20 research outputs found

    Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

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    The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels

    Quality of service differentiation for multimedia delivery in wireless LANs

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    Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below: 1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss. 2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system. 3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic

    From serendipity to sustainable Green IoT: technical, industrial and political perspective

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    Recently, Internet of Things (IoT) has become one of the largest electronics market for hardware production due to its fast evolving application space. However, one of the key challenges for IoT hardware is the energy efficiency as most of IoT devices/objects are expected to run on batteries for months/years without a battery replacement or on harvested energy sources. Widespread use of IoT has also led to a largescale rise in the carbon footprint. In this regard, academia, industry and policy-makers are constantly working towards new energy-efficient hardware and software solutions paving the way for an emerging area referred to as green-IoT. With the direct integration and the evolution of smart communication between physical world and computer-based systems, IoT devices are also expected to reduce the total amount of energy consumption for the Information and Communication Technologies (ICT) sector. However, in order to increase its chance of success and to help at reducing the overall energy consumption and carbon emissions a comprehensive investigation into how to achieve green-IoT is required. In this context, this paper surveys the green perspective of the IoT paradigm and aims to contribute at establishing a global approach for green-IoT environments. A comprehensive approach is presented that focuses not only on the specific solutions but also on the interaction among them, and highlights the precautions/decisions the policy makers need to take. On one side, the ongoing European projects and standardization efforts as well as industry and academia based solutions are presented and on the other side, the challenges, open issues, lessons learned and the role of policymakers towards green-IoT are discussed. The survey shows that due to many existing open issues (e.g., technical considerations, lack of standardization, security and privacy, governance and legislation, etc.) that still need to be addressed, a realistic implementation of a sustainable green-IoT environment that could be universally accepted and deployed, is still missing

    A survey of cognitive radio handoff schemes, challenges and issues for industrial wireless sensor networks (CR-IWSN)

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    Industrial wireless sensor network (IWSN) applications are mostly time-bound, mission-critical and highly delay sensitive applications therefore IWSN defines strict, stringent and unique QoS requirements such as timeliness, reliability and availability. In IWSN, unlike other sensor networks, late arrival of packets or delay or disruption to an on-going communication are considered as critical failure. Also, because IWSN is deployed in the overcrowded industrial, scientific, and medical (ISM) band it is difficult to meet this unique QoS requirements due to stiff competition for bandwidth from other technologies operating in ISM band resulting in scarcity of spectrum for reliable communication and/or disruption of ongoing communication. However, cognitive radio (CR) provides more spectral opportunities through opportunistic-use of unused licensed spectrum while ensuring minimal interference to licensed users. Similarly, spectrum handoff, which is a new type of handoff in cognitive radio, has the potential to offer increase bandwidth, reliable, smooth and interference-free communication for IWSNs through opportunistic-use of spectrum, minimal switching-delays, and efficient target channel selection strategies as well as effective link recovery maintenance. As a result, a new paradigm known as cognitive radio industrial wireless sensor network (CR-IWSN) has become the interest of recent research efforts. In this paper, we highlight and discuss important QoS requirements of IWSN as well as efforts of existing IWSN standards to address the challenges. We discuss the potential and how cognitive radio and spectrum handoff can be useful in the attempt to provide real-time reliable and smooth communication for IWSNs.The Council for Scientific and Industrial Research (CSIR), South Africa [ICT: Meraka].http://www.elsevier.com/locate/jnca2018-11-01hj2017Electrical, Electronic and Computer Engineerin

