33 research outputs found

    Centralized Conferencing in the IP Multimedia Subsystem: from theory to practice

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    In this paper we present a conferencing architecture compliant with the IP Multimedia Subsystem (IMS) specification. To the purpose, we embrace a practical approach, by describing an actual implementation of an open source centralized video-conferencing system, called CONFIANCE, capable to offer advanced communication experience to end-users through the effective exploitation of mechanisms like session management and floor control. CONFIANCE has been designed to be fully compliant with the latest standard proposals coming from both the IETF and the 3GPP and can be considered as an outstandingexample of a real-time application built on top of the grounds paved by the SIP protocol. We will discuss in the paper both the design of the overall conferencing framework and the most important issues we had to face during the implementation phase

    Artificial Intelligence:Up to here ... and on again

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    Multimedia-Streaming in Benutzergruppen

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    At the time being, multimedia services using IP technology like IPTV or video on-demand are a hot topic. Technically, they can be classified under the notion of streaming. A server sends media data in a continuous fashion to one or several clients, which consume and display data portions as soon as they arrive. Using a feedback channel customers may influence the play-back, watching programs time-shifted or pausing the program. An enhancement of such streaming services is to watch those movies with a group of people on several devices in parallel. Similar approaches have been developed using IP multicast. However, users cannot control the presentation: pausing or skipping of more unimportant parts is impossible. Moreover, members cannot be added to the session directly within the application. The costream architecture developed in this works offers a collaborative streaming service without these limitations: People may join others watching a movie or invite others to such a collaborative streaming session. Dependent on the desired course of the session the participants' control operations are executed for all users, or the group is split into subgroups to let watchers follow their own time-lines. A group management controls this by means of user roles. Separate from the group management, the so-called association service provides for streaming session control and synchronization among participants. This separation of duties is advantageous in the sense that standard components can be used: For group management, SIP conferencing servers are suitable, whereas session control can best be handled using RTSP proxies as already used for caching of media data. Eventually, the evaluation of this architecture shows that such a service offers both low latency for clients and an acceptable synchronization of media streams to different client devices. Moreover, the communication overhead compared to usual conferencing or streaming systems is very low.Mit Hilfe der IP-Technologie erbrachte Multimedia-Dienste wie IPTV oder Video-on-Demand sind zur Zeit ein gefragtes Thema. Technisch werden solche Dienste unter dem Begriff "Streaming" eingeordnet. Ein Server sendet Mediendaten kontinuierlich an Empfรคnger, welche die Daten sofort weiterverarbeiten und anzeigen. รœber einen Rรผckkanal hat der Kunde die Mรถglichkeit der Einflussnahme auf die Wiedergabe. Eine Weiterentwicklung dieser Streaming-Dienste ist die Mรถglichkeit, gemeinsam mit anderen denselben Film auf mehreren Gerรคten anzusehen. ร„hnliche Ansรคtze gibt es im Internet bereits durch IP-Multicast. Allerdings kรถnnen Benutzer hierbei keinen Einfluss auf die รœbertragung nehmen - das รœberspringen von Teilen ist zum Beispiel nicht mรถglich. Andere Benutzer kรถnnen nicht direkt zur Streaming-Sitzung eingeladen werden. Collaborative Streaming ohne solche Einschrรคnkungen bietet die in dieser Arbeit entwickelte costream-Architektur: Sie erlaubt es, andere zum gemeinsamen Betrachten eines Filmes einzuladen oder sich selbst in eine Benutzergruppe einzuklinken. Abhรคngig vom gewรผnschten Ablauf der Sitzung wird die Steuerung fรผr alle Teilnehmer durchgefรผhrt oder die Gruppe aufgeteilt. Eine Gruppenverwaltung regelt dies mit Hilfe von Rollenzuweisungen. Davon getrennt sorgt eine weitere Komponente fรผr die Steuerung der Streaming-Sitzungen und die Synchronisation zwischen Teilnehmern. Diese Aufteilung hat den Vorteil, dass von der IETF entwickelte Standardprotokolle eingesetzt werden kรถnnen. Fรผr die Gruppenverwaltung sind SIP-Konferenzsysteme geeignet, wรคhrend fรผr die Sitzungssteuerung ein RTSP-Zwischensystem benutzt wurde. Die Evaluierung dieser Architektur zeigt schlieรŸlich, dass ein solcher Dienst nicht nur geringe Wartezeiten aufweist, sondern eine akzeptable Synchronisation der Datenstrรถme auf die verschiedenen Ausgabegerรคte der Benutzer erreicht wird. Zudem ist der Zusatzaufwand verglichen mit รผblichen Konferenz- oder Streaming-Systemen sehr gering

