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

Orchestration of distributed ingestion and processing of IoT data for fog platforms

In recent years there has been an extraordinary growth of the Internet of Things (IoT) and its protocols. The increasing diffusion of electronic devices with identification, computing and communication capabilities is laying ground for the emergence of a highly distributed service and networking environment. The above mentioned situation implies that there is an increasing demand for advanced IoT data management and processing platforms. Such platforms require support for multiple protocols at the edge for extended connectivity with the objects, but also need to exhibit uniform internal data organization and advanced data processing capabilities to fulfill the demands of the application and services that consume IoT data. One of the initial approaches to address this demand is the integration between IoT and the Cloud computing paradigm. There are many benefits of integrating IoT with Cloud computing. The IoT generates massive amounts of data, and Cloud computing provides a pathway for that data to travel to its destination. But today’s Cloud computing models do not quite fit for the volume, variety, and velocity of data that the IoT generates. Among the new technologies emerging around the Internet of Things to provide a new whole scenario, the Fog Computing paradigm has become the most relevant. Fog computing was introduced a few years ago in response to challenges posed by many IoT applications, including requirements such as very low latency, real-time operation, large geo-distribution, and mobility. Also this low latency, geo-distributed and mobility environments are covered by the network architecture MEC (Mobile Edge Computing) that provides an IT service environment and Cloud-computing capabilities at the edge of the mobile network, within the Radio Access Network (RAN) and in close proximity to mobile subscribers. Fog computing addresses use cases with requirements far beyond Cloud-only solution capabilities. The interplay between Cloud and Fog computing is crucial for the evolution of the so-called IoT, but the reach and specification of such interplay is an open problem. This thesis aims to find the right techniques and design decisions to build a scalable distributed system for the IoT under the Fog Computing paradigm to ingest and process data. The final goal is to explore the trade-offs and challenges in the design of a solution from Edge to Cloud to address opportunities that current and future technologies will bring in an integrated way. This thesis describes an architectural approach that addresses some of the technical challenges behind the convergence between IoT, Cloud and Fog with special focus on bridging the gap between Cloud and Fog. To that end, new models and techniques are introduced in order to explore solutions for IoT environments. This thesis contributes to the architectural proposals for IoT ingestion and data processing by 1) proposing the characterization of a platform for hosting IoT workloads in the Cloud providing multi-tenant data stream processing capabilities, the interfaces over an advanced data-centric technology, including the building of a state-of-the-art infrastructure to evaluate the performance and to validate the proposed solution. 2) studying an architectural approach following the Fog paradigm that addresses some of the technical challenges found in the first contribution. The idea is to study an extension of the model that addresses some of the central challenges behind the converge of Fog and IoT. 3) Design a distributed and scalable platform to perform IoT operations in a moving data environment. The idea after study data processing in Cloud, and after study the convenience of the Fog paradigm to solve the IoT close to the Edge challenges, is to define the protocols, the interfaces and the data management to solve the ingestion and processing of data in a distributed and orchestrated manner for the