    Support of resource-aware vertical handovers in WLAN hotspots

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    Endgeräte wie Smartphones oder Tablets bieten häufig eine Vielfalt drahtloser Zugänge zum Internet an. Üblicherweise schließt dies die 802.11 WLANs und auch Technologien drahtloser Weitverkehrsnetze (WWANs) aus dem Bereich LTE oder WiMAX ein. Aufgrund dieser Optionen haben sich die Endanwender daran gewöhnt, überall und zu jeder Zeit auf ihre Internetdienste zuzugreifen. Damit hat auch der Datenverkehr pro Anwender zugenommen, was eine Herausforderung insbesondere für die Betreiber von WWANs ist. Soweit verfügbar, favorisieren Endanwender heutzutage eher einen drahtlosen Zugang zum Internet über WLANs als über WWANs. Des Weiteren haben die 3GPP-Standardisierungsgremien Ansätze erarbeitet, die zusätzlich Verkehr aus WWANs in Netze mit geringerer Abdeckung wie WLAN- oder Femto-Zellen abgeben. Solche Ansätze werden auch als "Traffic Offloading" bezeichnet und haben das Ziel, die WWANs zu entlasten. Dabei werden jedoch eher einfache Strategien verfolgt, die auf der Nutzung zusätzlicher Kapazitäten heterogener Netze beruhen und dann angewendet werden, wenn ein alternatives Zugangsnetz für ein Endgerät verfügbar ist. Im Rahmen dieser Arbeit zeigen wir Gewinne auf, die entstehen, wenn man die Auswahl der Endgeräte für ein WLAN-Netz stattdessen auf Basis der von ihnen belegten Ressourcen durchführt. In diesem Kontext schlagen wir vor, Geräte mit stark negativem Einfluss auf die WLAN-Kapazität wieder zurück in das WWAN zu reichen, was wir als "Onloading" bezeichnen. Ein solches "Onloading" zieht Herausforderungen in unterschiedlichen Richtungen mit sich. Die fortschreitende Miniaturisierung hat in den letzten Jahren zu dem Trend geführt, die Anzahl der Netzwerkkarten (NICs) in Endgeräten zu reduzieren. Wir bezeichnen eine NIC als multimodal, wenn sie mehrere Funktechnologien unterstützt, aber zu einem bestimmten Zeitpunkt immer nur eine davon genutzt werden kann. Deswegen stellt für eine multimodale NIC das "Onloading" während einer laufenden Verbindung eine Herausforderung dar. Wir schlagen einen Ansatz vor, der vorbereitende Mechanismen für ein "Onloading" als auch eine laufende Verbindung im WLAN über eine solche NIC ermöglicht. Des Weiteren ist es wichtig, in einem WLAN Hotspot zu entscheiden, welche Geräte einen negativen Einfluss auf die Kapazität des Netzes haben. Dafür haben wir eine Metrik entwickelt, die eine Entscheidungsgrundlage für das Onloading bildet. Diese Metrik basiert rein auf einer Beobachtung des Netzes und seiner Geräte, ermöglicht jedoch keine Entscheidung für sich neu assoziierende Geräte im WLAN. Erschwerend kommt hinzu, dass viele Eigenschaften der NICs durch herstellerabhängige Implementierungen geprägt werden. Solche Algorithmen bieten eine zusätzliche Herausforderung, da ihre internen Abläufe üblicherweise unbekannt sind. Ein bekanntes Beispiel für solche Algorithmen stellt die Anpassung der WLAN-Link-Datenraten dar. Diese Algorithmen wählen die jeweiligen Modulations- und Kodierungsschemata (MCSs) für die drahtlosen Übertragungen aus. Robuste MCSs resultieren dabei in geringere Link-Datenraten und haben somit einen starken Einfluss auf die Kapazität einer WLAN-Zelle. Aus diesem Grund fokussieren wir uns auf eine Abschätzung der Datenratenwahl eines Endgerätes. Damit lassen sich im Vorfeld Aussagen treffen, ob ein Gerät starken Einfluss auf die WLAN-Kapazität haben wird, so dass es für ein "Onloading" in Frage kommt.End-user devices such as smart phones and tablets have become very popular as they offer a variety of wireless Internet accesses ranging from the WLAN standards to WWAN technologies such as LTE or even WiMAX. Due to these different wireless access options and new emerging applications—e.g., from the areas of video streaming, social networks, as well as Internet clouds—people are increasingly connecting to the Internet with their de- vices while being on the move. In line with this, the number of devices as well as the traffic demand of end users have been reported to increase rapidly over the last years which imposes a strong challenge especially for the operators of WWANs. Thereby, end users frequently tend to use settings that favor a connectivity to the Internet whenever possible rather over WLAN than over WWAN access. Further, the cellular standardization bodies of the 3GPP envision solutions to hand over on-going wireless sessions from cellular to other small cell accesses such as WLANs or femto cells. This is also known as traffic offloading essentially freeing capacity in terms of users with a certain service in the cellular accesses. Nevertheless this offloading follows a rather simple strategy to utilize additional capacity of heterogeneous accesses such as WLANs whenever being available for a given device. This thesis shows that stronger gains can be expected if the selection of devices to be served in WLANs is conducted in a resource-aware fashion including an evaluation of the WLAN traffic in terms of the channel occupation time and MAC overhead as result of contention, interference, and fluctuating channels. In this context, this thesis envisions to onload unfavorable devices negatively affecting the WLAN capacity back to WWAN accesses. A support of such an onloading imposes challenges in different dimensions. From the hardware design of devices, there is a strong trend to limit the number of separate network interface cards (NICs) due to space and cost issues. We refer to a multi-mode NIC if it covers multiple technologies, while at a given time only access to one technology is possible. Thus, smoothly onloading a device with such a NIC is by far not trivial. We present an approach that conducts handover preparation mechanisms, while also allowing a continuous WLAN communication over a multi-mode NIC. Further, it is by far not trivial to judge which subset of associated devices is negatively affecting the capacity of a WLAN hotspot. Thus, a careful evaluation of devices regarding a selection for an onloading back to WWAN accesses imposes a challenge yet. In this direction, we present a performance metric that identifies devices degrading the WLAN capacity. While our performance metric tackles a reactive selection, it falls short to support a predictive evaluation, e.g., of devices which just joined the WLAN cell. Even worse, proprietary algorithms inside a WLAN stack impose a severe challenge as their internal routines are usually not conveyed via typical management interfaces. A well-known example for this category of algorithms are the link data rate adaptation schemes, with which WLAN devices adjust the modulation and coding scheme (MCS) for their transmissions. As MCSs resulting in low link data rates may specifically degrade the capacity of a WLAN cell, we focus on an estimation regarding the data rate selection of a device as a third contribution of this thesis. This estimation enables to select devices that will likely degrade the capacity of the WLAN hotspot for an onloading in advance

