has increased dramatically, generating zettabytes of traffic each year. In order to cater to the requirements of end-users, operators have deployed network services to enhance their infrastructure. Nowadays, telecommunications service providers are making use of virtualised, flexible, and cost-effective network-wide services, under what is known as Network Function Virtualisation (NFV). Future network and application requirements necessitate services to be delivered at the edge of the network, in close proximity to end-users, which has the potential to reduce end-to-end latency and minimise the utilisation of the core infrastructure while providing flexible allocation of resources. One class of functionality that NFV facilitates is the rapid deployment of network security services. However, the urgency for assuring connectivity to an ever increasing number of devices as well as their resource-constrained nature, has led to neglecting security principles and best practices. These low-cost devices are often exploited for malicious purposes in targeting the network infrastructure, with recent volumetric Distributed Denial of Service (DDoS) attacks often surpassing 1 terabyte per second of network traffic. The work presented in this thesis aims to identify the unique requirements of security modules implemented as Virtual Network Functions (VNFs), and the associated challenges in providing management and orchestration of complex chains consisting of multiple VNFs The work presented here focuses on deployment, placement, and lifecycle management of microservice-based security VNFs in resource-constrained environments using contextual information on device behaviour. Furthermore, the thesis presents a formulation of the latency-optimal placement of service chains at the network edge, provides an optimal solution using Integer Linear Programming, and an associated near-optimal heuristic solution that is able to solve larger-size problems in reduced time, which can be used in conjunction with context-based security paradigms. The results of this work demonstrate that lightweight security VNFs can be tailored for, and hosted on, a variety of devices, including commodity resource-constrained systems found in edge networks. Furthermore, using a context-based implementation of the management and orchestration of lightweight services enables the deployment of real-world complex security service chains tailored towards the user’s performance demands from the network. Finally, the results of this work show that on-path placement of service chains reduces the end-to-end latency and minimise the number of service-level agreement violations, therefore enabling secure use of latency-critical networks

    Accelerating orchestration with in-network offloading

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    The demand for low-latency Internet applications has pushed functionality that was originally placed in commodity hardware into the network. Either in the form of binaries for the programmable data plane or virtualised network functions, services are implemented within the network fabric with the aim of improving their performance and placing them close to the end user. Training of machine learning algorithms, aggregation of networking traffic, virtualised radio access components, are just some of the functions that have been deployed within the network. Therefore, as the network fabric becomes the accelerator for various applications, it is imperative that the orchestration of their components is also adapted to the constraints and capabilities of the deployment environment. This work identifies performance limitations of in-network compute use cases for both cloud and edge environments and makes suitable adaptations. Within cloud infrastructure, this thesis proposes a platform that relies on programmable switches to accelerate the performance of data replication. It then proceeds to discuss design adaptations of an orchestrator that will allow in-network data offloading and enable accelerated service deployment. At the edge, the topic of inefficient orchestration of virtualised network functions is explored, mainly with respect to energy usage and resource contention. An orchestrator is adapted to schedule requests by taking into account edge constraints in order to minimise resource contention and accelerate service processing times. With data transfers consuming valuable resources at the edge, an efficient data representation mechanism is implemented to provide statistical insight on the provenance of data at the edge and enable smart query allocation to nodes with relevant data. Taking into account the previous state of the art, the proposed data plane replication method appears to be the most computationally efficient and scalable in-network data replication platform available, with significant improvements in throughput and up to an order of magnitude decrease in latency. The orchestrator of virtual network functions at the edge was shown to reduce event rejections, total processing time, and energy consumption imbalances over the default orchestrator, thus proving more efficient use of the infrastructure. Lastly, computational cost at the edge was further reduced with the use of the proposed query allocation mechanism which minimised redundant engagement of nodes
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