Haut PDF Next Generation Internet Research and Experimentation

Next Generation Internet Research and Experimentation

Next Generation Internet Research and Experimentation

FIRE has evolved into a diverse portfolio of experimental facilities, increa- singly federated and supported by tools, and responding to the needs and demands of a large scientific experimenter community. Issues that require attention include the sustainability of facilities after projects’ termination, the engagement of industry and SMEs, and the further development of FIRE’s ecosystem. A more strategic issue is to develop a full service approach addressing the gaps between ecosystem layers and addressing integration issues that are only now coming up in other Future Internet-funded projects. A related challenge is to expand the nature of FIRE’s ecosystem from an offering of experimental facilities towards the creation of an ecosystem platform capable to attract market parties from different sides that benefit from mutual and complementary interests. Additionally, FIRE should anticipate the shifting focus of Future Internet innovation areas towards connecting users, sensor networks and heterogeneous systems, where data, heterogeneity and scale will determine future research and innovation in areas such as Big Data, and 5G and IoT [9]. Such demands lead to the need for FIRE to focus on testbeds, experimentation and innovation support in the area of “smart systems
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A new framework of operation research and learning path recommendation for next-generation of e-learning services

A new framework of operation research and learning path recommendation for next-generation of e-learning services

NRC Publications Archive Archives des publications du CNRC Access and use of this website and the material on it are subject to the Terms and Conditions set forth at A new framework of operation research and learning path recommendation for next-generation of e-learning services

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Data proxies, the cognitive layer, and application locality : enablers of cloud-connected vehicles and next-generation internet of things

Data proxies, the cognitive layer, and application locality : enablers of cloud-connected vehicles and next-generation internet of things

2.1 Creating a Secure, Efficient Architecture We first propose the concept of a Data Proxy and this Proxy’s related architecture. There is significant potential in connecting devices, platforms, services, and people. However, there exist challenges to the creation of pervasive connectivity in the form of power and bandwidth constraints and fear of insecurity. To ensure that even resource- constrained devices can belong to connected systems, inputs must be minimized system-wide. Approaches to date have focused on reducing requirements for just one element of a system, such as network loading, and focused largely on optimizing data transmission using resources on the device itself. We instead need an approach where systems are optimized using computation and power where it is more available, less costly, and more easily scaled — in gateway devices or in the Cloud. The following sections introduce the concept of the “Data Proxy,” a state-estimated digital duplicate of a physical object. This Proxy enables a reduction in sampling and transmission rate at the sensing or actuating device by deploying an estimator based on the system model. This pseudo-interpolation simultaneously addresses the common problems with timestamp corruption and unplanned data outages frequently occurring in connected systems.
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Federation of Internet experimentation facilities: architecture and implementation

Federation of Internet experimentation facilities: architecture and implementation

Abstract — Realistic experimentation facilities are indispensable to accelerate the design of novel Future Internet systems. As many of these ground-breaking new applications and services cover multiple innovation areas, the need for these solutions to be tested on cross-domain facilities with both novel infrastructure technologies and newly emerging service platforms is rising. The Fed4FIRE project therefore aims at federating otherwise isolated experimentation facilities in order to foster synergies between research communities. Currently the federation includes over 15 facilities from the Future Internet Research and Experiment (FIRE) initiative, covering wired, wireless and sensor networks, SDN and OpenFlow, cloud computing, smart city services, etc. This paper presents the architecture and implementation details of the federation, based on an extensive set of requirements coming from infrastructure owners, service providers and support communities.
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Flow Allocation with Path Protection in Next Generation Internet Networks

Flow Allocation with Path Protection in Next Generation Internet Networks

I. I NTRODUCTION Once capacities have been assigned to the Next Generation Internet (NGI) core links in the capacity design phase, net- work engineers can tackle the flow allocation problem. The challenge is to determine how much traffic of each demand should be admitted in the network and how this traffic should be routed in order to satisfy the requirement of high network utilization while guaranteeing fairness to the users. Thus, the optimization objective of the flow allocation problem depends on the provisioning strategy chosen by network engineers. Moreover, survivability requirements are introduced at this level of the network optimization. Backup capacity is provi- sioned in order to provide protection for allocated flows against network failures. Hence, considering both the provisioning strategy and the survivability mechanism, we end up with various formulations for the flow allocation problem.
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Next-Generation Model-based Variability Management: Languages and Tools