    Optimisation of Traffic Steering for Heterogeneous Mobile Networks

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    Mobile networks have changed from circuit switched to IP-based mobile wireless packet switched networks. This paradigm shift led to new possibilities and challenges. The development of new capabilities based on IP-based networks is ongoing and raises new problems that have to be tackled, for example, the heterogeneity of current radio access networks and the wide range of data rates, coupled with user requirements and behaviour. A typical example of this shift is the nature of traffic, which is currently mostly data-based; further, forecasts based on market and usage trends indicate a data traffic increase of nearly 11 times between 2013 and 2018. The majority of this data traffic is predicted to be multimedia traffic, such as video streaming and live video streaming combined with voice traffic, all prone to delay, jitter, and packet loss and demanding high data rates and a high Quality of Service (QoS) to enable the provision of valuable service to the end-user. While the demands on the network are increasing, the end-user devices become more mobile and end-user demand for the capability of being always on, anytime and anywhere. The combination of end-user devices mobility, the required services, and the significant traffic loads generated by all the end-users leads to a pressing demand for adequate measures to enable the fulfilment of these requirements. The aim of this research is to propose an architecture which provides smart, intelligent and per end-user device individualised traffic steering for heterogeneous mobile networks to cope with the traffic volume and to fulfil the new requirements on QoS, mobility, and real-time capabilities. The proposed architecture provides traffic steering mechanisms based on individual context data per end-user device enabling the generation of individual commands and recommendations. In order to provide valuable services for the end-user, the commands and recommendations are distributed to the end-user devices in real-time. The proposed architecture does not require any proprietary protocols to facilitate its integration into the existing network infrastructure of a mobile network operator. The proposed architecture has been evaluated through a number of use cases. A proof-of-concept of the proposed architecture, including its core functionality, was implemented using the ns-3 network simulator. The simulation results have shown that the proposed architecture achieves improvements for traffic steering including traffic offload and handover. Further use cases have demonstrated that it is possible to achieve benefits in multiple other areas, such as for example improving the energy efficiency, improving frequency interference management, and providing additional or more accurate data to 3rd party to improve their services
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