Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results

Context-Awareness Enhances 5G Multi-Access Edge Computing Reliability

The fifth generation (5G) mobile telecommunication network is expected to support Multi- Access Edge Computing (MEC), which intends to distribute computation tasks and services from the central cloud to the edge clouds. Towards ultra-responsive, ultra-reliable and ultra-low-latency MEC services, the current mobile network security architecture should enable a more decentralized approach for authentication and authorization processes. This paper proposes a novel decentralized authentication architecture that supports flexible and low-cost local authentication with the awareness of context information of network elements such as user equipment and virtual network functions. Based on a Markov model for backhaul link quality, as well as a random walk mobility model with mixed mobility classes and traffic scenarios, numerical simulations have demonstrated that the proposed approach is able to achieve a flexible balance between the network operating cost and the MEC reliability.Comment: Accepted by IEEE Access on Feb. 02, 201

OpenEPC Integration within 5GTN as an NFV proof of concept

Abstract. Gone are the days, when a hardware is changed on every malfunctioning and the whole operation either stays down or load on the replacing hardware becomes too much which ultimately compromises the QoS. The IT industry is mature enough to tackle problems regarding scalability, space utilization, energy consumption, cost, agility and low availability. The expected throughput and network latency with 5G in the cellular Telecommunication Networks seems to be unachievable with the existing architecture and resources. Network Function Virtualization promises to merge IT and Telecommunications in such an efficient way that the expected results could be achieved no longer but sooner. The thesis work examines the compatibility and flexibility of a 3GPP virtual core network in a virtualization platform. The testbed is established on an LTE (Long Term Evolution) based network being already deployed and OpenEPC is added as virtual core network on it. The integration of OpenEPC in 5GTN (5TH Generation Test Network) is discussed in details in the thesis which will give an account of the possibility of implementing such a simulated vEPC (Virtual Evolved Packet Core) in a real network platform. The deployed setup is tested to check its feasibility and flexibility for a platform which could be used for NFV deployment in future. The monitoring of OpenEPC’s individual components while utilizing the major resources within them, forms the primary performance test. The CPU Load and Memory Utilization is tested on different CPU stress levels having a constant data traffic from actual UEs. At the completion of the thesis work, a consensus is built up based on the test results that the test setup can hold number of subscribers to a certain amount without any performance degradation. Moreover, the virtual core network throughput and network latency is also compared to the commercial LTE networks and theoretical maximum values on similar resources to check performance consistency OpenEPC must offer

Integration of LoRa Wide Area Network with the 5G Test Network

Abstract. The global communication network is going through major transformation from conventional to more versatile and diversified network approaches. With the advent of virtualization and cloud technology, information technology (IT) is merging with telecommunications to alter the conventional approaches of traditional proprietary networking techniques. From radio to network and applications, the existing infrastructure lacks several features that we wished to be part of 5th Generation Mobile Networks (5G). Having a support for large number of applications, Internet of Things (IoT) will bring a major evolution by creating a comfortable, flexible and an automated environment for end users. A network having the capability to support radio protocols on top of basic networking protocols, when blended with a platform which can generate IoT use cases, can make the expectations of 5G a reality. Low Power Wide Area Network (LPWAN) technologies can be utilized with other emerging and suitable technologies for IoT applications. To implement a network where all the technologies can be deployed virtually to serve their applications within a single cloud, Network Functions Virtualization (NFV) and Software Defined Network (SDN) is introduced to implement such a networking possibility for upcoming technologies. The 5G Test Network (5GTN), a testbed for implementing and testing 5G features in real time, is deployed in virtual platform which allows to add other technologies for IoT applications. To implement a network with an IoT enabler technology, LoRa Wide Area Network (LoRaWAN) technology can be integrated to test the feasibility and capability of IoT implications. LoRaWAN being an IoT enabler technology is chosen out of several possibilities to be integrated with the 5GTN. Using MultiConnect Conduit as a gateway, the integration is realized by establishing point to point protocol (PPP) connection with eNodeB. Once the connection is established, LoRa packets are forwarded to the ThingWorx IoT cloud and responses can be received by the end-devices from that IoT cloud by using Message Queuing Telemetry Transport (MQTT) protocol. Wireshark, an open source packet analyser, is then used to ensure successful transmission of packets to the ThingWorx using the 5GTN default packet routes

Efficient Service for Next Generation Network Slicing Architecture and Mobile Traffic Analysis Using Machine Learning Technique

The tremendous growth of mobile devices, IOT devices, applications and many other services have placed high demand on mobile and wireless network infrastructures. Much research and development of 5G mobile networks have found the way to support the huge volume of traffic, extracting of fine-gained analytics and agile management of mobile network elements, so that it can maximize the user experience. It is very challenging to accomplish the tasks as mobile networks increase the complexity, due to increases in the high volume of data penetration, devices, and applications. One of the solutions, advance machine learning techniques, can help to mitigate the large number of data and algorithm driven applications. This work mainly focus on extensive analysis of mobile traffic for improving the performance, key performance indicators and quality of service from the operations perspective. The work includes the collection of datasets and log files using different kind of tools in different network layers and implementing the machine learning techniques to analyze the datasets to predict mobile traffic activity. A wide range of algorithms were implemented to compare the analysis in order to identify the highest performance. Moreover, this thesis also discusses about network slicing architecture its use cases and how to efficiently use network slicing to meet distinct demands

