Performance Analysis of Wireless Networks with QoS Adaptations

The explosive demand for multimedia and fast transmission of continuous media on wireless networks means the simultaneous existence of traffic requiring different qualities of service (QoS). In this thesis, several efficient algorithms have been developed which offer several QoS to the end-user. We first look at a request TDMA/CDMA protocol for supporting wireless multimedia traffic, where CDMA is laid over TDMA. Then we look at a hybrid push-pull algorithm for wireless networks, and present a generalized performance analysis of the proposed protocol. Some of the QoS factors considered include customer retrial rates due to user impatience and system timeouts and different levels of priority and weights for mobile hosts. We have also looked at how customer impatience and system timeouts affect the QoS provided by several queuing and scheduling schemes such as FIFO, priority, weighted fair queuing, and the application of the stretch-optimal algorithm to scheduling

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

An adaptive framework for end-to-end quality of service management

Ph.DDOCTOR OF PHILOSOPH

Integration of unidirectional technologies into wireless back-haul architecture

This thesis was submitted for the degree of Docter of Philosophy and awarded by Brunel University.Back-haul infrastructures of today's wireless operators must support the triple-play services demanded by the market or regulatory bodies. To cope with increasing capacity demand, the EU FP7 project CARMEN has developed a cost-effective heterogeneous multi-radio wireless back-haul architecture, which may also leverage the native multicast capabilities of broadcast technologies such as DVB-T to off-load high-bandwidth broadcast content delivery. However, the integration of such unidirectional technologies into a packet-switched architecture requires careful considerations. The contribution of this thesis is the investigation, design and evaluation of protocols and mechanisms facilitating the integration of such unidirectional technologies into the wireless back-haul architecture so that they can be configured and utilized by the spectrum and capacity optimization modules. This integration mainly concerns the control plane and, in particular, the aspects related to resource and capability descriptions, neighborhood, link and Multi Protocol Label Switching (MPLS) Label-Switched Path (LSP) monitoring, unicast and multicast LSP signalling as well as topology forming and maintenance. During the course of this study we have analyzed the problem space, proposed solutions to the resulting research questions and evaluated our approach. Our results show that the now Unidirectional Technology (UDT)-aware architecture can readily consider Unidirectional Technologies (UDTs) to distribute, for example, broadcast content

Model-based provisioning and management of adaptive distributed communication in mobile cooperative systems

Adaptation of communication is required to maintain the reliable connection and to ensure the minimum quality in collaborative activities. Within the framework of wireless environment, how can host entities be handled in the event of a sudden unexpected change in communication and reliable sources? This challenging issue is addressed in the context of Emergency rescue system carried out by mobile devices and robots during calamities or disaster. For this kind of scenario, this book proposes an adaptive middleware to support reconfigurable, reliable group communications. Here, the system structure has been viewed at two different states, a control center with high processing power and uninterrupted energy level is responsible for global task and entities like autonomous robots and firemen owning smart devices act locally in the mission. Adaptation at control center is handled by semantic modeling whereas at local entities, it is managed by a software module called communication agent (CA). Modeling follows the well-known SWRL instructions which establish the degree of importance of each communication link or component. Providing generic and scalable solutions for automated self-configuration is driven by rule-based reconfiguration policies. To perform dynamically in changing environment, a trigger mechanism should force this model to take an adaptive action in order to accomplish a certain task, for example, the group chosen in the beginning of a mission need not be the same one during the whole mission. Local entity adaptive mechanisms are handled by CA that manages internal service APIs to configure, set up, and monitors communication services and manages the internal resources to satisfy telecom service requirements

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

[DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; García-García, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

Quality-aware Content Adaptation in Digital Video Streaming

User-generated video has attracted a lot of attention due to the success of Video Sharing Sites such as YouTube and Online Social Networks. Recently, a shift towards live consumption of these videos is observable. The content is captured and instantly shared over the Internet using smart mobile devices such as smartphones. Large-scale platforms arise such as YouTube.Live, YouNow or Facebook.Live which enable the smartphones of users to livestream to the public. These platforms achieve the distribution of tens of thousands of low resolution videos to remote viewers in parallel. Nonetheless, the providers are not capable to guarantee an efficient collection and distribution of high-quality video streams. As a result, the user experience is often degraded, and the needed infrastructure installments are huge. Efficient methods are required to cope with the increasing demand for these video streams; and an understanding is needed how to capture, process and distribute the videos to guarantee a high-quality experience for viewers. This thesis addresses the quality awareness of user-generated videos by leveraging the concept of content adaptation. Two types of content adaptation, the adaptive video streaming and the video composition, are discussed in this thesis. Then, a novel approach for the given scenario of a live upload from mobile devices, the processing of video streams and their distribution is presented. This thesis demonstrates that content adaptation applied to each step of this scenario, ranging from the upload to the consumption, can significantly improve the quality for the viewer. At the same time, if content adaptation is planned wisely, the data traffic can be reduced while keeping the quality for the viewers high. The first contribution of this thesis is a better understanding of the perceived quality in user-generated video and its influencing factors. Subjective studies are performed to understand what affects the human perception, leading to the first of their kind quality models. Developed quality models are used for the second contribution of this work: novel quality assessment algorithms. A unique attribute of these algorithms is the usage of multiple features from different sensors. Whereas classical video quality assessment algorithms focus on the visual information, the proposed algorithms reduce the runtime by an order of magnitude when using data from other sensors in video capturing devices. Still, the scalability for quality assessment is limited by executing algorithms on a single server. This is solved with the proposed placement and selection component. It allows the distribution of quality assessment tasks to mobile devices and thus increases the scalability of existing approaches by up to 33.71% when using the resources of only 15 mobile devices. These three contributions are required to provide a real-time understanding of the perceived quality of the video streams produced on mobile devices. The upload of video streams is the fourth contribution of this work. It relies on content and mechanism adaptation. The thesis introduces the first prototypically evaluated adaptive video upload protocol (LiViU) which transcodes multiple video representations in real-time and copes with changing network conditions. In addition, a mechanism adaptation is integrated into LiViU to react to changing application scenarios such as streaming high-quality videos to remote viewers or distributing video with a minimal delay to close-by recipients. A second type of content adaptation is discussed in the fifth contribution of this work. An automatic video composition application is presented which enables live composition from multiple user-generated video streams. The proposed application is the first of its kind, allowing the in-time composition of high-quality video streams by inspecting the quality of individual video streams, recording locations and cinematographic rules. As a last contribution, the content-aware adaptive distribution of video streams to mobile devices is introduced by the Video Adaptation Service (VAS). The VAS analyzes the video content streamed to understand which adaptations are most beneficial for a viewer. It maximizes the perceived quality for each video stream individually and at the same time tries to produce as little data traffic as possible - achieving data traffic reduction of more than 80%