    RESTful Web Services for Service Provisioning in Next Generation Networks: A Survey

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    Next Generation Networks (NGNs), as envisioned by ITU-T, are packet-based networks, capable of provisioning consistent and ubiquitous services to end-users, independently of the network, the access technology and the devices used. RESTful Web services are now being contemplated as a technology for service provisioning in NGNs. They are emerging as an alternative, which may be more adequate than SOAPbased Web services in some cases. SOAP-based Web services are modular applications that can be discovered and invoked over a network. RESTful Web services, on the other hand, are defined as a network architectural style for distributed hypermedia systems. This paper presents a survey on RESTful Web services for service provisioning in NGNs. It introduces the concept of RESTful Web services and reviews the state-of-the-art of RESTful-based-service provisioning in NGNs. It also provides an evaluation of the overall suitability of RESTful Web services for service provisioning in NGNs, and discusses research directions. RESTful Web services do show significant potential for service provisioning in NGNs. However, open issues such as publication/discovery and mechanisms for the development of complex session-based services need to be solved before its full potential can be realized

    ์ธ๊ณต์ง€๋Šฅ์„ ์ด์šฉํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฐ˜์˜ ์‹œ์Šคํ…œ๊ณผ ์‚ฌ์šฉ์ž์˜ ์ธํ„ฐ๋ž™์…˜์— ๋Œ€ํ•œ ์ดํ•ด