Fog Computing paradigm for IoT in a moving data environment.En els últims anys hi ha hagut un gran creixement del Internet of Things (IoT) i els seus protocols. La creixent difusió de dispositius electrònics amb capacitats d'identificació, computació i comunicació esta establint les bases de l’aparició de serveis altament distribuïts i del seu entorn de xarxa. L’esmentada situació implica que hi ha una creixent demanda de plataformes de processament i gestió avançada de dades per IoT. Aquestes plataformes requereixen suport per a múltiples protocols al Edge per connectivitat amb el objectes, però també necessiten d’una organització de dades interna i capacitats avançades de processament de dades per satisfer les demandes de les aplicacions i els serveis que consumeixen dades IoT. Una de les aproximacions inicials per abordar aquesta demanda és la integració entre IoT i el paradigma del Cloud computing. Hi ha molts avantatges d'integrar IoT amb el Cloud. IoT genera quantitats massives de dades i el Cloud proporciona una via perquè aquestes dades viatgin a la seva destinació. Però els models actuals del Cloud no s'ajusten del tot al volum, varietat i velocitat de les dades que genera l'IoT. Entre les noves tecnologies que sorgeixen al voltant del IoT per proporcionar un escenari nou, el paradigma del Fog Computing s'ha convertit en la més rellevant. Fog Computing es va introduir fa uns anys com a resposta als desafiaments que plantegen moltes aplicacions IoT, incloent requisits com baixa latència, operacions en temps real, distribució geogràfica extensa i mobilitat. També aquest entorn està cobert per l'arquitectura de xarxa MEC (Mobile Edge Computing) que proporciona serveis de TI i capacitats Cloud al edge per la xarxa mòbil dins la Radio Access Network (RAN) i a prop dels subscriptors mòbils. El Fog aborda casos d?us amb requisits que van més enllà de les capacitats de solucions només Cloud. La interacció entre Cloud i Fog és crucial per a l'evolució de l'anomenat IoT, però l'abast i especificació d'aquesta interacció és un problema obert. Aquesta tesi té com objectiu trobar les decisions de disseny i les tècniques adequades per construir un sistema distribuït escalable per IoT sota el paradigma del Fog Computing per a ingerir i processar dades. L'objectiu final és explorar els avantatges/desavantatges i els desafiaments en el disseny d'una solució des del Edge al Cloud per abordar les oportunitats que les tecnologies actuals i futures portaran d'una manera integrada. Aquesta tesi descriu un enfocament arquitectònic que aborda alguns dels reptes tècnics que hi ha darrere de la convergència entre IoT, Cloud i Fog amb especial atenció a reduir la bretxa entre el Cloud i el Fog. Amb aquesta finalitat, s'introdueixen nous models i tècniques per explorar solucions per entorns IoT. Aquesta tesi contribueix a les propostes arquitectòniques per a la ingesta i el processament de dades IoT mitjançant 1) proposant la caracterització d'una plataforma per a l'allotjament de workloads IoT en el Cloud que proporcioni capacitats de processament de flux de dades multi-tenant, les interfícies a través d'una tecnologia centrada en dades incloent la construcció d'una infraestructura avançada per avaluar el rendiment i validar la solució proposada. 2) estudiar un enfocament arquitectònic seguint el paradigma Fog que aborda alguns dels reptes tècnics que es troben en la primera contribució. La idea és estudiar una extensió del model que abordi alguns dels reptes centrals que hi ha darrere de la convergència de Fog i IoT. 3) Dissenyar una plataforma distribuïda i escalable per a realitzar operacions IoT en un entorn de dades en moviment. La idea després d'estudiar el processament de dades a Cloud, i després d'estudiar la conveniència del paradigma Fog per resoldre el IoT prop dels desafiaments Edge, és definir els protocols, les interfícies i la gestió de dades per resoldre la ingestió i processament de dades en un distribuït i orquestrat per al paradigma Fog Computing per a l'IoT en un entorn de dades en moviment