Next-Generation Model-based Variability Management: Languages and Tools

Dr. Patrick Heymans is full professor of software engineering at University of Na- mur, Belgium and visiting researcher at INRIA/University of Lille/CNRS. He is found- ing member and co-director of the PReCISE research centre (50 researchers) where he leads the requirements engineering and software product line efforts. He has supervised 9 PhD theses and authored 85 peer-reviewed papers. He is a regular referee for top SE journals and conferences, and associate editor of IEEE TSE. Patrick was recently the program chair of RE’11. He is principal investigator on various international soft- ware engineering research projects and regularly acts as an advisor and trainer for IT companies.
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KEIHANNA : Keihanna Eco-City Next-Generation Energy and Social System. Projet SMARTMOB

KEIHANNA : Keihanna Eco-City Next-Generation Energy and Social System. Projet SMARTMOB

3 Keihanna Eco-City Next-Generation Energy and Social System 1. Présentation du site Le démonstrateur de smart community de Keihanna se situe sur une partie du territoire de la cité scientifique du même nom. Dans ce terrain d’expérimentation, les chercheurs universitaires possèdent un rôle plus affirmé dans la conduite des programmes mis en œuvre. Ce tropisme est important pour saisir la complexité apparente de l’élaboration de l’appel d’offre et du master plan de la smart community. Les obstacles qui ont jalonné l’élaboration du projet (voir rapport transversal de la recherche) témoignent de la difficulté à faire collaborer les entreprises et les chercheurs de par la diversité des profils et des récits d’action mobilisés par chaque acteur, ce qui influence également la gouvernance de la smart community. Localisée à la frontière de trois préfectures – Kyoto, Osaka et Nara 1 –, la cité scientifique ou « parc de recherche scientifique et culturelle du Kansai 2 » est composé de douze « districts » couvrant un total de 3 600 hectares dont près de 2 000 hectares dans la préfecture de Kyoto. Si la cité scientifique comprend sept villes (shi) – Hirakata, Ikoma, Katano, Kizugawa, Kyotanabe, Nara et Shijonawate – et le bourg (chō) de Seika, le projet de smart community ne porte que sur les trois municipalités au sud de la préfecture de Kyoto : Kyotanabe, Kizugawa et Seika. Ces trois municipalités ne représentent que 173 301 habitants 3 (2010) sur les 2,61 millions d’habitants que compte la préfecture de Kyoto 4 (dont ville de Kyoto : 1,47 million). La cité scientifique per se regroupant quant à elle quelques 100 000 habitants (Kansai Research Institute, 2013). Il ne s’agit en effet pas d’un espace universitaire fermé mais d’un label donné à une large zone incluant des universités, des laboratoires de recherche, des usines, mais aussi des habitants et des commerces.
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Toward Third Generation Internet Desktop Grids

Toward Third Generation Internet Desktop Grids

3 A third generation of Desktop Grid architecture Our proposal for a third generation IDG intents to cope with the flexibility and adap- tability limitations of the first and second generations IDG. In addition, the proposed ar- chitecture aims at reusing existing cluster and Grid software compliant with the low com- munication performance of IDG. For these mechanisms, it is questionable to design and implement novel software. If we take the example of a batch scheduler, there are several existing software that have demonstrated to be extremely reliable and have the experience of years of utilization (Condor, Sun Grid Engine, Torque, LSF). The development effort of a dedicated stable scheduler with a sophisticated interface similar to the existing ones would be considerable. Moreover, most of the extra features implemented in a novel would probably be implementable in the existing ones. In addition to mechanisms shared with Cluster and Grid, there are some specific mechanisms that clearly distinguish Desktop Grids. The objec- tive of our proposal for a third generation is to concentrate the development and research effort on these specific mechanisms.
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Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges

Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges

CONCLUSION BCI provides a novel channel for HCI, from which not only disabled people but also healthy users can benefit. Despite a number of challenges that it faces, BCI shows a bright future and opportunity in its existing and potential applications. As a result, the BCI research has recently become a strong topic with research activities even outside its traditional application field (i.e. rehabilitation engineering), such as the well-known OpenVibe 2 project, and has attracted some large companies’ attentions (e.g. France Telecom). There are reasons to believe that BCI will become a powerful tool for next generation HCI.
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A combined smart-materials approach for next-generation airfoils

