DVB-RCS return link radio resource management for broadband satellite systems using fade mitigation techniques at ka band

Current Broadband Satellite systems supporting DVB-RCS at Ku band have static physical layer in order not to complicate their implementation. However at Ka band frequencies and above an adaptive physical layer wherein the physical layer parameters are dynamically modified on a per user basis is necessary to counteract atmospheric attenuation. Satellite Radio Resource Management (RRM) at the Medium Access Control (MAC) layer has become an important issue given the emphasis placed on Quality of Service (QoS) provided to the Users. The work presented here tackles the problem of Satellite RRM for Broadband Satellite systems using DVB-RCS where a fully adaptive physical layer is envisaged at Ka band frequencies. The impact of adaptive physical layer and user traffic conditions on the MAC layer functions is analyzed and an algorithm is proposed for the RRM process. Various physical layer issues associated with the resource management problem are also analyzed

QoSatAr: a cross-layer architecture for E2E QoS provisioning over DVB-S2 broadband satellite systems

This article presents QoSatAr, a cross-layer architecture developed to provide end-to-end quality of service (QoS) guarantees for Internet protocol (IP) traffic over the Digital Video Broadcasting-Second generation (DVB-S2) satellite systems. The architecture design is based on a cross-layer optimization between the physical layer and the network layer to provide QoS provisioning based on the bandwidth availability present in the DVB-S2 satellite channel. Our design is developed at the satellite-independent layers, being in compliance with the ETSI-BSM-QoS standards. The architecture is set up inside the gateway, it includes a Re-Queuing Mechanism (RQM) to enhance the goodput of the EF and AF traffic classes and an adaptive IP scheduler to guarantee the high-priority traffic classes taking into account the channel conditions affected by rain events. One of the most important aspect of the architecture design is that QoSatAr is able to guarantee the QoS requirements for specific traffic flows considering a single parameter: the bandwidth availability which is set at the physical layer (considering adaptive code and modulation adaptation) and sent to the network layer by means of a cross-layer optimization. The architecture has been evaluated using the NS-2 simulator. In this article, we present evaluation metrics, extensive simulations results and conclusions about the performance of the proposed QoSatAr when it is evaluated over a DVB-S2 satellite scenario. The key results show that the implementation of this architecture enables to keep control of the satellite system load while guaranteeing the QoS levels for the high-priority traffic classes even when bandwidth variations due to rain events are experienced. Moreover, using the RQM mechanism the user’s quality of experience is improved while keeping lower delay and jitter values for the high-priority traffic classes. In particular, the AF goodput is enhanced around 33% over the drop tail scheme (on average)

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

Neuro-Fuzzy Computing System with the Capacity of Implementation on Memristor-Crossbar and Optimization-Free Hardware Training

In this paper, first we present a new explanation for the relation between logical circuits and artificial neural networks, logical circuits and fuzzy logic, and artificial neural networks and fuzzy inference systems. Then, based on these results, we propose a new neuro-fuzzy computing system which can effectively be implemented on the memristor-crossbar structure. One important feature of the proposed system is that its hardware can directly be trained using the Hebbian learning rule and without the need to any optimization. The system also has a very good capability to deal with huge number of input-out training data without facing problems like overtraining.Comment: 16 pages, 11 images, submitted to IEEE Trans. on Fuzzy system