5G network end-to-end delay measurements for live video streaming

Abstract. Focus of this thesis is in the data transmission delay comparison between Edge server and Cloud server when utilizing either 4G or 5G connectivity. In previous mobile phone network generations for example a multimedia server had to be installed on a Cloud server in the internet. 5G mobile phone network introduces a new concept called Edge server. Edge server is located close to the base station and therefore it is assumed to shorten the data transmission delay between the 5G mobile/client and a server application. Edge server can be used both in 4G and 5G networks. In this thesis first the 5G network and the essential new 5G architecture main design principles are gone through. Next the 5G Test Network that is used as a test environment is described and 5G main modules like Multi-access Edge Computing are introduced. 5G performance is clarified and compared against 4G. Delay testing is done in the 5G Test Network using Hospital Use Case demo. There operating room personnel like doctors and nurses is wearing Augmented Reality glasses and they are streaming their view together with patient status related information to multimedia server residing in 5G Test Network Edge server or in internet cloud. From the multimedia server the video is streamed by for example students, medical experts or consultants in a remote location. As part of the thesis the test system is defined and built based on the Hospital Use Case demo. Test specification is created, and tests are executed according to it. Results are recorded and analysed. Data transmission delays between the video stream originator and multimedia server are measured using Qosium measurement system. Also delay between the multimedia server and the streaming client is measured. Measurements are done for configurations where multimedia server is located at the Edge server and the internet cloud server. Both 4G and 5G connectivity is used for both server locations. When delay measurement results were compared it became clear that Edge server has much shorter data transmission delays compared to the internet cloud server. With 5G connectivity the delay was measured to be around 10 milliseconds for both uplink and downlink. With internet cloud the delays varied between 31 and 45 milliseconds with 5G connection. It can be concluded that from today’s mobile phone networks, 5G network does offer the fastest connection to a server environment by utilizing Edge server.5G verkon viiveen mittaaminen videostriimille. Tiivistelmä. Tämä diplomityö keskittyy vertaamaan datatiedonsiirron eroja reunapalvelimen ja internetin pilvipalvelimen välillä 4G ja 5G matkapuhelinverkossa. Aiempien sukupolvien matkapuhelinverkoissa esimerkiksi multimediapalvelin oli asennettava internetin pilvipalvelimelle. Viidennen sukupolven matkapuhelinverkossa otetaan käyttöön reunapalvelin. Reunapalvelin sijaitsee tukiaseman läheisyydessä ja täten sen oletetaan lyhentävän 5G-päätelaitteen ja palvelimen sovelluksen välistä tiedonsiirtoviivettä. Reunapalvelinta voidaan käyttää sekä neljännen että viidennen sukupolven matkapuhelinverkoissa. Tässä diplomityössä käydään ensin läpi 5G-matkapuhelinverkko ja sen arkkitehtuurin pääsuunnittelukriteerit. Seuraavaksi kuvataan testaamisessa käytettävä 5G-testiverkko ja 5G-verkon tärkeimmät moduulit kuten Multi-access Edge Computing. 5G-verkon suorituskyky selitetään ja sitä verrataan edelliseen 4. sukupolven verkkoon. Viivemittaukset tehdään 5G testiverkossa käyttäen 5G lääketieteen käyttötapauksen demoympäristöä. Siinä operointihuoneen henkilöstöllä, kuten lääkäreillä ja hoitajilla, on yllään lisätyn todellisuuden lasit. Lasit lähettävät henkilön näkymän ja potilaaseen liittyvää tietoa 5G-testiverkon reunapalvelimella tai internetin pilvipalvelimella sijaitsevalle multimediapalvelimelle. Multimediapalvelimelta video striimataan esimerkiksi lääketieteen opiskelijoille, asiantuntijoille tai konsulteille, jotka ovat etäällä lähetyspaikasta. Osana diplomityötä määritellään ja rakennetaan lääketieteen käyttötapauksen demon perustuva testausjärjestelmä. Testispesifikaatio luodaan, testit suoritetaan sen perusteella. Testitulokset tallennetaan ja analysoidaan. Tiedonsiirtoviiveet videolähteen ja multimediapalvelimen välillä mitataan käyttäen Qosium mittausjärjestelmää. Myös multimediapalvelimen ja videostriimin vastaanottajan väliset viiveet mitataan. Mittaukset tehdään konfiguraatiolle, jossa multimediapalvelin on sijoitettu reunapalvelimelle ja konfiguraatiolle, jossa se on sijoitettu internetin pilvipalvelimelle. Sekä 4G että 5G-yhteyttä käytetään molemmille konfiguraatiolle. Kun mittaustuloksia verrataan, käy selväksi, että reunapalvelimella on huomattavasti lyhyempi tiedonsiirtoviive kuin internetin pilvipalvelimella. 5G-yhteydellä mitattu viive oli noin 10 ms sekä ylössyöttö- että alassyöttösuuntaan. Internetin pilvipalvelimella viiveet vaihtelivat 31 ja 45 millisekunnin välillä 5G-yhteydellä. Voidaankin todeta, että nykyisistä matkapuhelinverkoista 5G-verkko tarjoaa nopeimman yhteyden palvelinympäristöön reunapalvelimen avulla