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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
Federated Robust Embedded Systems: Concepts and Challenges
The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements.
While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development.
During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs
Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence
Smartphones, wearables, and Internet of Things (IoT) devices produce a wealth
of data that cannot be accumulated in a centralized repository for learning
supervised models due to privacy, bandwidth limitations, and the prohibitive
cost of annotations. Federated learning provides a compelling framework for
learning models from decentralized data, but conventionally, it assumes the
availability of labeled samples, whereas on-device data are generally either
unlabeled or cannot be annotated readily through user interaction. To address
these issues, we propose a self-supervised approach termed
\textit{scalogram-signal correspondence learning} based on wavelet transform to
learn useful representations from unlabeled sensor inputs, such as
electroencephalography, blood volume pulse, accelerometer, and WiFi channel
state information. Our auxiliary task requires a deep temporal neural network
to determine if a given pair of a signal and its complementary viewpoint (i.e.,
a scalogram generated with a wavelet transform) align with each other or not
through optimizing a contrastive objective. We extensively assess the quality
of learned features with our multi-view strategy on diverse public datasets,
achieving strong performance in all domains. We demonstrate the effectiveness
of representations learned from an unlabeled input collection on downstream
tasks with training a linear classifier over pretrained network, usefulness in
low-data regime, transfer learning, and cross-validation. Our methodology
achieves competitive performance with fully-supervised networks, and it
outperforms pre-training with autoencoders in both central and federated
contexts. Notably, it improves the generalization in a semi-supervised setting
as it reduces the volume of labeled data required through leveraging
self-supervised learning.Comment: Accepted for publication at IEEE Internet of Things Journa
A novel MAC Protocol for Cognitive Radio Networks
In Partial Fulfilment of the Requirements for the Degree Doctor of Philosophy from the University of BedfordshireThe scarcity of bandwidth in the radio spectrum has become more vital since the demand for wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum bands and the inefficiency in their utilization have been smartly addressed by the cognitive radio (CR) technology which is an opportunistic network that senses the environment, observes the network changes, and then uses knowledge gained from the prior interaction with the network to make intelligent decisions by dynamically adapting transmission characteristics. In this thesis, recent research and survey about the advances in theory and applications of cognitive radio technology has been reviewed. The thesis starts with the essential background on cognitive radio techniques and systems and discusses those characteristics of CR technology, such as standards, applications and challenges that all can help make software radio more personal. It then presents advanced level material by extensively reviewing the work done so far in the area of cognitive radio networks and more specifically in medium access control (MAC) protocol of CR. The list of references will be useful to both researchers and practitioners in this area. Also, it can be adopted as a graduate-level textbook for an advanced course on wireless communication networks.
The development of new technologies such as Wi-Fi, cellular phones, Bluetooth, TV broadcasts and satellite has created immense demand for radio spectrum which is a limited natural resource ranging from 30KHz to 300GHz. For every wireless application, some portion of the radio spectrum needs to be purchased, and the Federal Communication Commission (FCC) allocates the spectrum for some fee for such services. This static allocation of the radio spectrum has led to various problems such as saturation in some bands, scarcity, and lack of radio resources to new wireless applications. Most of the frequencies in the radio spectrum have been allocated although many studies have shown that the allocated bands are not being used efficiently. The CR technology is one of the effective solutions to the shortage of spectrum and the inefficiency of its utilization. In this thesis, a detailed investigation on issues related to the protocol design for cognitive radio networks with particular emphasis on the MAC layer is presented. A novel Dynamic and Decentralized and Hybrid MAC (DDH-MAC) protocol that lies between the CR MAC protocol families of globally available common control channel (GCCC) and local control channel (non-GCCC). First, a multi-access channel MAC protocol, which integrates the best features of both GCCC and non-GCCC, is proposed. Second, an enhancement to the protocol is proposed by enabling it to access more than one control channel at the same time. The cognitive users/secondary users (SUs) always have access to one control channel and they can identify and exploit the vacant channels by dynamically switching across the different control channels. Third, rapid and efficient exchange of CR control information has been proposed to reduce delays due to the opportunistic nature of CR. We have calculated the pre-transmission time for CR and investigate how this time can have a significant effect on nodes holding a delay sensitive data. Fourth, an analytical model, including a Markov chain model, has been proposed. This analytical model will rigorously analyse the performance of our proposed DDH-MAC protocol in terms of aggregate throughput, access delay, and spectrum opportunities in both the saturated and non-saturated networks. Fifth, we develop a simulation model for the DDH-MAC protocol using OPNET Modeler and investigate its performance for queuing delays, bit error rates, backoff slots and throughput. It could be observed from both the numerical and simulation results that when compared with existing CR MAC protocols our proposed MAC protocol can significantly improve the spectrum utilization efficiency of wireless networks. Finally, we optimize the performance of our proposed MAC protocol by incorporating multi-level security and making it energy efficient
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