2,274 research outputs found

    Satellite-enabled interactive education: scenarios and systems architectures

    Get PDF
    There are specific sectors of the economy that can benefit from satellite-based tele-education. Areas, such as maritime and agriculture, share common needs for both broadband connectivity at remote geographical areas that cannot otherwise be covered, and for innovative content for tele-education purposes. Furthermore, each area has special requirements with regard to the type of content to be delivered. In this paper we propose a set of architectural designs and case scenarios that will realise such interactive end-to-end education systems based on satellite communications. Services requirements in this setting are also identified and discussed

    Wifi AP Based Secure Data Sharing Among Smartphones And Computer System

    Get PDF
    Smartphones operate independently of each other, using only local computing, sensing, networking, and storage capabilities and functions provided by remote Internet services. It is generally difficult or expensive for one smartphone to share data and computing resources with another. Coordinating smartphone data and computing would allow mobile applications to utilize the capabilities of an entire smartphone cloud while avoiding global network bottlenecks. In many cases, processing mobile data in-place and transferring it directly between smartphones would be more efficient and less susceptible to network limitations than offloading data and processing to remote servers. The main objective of this paper is to introduce a methodology to provide flexible media content sharing by exploiting collaborative amongst WiFi devices via the temporarily-established links over the local server which is based on heterogeneous mobile which is having different mobile platform, users connected to the server like computer System via Wi-Fi. The realized prototype devices altogether show improved sharing performance by supporting two-times more concurrent devices at target media quality when compared with conventional non-collaborative. In this the client and local server will upload or retrieve the data in authenticated and in confidential manner. The proposed method is based on sending/receiving data between client server via Wi-Fi connection without the need of taking any service from mobile service provider and without the use of internet connection. DOI: 10.17762/ijritcc2321-8169.160411

    Satellite-enabled educational services specification and requirements analysis based on user feedback

    No full text
    Advanced tele-education services provision in remote geographically dispersed user communities (such as agriculture and maritime), based on the specific needs and requirements of such communities, implies significant infrastructural and broadband connectivity requirements for rich media, timely and quality-assured content delivery and interactivity. The solution to broadband access anywhere is provided by satellite-enabled communication infrastructures. This paper aims to present such satellite-based infrastructures that are capable of addressing the core requirements of rich media educational services in remote areas. The paper proceeds to examine a set of services that will realise such satellite-based distance learning systems and to assess the targeted users’ interest in such services. The presented work is undertaken within the framework of the EU-funded Broadband Access Satellite Enabled Education (BASE2) project. Furthermore, requirements analysis, based on the Volere template (Robertson) and on user feedback, is undertaken