Open Platforms for Connected Vehicles

L'abstract è presente nell'allegato / the abstract is in the attachmen

자율주행을 위한 V2X 기반 차량 CDN 설계

학위논문 (석사) -- 서울대학교 대학원 : 공학전문대학원 응용공학과, 2021. 2. 김성우.Recent technical innovation has driven the evolution of autonomous vehicles. To improve safety as well as on-road vehicular experience, vehicles should be connected with each other or to vehicular networks. Some specification groups, e.g., IEEE and 3GPP, have studied and released vehicular communication requirements and architecture. IEEEs Wireless Access in Vehicular Environment focuses on dedicated and short-range communication, while 3GPPs New radio V2X supports not only sidelink but also uplink communication. The 3GPP Release 16, which supports 5G New Radio, offers evolved functionalities such as network slice, Network Function Virtualization, and Software-Defined Networking. In this study, we define and design a vehicular network architecture compliant with 5G core networks. For localization of autonomous driving vehicles, a high-definition map needs to contain the context of trajectory . We also propose new methods by which autonomous vehicles can push and pull map content efficiently, without causing bottlenecks on the network core. We evaluate the performance of V2X and of the proposed caching policy via network simulations. Experimental results indicate that the proposed method improves the performance of vehicular content delivery in real-world road environments.최근들어 기술의 혁신은 자율주행 자동차의 발전을 가속화 하고 있다. 보다 높은 수준의 자율 주행을 구현하기 위해서, 차량은 네트워크를 통해 서로 연결되어 있어야 하고 차량의 안전과 편의성을 향상 시킬 수 있도록 정보를 공유 할 수 있어야 한다. 표준화 단체인 IEEE와 3GPP는 차량 통신 요구사항, 아키텍처를 연구하고 개정해왔다. IEEE가 전용 채널을 통한 근접 지역 통신에 초점을 맞추는 반면에, 3GPP의 New Radio V2X는 Sidelink 뿐만 아니라 Uplink 통신을 동시에 지원한다. 5G 통신을 지원하는 3GPP Release 16은 Network Slice, NFV, SDN과 같은 새로운 통신 기능들을 제공한다. 이 연구에서는 새롭게 정의된 5G Core Network Architecture를 바탕으로 차량 네트워크를 정의하고 설계하였다. 자율주행 자동차의 측위를 위해서, 고해상도 지도는 각 구성요소들의 의미와 속성을 자세하게 포함하고 있어야 한다. 우리는 이 연구에서 V2X 네트워크 상에 HD map을 중계할 수 있는 Edge Server를 제안 함으로써, 중앙에서 발생할 수 있는 병목현상을 줄이고 전송 Delay를 최소화한다. 또한 Edge의 컨텐츠를 등록하고 삭제하는 정책으로 기존의 LRU, LFU가 아닌 새로운 컨텐츠 교체 알고리즘을 제안하였다. 실제 주행 시험과 시뮬레이션을 통한 실험을 통해 전송 품질을 향상시켰으며, Edge 컨텐츠의 활용도를 높였다.I. Introduction 1 II. Related Works 6 2.1 V2X Standardization 6 2.1.1 IEEE WAVE 6 2.1.2 3GPP C-V2X 9 2.2 Geographic Contents 14 2.3 Vehicular Content Centric Network 17 III. System Modeling 20 3.1 NR-V2X Architecture Analysis 20 3.2 Caching Strategy for HD Map Acquisition 23 IV. Evaluation 30 4.1 Contents Replacement Strategy 30 4.2 V2X Characteristics 36 4.3 Edge Performance in Driving on the Road 38 4.4 Edge Performance on 3D Point Clouds Caching for Localization 44 V. Conclusion 47 Bibliography 49 Abstract 54Maste

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Failure Analysis in Next-Generation Critical Cellular Communication Infrastructures

The advent of communication technologies marks a transformative phase in critical infrastructure construction, where the meticulous analysis of failures becomes paramount in achieving the fundamental objectives of continuity, security, and availability. This survey enriches the discourse on failures, failure analysis, and countermeasures in the context of the next-generation critical communication infrastructures. Through an exhaustive examination of existing literature, we discern and categorize prominent research orientations with focuses on, namely resource depletion, security vulnerabilities, and system availability concerns. We also analyze constructive countermeasures tailored to address identified failure scenarios and their prevention. Furthermore, the survey emphasizes the imperative for standardization in addressing failures related to Artificial Intelligence (AI) within the ambit of the sixth-generation (6G) networks, accounting for the forward-looking perspective for the envisioned intelligence of 6G network architecture. By identifying new challenges and delineating future research directions, this survey can help guide stakeholders toward unexplored territories, fostering innovation and resilience in critical communication infrastructure development and failure prevention

5G-MEC Testbeds for V2X Applications

Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low latency and high computational capabilities at the network’s edge. To meet these requirements, ETSI standardized Multi-access Edge Computing (MEC), which provides cloud computing capabilities and addresses the need for low latency. This paper presents a generalized overview for implementing a 5G-MEC testbed for Vehicle-to-Everything (V2X) applications, as well as the analysis of some important testbeds and state-of-the-art implementations based on their deployment scenario, 5G use cases, and open source accessibility. The complexity of using the testbeds is also discussed, and the challenges researchers may face while replicating and deploying them are highlighted. Finally, the paper summarizes the tools used to build the testbeds and addresses open issues related to implementing the testbeds.publishedVersio