Multi-Connectivity Management and Orchestration Architecture Integrated With 5g Multi Radio Access Technology Network

The significant growth in the number of devices and the tremendous boost in network/user traffic types and volume as well as the efficiency constraints of 4G innovations have encouraged industry efforts and also financial investments towards defining, developing, and releasing systems for the fifth generation. The 5G of mobile broadband wireless networks with multiple Radio Access Technologies (Multi-RATs) have actually been designed to satisfy the system and service requirements of the existing as well as the coming applications. The multi-RAT access network is considered the key enabling technology to satisfy these requirements based on low latency, high throughput. To utilize all available network resources efficiently, research activities have been proposed on multi-connectivity to connect, split, steer, switch, and orchestrate across multiple RATs. Recently, multi-connectivity management and orchestration architecture standardization has just started; therefore, further study and research is needed. This project proposed a multi-connectivity management and orchestration architecture integrated with 5G, Long-Term Evolution (LTE), and Wireless LANs (WLAN) technologies. The simulations experiments conducted to measure the Quality of Experience (QoE) by provisioning network resources efficiently, which are: data rate, latency, bit error rate. The results show that the 5G requirements have been achieved with latency and throughput around 1ms and 200 Mbps, respectively

Network Selection Problems - QoE vs QoS Who is the Winner?

In network selection problem (NSP), there are now two schools of thought. There are those who think using QoE (Quality of Experience) is the best yardstick to measure the suitability of a Candidate Network (CN) to handover to. On the other hand, Quality of Service (QoS) is also advocated as the solution for network selection problems. In this article, a comprehensive framework that supports effective and efficient network selection is presented. The framework   attempts to provide a holistic solution to network selection problem that is achieved by combining both of the QoS and QoE measures.   Using this hybrid solution the best qualities in both methods are combined to overcome issues of the network selection problem According to ITU-R (International Telecommunications Union – Radio Standardization Sector), a 4G network is defined as having peak data rates of 100Mb/s for mobile nodes with speed up to 250 km/hr and 1Gb/s for mobile nodes moving at pedestrian speed. Based on this definition, it is safe to say that mobile nodes that can go from pedestrian speed to speed of up to 250 km/hr will be the norm in future. This indicates that the MN’s mobility will be highly dynamic. In particular, this article addresses the issue of network selection for high speed Mobile Nodes (MN) in 4G networks. The framework presented in this article also discusses how the QoS value collected from CNs can be fine-tuned to better reflect an MN’s current mobility scenario

Network-aware video streaming for future media Internet

272 p

An innovative machine learning-based scheduling solution for improving live UHD video streaming quality in highly dynamic network environments

The latest advances in terms of network technologies open up new opportunities for high-end applications, including using the next generation video streaming technologies. As mobile devices become more affordable and powerful, an increasing range of rich media applications could offer a highly realistic and immersive experience to mobile users. However, this comes at the cost of very stringent Quality of Service (QoS) requirements, putting significant pressure on the underlying networks. In order to accommodate these new rich media applications and overcome their associated challenges, this paper proposes an innovative Machine Learning-based scheduling solution which supports increased quality for live omnidirectional (360◦) video streaming. The proposed solution is deployed in a highly dy-namic Unmanned Aerial Vehicle (UAV)-based environment to support immersive live omnidirectional video streaming to mobile users. The effectiveness of the proposed method is demonstrated through simulations and compared against three state-of-the-art scheduling solutions, such as: Static Prioritization (SP), Required Activity Detection Scheduler (RADS) and Frame Level Scheduler (FLS). The results show that the proposed solution outperforms the other schemes involved in terms of PSNR, throughput and packet loss rate

Definition and specification of connectivity and QoE/QoS management mechanisms – final report

This document summarizes the WP5 work throughout the project, describing its functional architecture and the solutions that implement the WP5 concepts on network control and orchestration. For this purpose, we defined 3 innovative controllers that embody the network slicing and multi tenancy: SDM-C, SDM-X and SDM-O. The functionalities of each block are detailed with the interfaces connecting them and validated through exemplary network processes, highlighting thus 5G NORMA innovations. All the proposed modules are designed to implement the functionality needed to provide the challenging KPIs required by future 5G networks while keeping the largest possible compatibility with the state of the art