    Collaborative Traffic Offloading for Mobile Systems

    Get PDF
    Due to the popularity of smartphones and mobile streaming services, the growth of traffic volume in mobile networks is phenomenal. This leads to huge investment pressure on mobile operators' wireless access and core infrastructure, while the profits do not necessarily grow at the same pace. As a result, it is urgent to find a cost-effective solution that can scale to the ever increasing traffic volume generated by mobile systems. Among many visions, mobile traffic offloading is regarded as a promising mechanism by using complementary wireless communication technologies, such as WiFi, to offload data traffic away from the overloaded mobile networks. The current trend to equip mobile devices with an additional WiFi interface also supports this vision. This dissertation presents a novel collaborative architecture for mobile traffic offloading that can efficiently utilize the context and resources from networks and end systems. The main contributions include a network-assisted offloading framework, a collaborative system design for energy-aware offloading, and a software-defined networking (SDN) based offloading platform. Our work is the first in this domain to integrate energy and context awareness into mobile traffic offloading from an architectural perspective. We have conducted extensive measurements on mobile systems to identify hidden issues of traffic offloading in the operational networks. We implement the offloading protocol in the Linux kernel and develop our energy-aware offloading framework in C++ and Java on commodity machines and smartphones. Our prototype systems for mobile traffic offloading have been tested in a live environment. The experimental results suggest that our collaborative architecture is feasible and provides reasonable improvement in terms of energy saving and offloading efficiency. We further adopt the programmable paradigm of SDN to enhance the extensibility and deployability of our proposals. We release the SDN-based platform under open-source licenses to encourage future collaboration with research community and standards developing organizations. As one of the pioneering work, our research stresses the importance of collaboration in mobile traffic offloading. The lessons learned from our protocol design, system development, and network experiments shed light on future research and development in this domain.Yksi mobiiliverkkojen suurimmista haasteista liittyy liikennemÀÀrien eksponentiaaliseen kasvuun. TÀmÀ verkkoliikenteen kasvu johtuu pitkÀlti suosituista videopalveluista, kuten YouTube ja Netflix, jotka lÀhettÀvÀt liikkuvaa kuvaa verkon yli. Verkon lisÀÀntynyt kuormitus vaatii investointeja verkon laajentamiseksi. On tÀrkeÀÀ löytÀÀ kustannustehokkaita tapoja vÀlittÀÀ suuressa mittakaavassa sisÀltöÀ ilman mittavia infrastruktuuri-investointeja. Erilaisia liikennekuormien ohjausmenetelmiÀ on ehdotettu ratkaisuksi sisÀllönvÀlityksen tehostamiseen mobiiliverkoissa. NÀissÀ ratkaisuissa hyödynnetÀÀn toisiaan tukevia langattomia teknologioita tiedonvÀlityksen tehostamiseen, esimerkiksi LTE-verkosta voidaan delegoida tiedonvÀlitystÀ WiFi-verkoille. Useimmissa kannettavissa laitteissa on tuki useammalle langattomalle tekniikalle, joten on luonnollista hyödyntÀÀ nÀiden tarjoamia mahdollisuuksia tiedonvÀlityksen tehostamisessa. TÀssÀ vÀitöskirjassa tutkitaan liikennekuormien ohjauksen toimintaa ja mahdollisuuksia mobiiliverkoissa. TyössÀ esitetÀÀn uusi yhteistyöpohjainen liikennekuormien ohjausjÀrjestelmÀ, joka hyödyntÀÀ pÀÀtelaitteiden ja verkon tilannetietoa liikennekuormien optimoinnissa. Esitetty jÀrjestelmÀ ja arkkitehtuuri on ensimmÀinen, joka yhdistÀÀ energiankulutuksen ja kontekstitiedon liikennekuormien ohjaukseen. VÀitöskirjan keskeisiÀ tuloksia ovat verkon tukema liikennekuormien ohjauskehikko, yhteistyöpohjainen energiatietoinen optimointiratkaisu sekÀ avoimen lÀhdekoodin SoftOffload-ratkaisu, joka mahdollistaa ohjelmistopohjaisen liikennekuormien ohjauksen. EsitettyjÀ jÀrjestelmiÀ arvioidaan kokeellisesti kaupunkiympÀristöissÀ Àlypuhelimia kÀyttÀen. Työn tulokset mahdollistavat entistÀ energiatehokkaammat liikennekuormien ohjausratkaisut ja tarjoavat ideoita ja lÀhtökohtia tulevaan 5G kehitystyöhön

    Deep Learning for Edge Computing Applications: A State-of-the-Art Survey

    Get PDF
    With the booming development of Internet-of-Things (IoT) and communication technologies such as 5G, our future world is envisioned as an interconnected entity where billions of devices will provide uninterrupted service to our daily lives and the industry. Meanwhile, these devices will generate massive amounts of valuable data at the network edge, calling for not only instant data processing but also intelligent data analysis in order to fully unleash the potential of the edge big data. Both the traditional cloud computing and on-device computing cannot sufficiently address this problem due to the high latency and the limited computation capacity, respectively. Fortunately, the emerging edge computing sheds a light on the issue by pushing the data processing from the remote network core to the local network edge, remarkably reducing the latency and improving the efficiency. Besides, the recent breakthroughs in deep learning have greatly facilitated the data processing capacity, enabling a thrilling development of novel applications, such as video surveillance and autonomous driving. The convergence of edge computing and deep learning is believed to bring new possibilities to both interdisciplinary researches and industrial applications. In this article, we provide a comprehensive survey of the latest efforts on the deep-learning-enabled edge computing applications and particularly offer insights on how to leverage the deep learning advances to facilitate edge applications from four domains, i.e., smart multimedia, smart transportation, smart city, and smart industry. We also highlight the key research challenges and promising research directions therein. We believe this survey will inspire more researches and contributions in this promising field

    CAST: Proximity broadcasting as a mode of news distribution in rural Armenia

    Get PDF
    CAST (DisCovery Amplification Sustainability and InTeractions) has trialled a new community communication network in rural Armenia developing models to emerge alternative news media in a highly politically pressured national state. The project was a collaboration between the Media Innovation Studio, UK, Impact Hub Yerevan and SMART Edge Platform provider WICASTRℱ, Yerevan. The project also ran with the support of the United Nations Development Programme, award-winning investigative journalism outlet Hetq, and Civilnet from the Civilitas Foundation. It was a three-phase year-long pilot that ran in 2016 and 2017, funded by the UK Higher Education Innovation Fund. The aim was to: Build a lightweight community connectivity system for content distribution Generate proximity insights: new data analytics that allow publishers to pinpoint what content is consumed where Facilitate novel approaches to digital literacy by creating engaged digital communities New knowledge and impact have been created around: How to build hyperlocal proximity networks using online to offline wifi technology Future scoping information systems for remote communities New hyperlocal news data analytics for publishers Novel methods to add to media plurality in a highly politically pressured environment Strategies to improve digital literacy and community communication that can challenge a digital divid
    • 

    corecore