A combined smart-materials approach for next-generation airfoils

Introduction Today’s rigid airfoil geometries are usually the result of compromise in the design process optimizing the airfoil for some parts of the mission profile. In order to circumvent this disadvantage control surfaces are used. Unfortunately these are usually characterized by poor aerodynamic performance and efficiency. Morphing structures potentially hold the key to solve this problem. Hence, wing deformation studies are subject of much interest in the aerospace domain and recent advances made in the field of smart-materials have renewed this interest [1]. The Electro-active morphing for micro-air-vehicles (EMMAV) research program aims at optimizing the performance of micro-air-vehicles in realistic environments via electroactive morphing. During the course of this project a prototype NACA 0012 wing was developed with embedded Shape memory alloys (SMAs) and trailing-edge piezoelectric actuators enabling both large deformations (~10% of the chord) at limited frequency (<1Hz) and small deformations (several μm) at high frequencies (≤100Hz) [4]. The characteristics of the SMA technology, which were activated using the well understood Joule effect, make it especially suitable to optimize the shape of the wing and to control the flight [2, 6]. The high-frequent but low amplitude piezoelectric technology on the other hand is useful to produce trailing-edge vortex breakdown [11].
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Modeling quality of experience of internet video streaming by controlled experimentation and machine learning

Modeling quality of experience of internet video streaming by controlled experimentation and machine learning

Video streaming is the dominant contributor of today’s Internet traffic. Consequently, estimating Quality of Experience (QoE) for video streaming is of paramount importance for network operators. The QoE of video streaming is directly dependent on the network conditions (e.g., bandwidth, delay, packet loss rate) referred to as the network Quality of Service (QoS). This inherent relationship between the QoS and the QoE motivates the use of supervised Machine Learning (ML) to build models that map the network QoS to the video QoE. In most ML works on QoE modeling, the training data is usually gathered in the wild by crowdsourcing or generated inside the service provider networks. However, such data is not easily accessible to the general research community. Conse- quently, the training data if not available beforehand, needs to be built up by controlled experimentation. Here, the target application is run under emulated network environ- ments to build models that predict video QoE from network QoS. The network QoS can be actively measured outside the data plane of the application (outband ), or measured passively from the video traffic (inband ). These two distinct types of QoS correspond to the use cases of QoE forecasting (from end user devices) and QoE monitoring (from within the networks). In this thesis, we consider the challenges associated with network QoS-QoE modeling, which are 1) the large training cost of QoE modeling by controlled experimentation, and 2) the accurate prediction of QoE considering the large diversity of video contents and the encryption deployed by today’s content providers.
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Building the next generation of personal digital assistants

Building the next generation of personal digital assistants

However, from a technical perspective VUIs represent a complex interface option. In particular, since currently the capabilities of the underlying technologies for Automatic Speech Recognition (ASR), Natural Language Understanding (NLU) and Text-to-Speech (TTS) synthesis are constrained by pre-defined application contexts and not yet ready for supporting a free-form human-machine conversation. This is why current voice enabled systems are developed based on specific use case descriptions. Scenarios range from rather simple applications such as using speech input to surf the Internet, to more complex settings where voice may be used to monitor the well being of elderly people, or to offer them assistance in operating technological services such as sending an SMS, writing an e-mail, searching their weekly agenda, or managing a calendar program. Systems targeted at el- derly people face particular challenges, as due to possible age-related fine motor articulatory impairments additional efforts are required in order to adapt and improve the speech recognition algorithms [7].
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Towards next generation networks with SDN and NFV

Towards next generation networks with SDN and NFV

With the large yearly increase of Internet traffic and the growing concern of the public and governments towards greenhouse gas emissions, future net- works will have to be more energy efficient [ Mat+13 ]. In the past few years, this has been the focus of extensive research work [ Ver+11 ; Le +13 ]. One of the classic methods to reduce the energy consumption of networks is to try to aggregate network traffic on a small number of network equipment in order to put to sleep the unused hardware. However, an additional chal- lenge is given by the fact that today’s traffic must pass through a certain number of network functions. Examples of network functions include deep packet inspection (DPI), firewall, load balancing, and WAN optimization. The network functions often need to be applied in a specific order, e.g., in a security scenario, the firewall has to be applied before carrying out a DPI, as the latter is more CPU intensive than the former. In this context, a Service Function Chain (SFC) is a list of network functions, that need to be applied to a flow in a particular order. These functions are carried out by specific hardware, which are installed at specific locations of the network. The paths followed by demands are thus very constrained, reducing the opportunities to aggregate traffic.
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Enable the next generation of interactive video streaming

Enable the next generation of interactive video streaming

which is much higher than the worldwide median Internet access connection speed. Applying traditional adaptive streaming technologies used by Over-The-Top (OTT) companies such as YouTube, Netflix, and Facebook would result, to match the available download bandwidth, in very low quality viewports. In this dissertation I present my contributions to enable the streaming of highly immersive omnidirectional videos over the Internet. The contributions can be gathered into six contributions and into three main topics. First we propose new streaming architectures. Our goal is to stay as close as possible as existing HTTP Adaptive Streaming (HAS) architecture for obvious cost reduction reasons. We propose first a viewport-adaptive streaming architecture where omnidirectional video are encoded with a Quality Emphasized Region (QER) in order to stream video with high quality in the direction user is predicted to look in a few seconds while keeping traditional download throughput adaptation from HAS . Then we propose an extension to this streaming architecture to stream a next generation of omnidirectional video, denoted as Multi-ViewPoint (MVP) omnidirectional video, where users can not only perform rotational movement inside the content but also predefined translational movements. Secondly we perform theoretical studies. We study the relationship between the spherical pixel density
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Computational training for the next generation of neuroscientists

Computational training for the next generation of neuroscientists

Meeting these needs can be challenging in practice. Most fundamentally, it requires that life science departments re-think what skills are important for students who will be mid-career in 2050. This entails deciding what courses should be offered, which of these should be required, and what these courses’ prerequisites should be. We recommend that such considerations start from the point of view of what core thinking skills will be most valuable to students’ future endeavors. This viewpoint should take precedence over other factors such as a possible lack of popularity of quantitative courses among students, or departmental financial considerations that may be tied to enrollment numbers. As emphasized by a host of reports on undergraduate biology training from the AAAS [42], National Academies [41,44,45], and American
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Design and manufacture of the next generation of ion electrospray thrusters

Design and manufacture of the next generation of ion electrospray thrusters

Originally, the plan was to wet-etch the oxide layer, as it is a well-quantified process. However, in testing, it was found that the greater etch duration coupled [r]

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Crayon: saving power through shape and color approximation on next-generation displays

Crayon: saving power through shape and color approximation on next-generation displays

➋ Shape Transform: It presents a technique for perception- aware shape approximation. The technique is the first to exploit object shape and color information to reduce dis- play power dissipation. The experimental results show that this transform is effective for both online and offline optimization of drawing API calls and vector image files. ➌ Architecture and Implementation: It presents an archi- tecture and implementation for dynamically intercepting drawing API calls to apply perception-aware shape and color approximation. Our implementation of the entire Crayon system is currently ~14 k lines of C code. The current implementation runs on desktops and on an An- droid tablet. As one demonstration of the architecture, we show how to integrate Crayon into the Cairo draw- ing API [ 70 ] via the addition of approximately 50 lines of glue logic C code (Section 3 ). 2
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Archaea: Microbial Candidates in Next-generation Probiotics Development

Archaea: Microbial Candidates in Next-generation Probiotics Development

Jean François Brugere, Wajdi Ben Hania, Marie-Edith Arnal, Céline Ribière, Nathalie Ballet, Pascal Vandeckerkove, Bernard Ollivier, Paul W.. O’toole[r]

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Advancing lean implementation for next generation biomanufacturing operations

Advancing lean implementation for next generation biomanufacturing operations

During the R2R process improvement many instances were identified that supported the hypothesis that implementing from the start of operations would be conducive to more [r]

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Carrier Aggregation/Channel Bonding in Next Generation Cellular Networks: Methods and Challenges

Carrier Aggregation/Channel Bonding in Next Generation Cellular Networks: Methods and Challenges

A. Licensed Plus Unlicensed Using Small Cells In this scenario, a heterogeneous network operator deploys small cells in unlicensed bands that use the modified version of the same technology (such as LTE-A or its future versions) that is used in the macro cell (which operates on a licensed band) to co-exist with WiFi systems [10]. In principle LTE-A offers a good opportunity for utilizing CA in both 2.4 GHz and 5 GHz bands due to its ability to utilize flexible bandwidths of different sizes for component carriers (CCs) (such as 1.4, 3, 5, 10, 15 or 20 MHz). The main idea behind this scheme is that when suitable carrier(s) are available in the unlicensed band, then a user’s primary component carrier (PCC) in the licensed band is aggregated with these secondary component carriers (SCCs) in the unlicensed band. Control signalling (such as ACK/NACK and channel quality indicator [CQI]) is carried on the PCC. A listen-before-talk scheme is utilized before transmission on aggregated channels in the unlicensed aggregated carriers so that the interference with WiFi systems is avoided. In addition, the unlicensed spectrum is used on an “on demand” basis, meaning that only the small cells that have active users are able to transmit in the unlicensed band, and do not transmit at all at other times. This is possible because of a mandatory “anchor” in the licensed band.
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