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(๋””์ง€ํ„ธ์ •๋ณด์œตํ•ฉ์ „๊ณต), 2019. 2. ์„œ๋ด‰์›.์ปดํ“จํŒ… ํŒŒ์›Œ์˜ ๊ฐœ์„ , ์ธํ„ฐ๋„ท๊ณผ ์†Œ์…œ๋ฏธ๋””์–ด, ๋ชจ๋ฐ”์ผ ๋””๋ฐ”์ด์Šค ๋“ฑ์˜ ๋ณด๊ธ‰์„ ํ†ตํ•œ ์ˆ˜๋งŽ์€ ๋ฐ์ดํ„ฐ์˜ ์ถ•์ , ๋”ฅ๋Ÿฌ๋‹์„ ๋น„๋กฏํ•œ ๊ธฐ๊ณ„ํ•™์Šต ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๋ฐœ์ „์œผ๋กœ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์ˆ ์ด ์–ด๋Š๋•Œ๋ณด๋‹ค ๋”์šฑ ํฐ ์„ฑ๊ณผ๋ฅผ ๋ณด์ด๊ณ  ์žˆ๋‹ค. ์Œ์„ฑ ์ธ์‹, ์ปดํ“จํ„ฐ ๋น„์ „, ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ ๋“ฑ์˜ ๋ถ„์•ผ์—์„œ ์ธ๊ณต์ง€๋Šฅ์€ ์ด๋ฏธ ์ธ๊ฐ„์— ํ•„์ ํ•˜๊ฑฐ๋‚˜ ํ˜น์€ ์ธ๊ฐ„์„ ๋›ฐ์–ด๋„˜๋Š” ์„ฑ๋Šฅ์„ ๋ณด์ด๊ณ  ์žˆ์œผ๋ฉฐ, ์ž์œจ์ฃผํ–‰, ๋กœ๋ด‡, ์˜๋ฃŒ์„œ๋น„์Šค ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์— ์ ์šฉ๋˜์–ด ์šฐ๋ฆฌ์˜ ์‚ถ์— ๋งŽ์€ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์˜ฌ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ํ•˜์ง€๋งŒ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ธก๋ฉด์—์„œ์˜ ๊ธฐ์ˆ ์ ์ธ ๋ฐœ์ „์— ๋น„ํ•ด ์ธ๊ณต์ง€๋Šฅ์˜ ์ธ๊ฐ„๊ณตํ•™์  ์š”์†Œ์™€ ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์— ๋Œ€ํ•œ ๊ด€์‹ฌ๊ณผ ๋…ผ์˜๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์กฑํ•œ ํŽธ์ด๋‹ค. ์ด์— ์ด ์—ฐ๊ตฌ๋Š” ์ธ๊ฐ„์ปดํ“จํ„ฐ์ƒํ˜ธ์ž‘์šฉ์˜ ๊ด€์ ์—์„œ ์ธ๊ณต์ง€๋Šฅ๊ณผ ์‚ฌ์šฉ์ž๊ฐ€ ์ƒํ˜ธ์ž‘์šฉ ํ•˜๋Š” ๋ฐฉ์‹์— ๋Œ€ํ•ด ๋‹ค์ธต์ ์ด๊ณ  ํ†ตํ•ฉ์ ์œผ๋กœ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•˜๊ณ  ์ด๋ฅผ ํ†ตํ•ด ์ธ๊ณต์ง€๋Šฅ ๊ธฐ๋ฐ˜์˜ ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค ๋””์ž์ธ์„ ์œ„ํ•œ ํ•จ์˜์ ์„ ๋„์ถœํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ํŠนํžˆ ์ด ๋…ผ๋ฌธ์€ ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์ˆ ์„ ์ด์šฉํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฐ˜์˜ ์‹œ์Šคํ…œ๊ณผ ์‚ฌ์šฉ์ž์˜ ์ƒํ˜ธ์ž‘์šฉ์— ์ฃผ๋ชฉํ•˜๊ณ , ์ด๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ธ์ง€, ํ•ด์„ ๋ฐ ํ‰๊ฐ€, ์ง€์†์ ์ธ ์ธํ„ฐ๋ž™์…˜, ์‹ค์šฉ์ ์ธ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ์ฃผ์ œ๋กœ ํ•œ ๋„ค ๋‹จ๊ณ„์˜ ์—ฐ๊ตฌ๋ฅผ ๊ธฐํšํ•˜๊ณ  ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ฒซ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋Œ€ํ•œ ์‚ฌ๋žŒ๋“ค์˜ ์„ ํ—˜์  ์ธ์‹์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์—ฐ๋ น๊ณผ ์„ฑ๋ณ„, ์ง์—…์˜ ๋‹ค์–‘์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ๋Œ€ํ‘œ์„ฑ์„ ๊ฐ–๋Š” ์ฐธ๊ฐ€์ž๋ฅผ ๋ชจ์ง‘ํ•˜์˜€์œผ๋ฉฐ, ์ด๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์ธ๊ณต์ง€๋Šฅ ์ธ์‹์— ๋Œ€ํ•œ ์ •์„ฑ์  ๋ฐฉ์‹์˜ ์กฐ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์กฐ์‚ฌ ๊ฒฐ๊ณผ ์‚ฌ๋žŒ๋“ค์ด ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋Œ€ํ•ด ๊ฐ–๋Š” ์„ ์ž…๊ฒฌ๊ณผ ๊ณ ์ •๊ด€๋…์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ์‚ฌ๋žŒ๋“ค์ด ์ธ๊ณต์ง€๋Šฅ์„ ์˜์ธํ™” ํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํƒ€์žํ™” ํ•˜๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์‚ฌ์šฉ์ž์˜ ๊ด€๊ณ„์—์„œ ์ง€์†์ ์ด๊ณ  ์ „์ฒด์ ์ธ ๊ฒฝํ—˜์ด ์ค‘์š”ํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž์˜ ํ•ด์„๊ณผ ํ‰๊ฐ€์— ๊ด€ํ•œ ๊ฒƒ์ด๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์ด๋ฏธ์ง€์˜ ๋ฏธ์  ์ ์ˆ˜๋ฅผ ๊ณ„์‚ฐํ•ด์ฃผ๋Š” ์‹ ๊ฒฝ๋ง ๊ธฐ๋ฐ˜์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๊ตฌํ˜„๋œ AI Mirror๋ผ๋Š” ์—ฐ๊ตฌ ํ”„๋กœํ† ํƒ€์ž…์„ ์ œ์ž‘ํ•˜์˜€์œผ๋ฉฐ, ์ธ๊ณต์ง€๋Šฅ/๊ธฐ๊ณ„ํ•™์Šต ๋ถ„์•ผ์˜ ์ „๋ฌธ๊ฐ€, ์‚ฌ์ง„์ „๋ฌธ๊ฐ€, ์ผ๋ฐ˜์ธ์œผ๋กœ ๊ตฌ๋ถ„๋œ ์„ธ ์ง‘๋‹จ์˜ ์‚ฌ์šฉ์ž๋ฅผ ๋ชจ์ง‘ํ•˜์—ฌ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์‚ฌ์šฉ์ž๋Š” ์ €๋งˆ๋‹ค ๋‹ค๋ฅธ ๋ฐฐ๊ฒฝ ์ง€์‹์„ ๋ฐ˜์˜ํ•ด ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ•ด์„ํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ์‚ฌ์ง„์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐ€์žฅ ๋†’์€ ์ •๋„๋กœ ํ•ด์„ํ•˜์˜€์œผ๋ฉฐ ํ•ฉ๋ฆฌ์ ์ด๋ผ๊ณ  ์—ฌ๊ธด ๋ฐ˜๋ฉด, ์ธ๊ณต์ง€๋Šฅ/๊ธฐ๊ณ„ํ•™์Šต ์ „๋ฌธ๊ฐ€ ์ง‘๋‹จ์€ ๊ฐ€์žฅ ๋‚ฎ์€ ์ •๋„๋กœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ•ด์„ํ•˜๊ณ  ํ‰๊ฐ€ํ–ˆ๋‹ค. ์‚ฌ์šฉ์ž๋Š” ๋‹ค์–‘ํ•œ ์ „๋žต์„ ํ†ตํ•ด ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์›๋ฆฌ๋ฅผ ์ถ”๋ก ํ•˜๊ณ ์ž ํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ํ†ตํ•ด ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ์˜ ์ฐจ์ด๋ฅผ ์ขํ˜€๊ฐˆ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์‚ฌ์šฉ์ž๋Š” ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์Œ๋ฐฉ ์†Œํ†ต์„ ํ†ตํ•ด ์˜๊ฒฌ์„ ๊ตํ™˜ํ•˜๊ณ ์ž ํ•˜๋Š” ๋‹ˆ์ฆˆ๋ฅผ ํ‘œ์ถœํ•˜์˜€๋‹ค. ์„ธ๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์‚ฌ์šฉ์ž๊ฐ€ ๊ณต๋™์˜ ๋ชฉํ‘œ๋ฅผ ๋‘๊ณ  ์ง€์†์ ์ธ ์ธํ„ฐ๋ž™์…˜์„ ์ด์–ด๊ฐ€๋Š” ๊ณผ์ •์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋ชฉํ‘œ๋กœ ํ•˜์˜€๋‹ค. ์‚ฌ์šฉ์ž๊ฐ€ ์ผ๋ถ€ ๊ทธ๋ฆฐ ๋ฌผ์ฒด๋ฅผ ์™„์„ฑํ•˜๊ณ  ์Šค์ผ€์น˜์— ์ƒ‰์น ์„ ์ž๋™์œผ๋กœ ์™„์„ฑํ•ด์ฃผ๋Š” ์‹ ๊ฒฝ๋ง ๊ธฐ๋ฐ˜์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜ API๋ฅผ ์ด์šฉํ•˜์—ฌ DuetDraw๋ผ๋Š” ๋ฆฌ์„œ์น˜ ํ”„๋กœํ† ํƒ€์ž…์„ ์ œ์ž‘ํ•˜์˜€๊ณ , ์ •๋Ÿ‰ ๋ฐ ์ •์„ฑ์  ๋ฐฉ๋ฒ•์œผ๋กœ ์ด์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์‚ฌ์šฉ์ž ํ‰๊ฐ€ ๊ฒฐ๊ณผ ์‚ฌ์šฉ์ž๋Š” ์ธ๊ณต์ง€๋Šฅ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ์˜ ํ˜‘์—… ๊ณผ์ •์—์„œ ์ธ๊ณต์ง€๋Šฅ์œผ๋กœ๋ถ€ํ„ฐ ๋‹จ์ˆœํ•œ ํ”ผ๋“œ๋ฐฑ ๋ณด๋‹ค๋Š” ์ž์„ธํ•œ ์„ค๋ช…์„ ์ œ๊ณต๋ฐ›๊ธฐ๋ฅผ ์›ํ–ˆ์œผ๋ฉฐ, ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ์˜ ๊ด€๊ณ„์—์„œ ํ•ญ์ƒ ์ฃผ๋„์ ์ธ ์œ„์น˜์— ์žˆ๊ณ ์ž ํ•˜์˜€๋‹ค. ์ธ๊ณต์ง€๋Šฅ๊ณผ์˜ ์ธํ„ฐ๋ž™์…˜์€ ๊ณผ์—… ์ˆ˜ํ–‰์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž์˜ ์˜ˆ์ธก๊ฐ€๋Šฅ์„ฑ, ์ดํ•ด๋„, ํ†ต์ œ๋ ฅ์„ ๋‚ฎ์ถ”๋Š” ๊ฒฝํ•ญ์ด ์žˆ์—ˆ์ง€๋งŒ, ์‚ฌ์šฉ์ž์—๊ฒŒ ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ์‚ฌ์šฉ์„ฑ์„ ์ œ๊ณตํ•˜์˜€์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‚ฌ์šฉ์ž๊ฐ€ ์ „๋ฐ˜์ ์œผ๋กœ ๋งŒ์กฑ์Šค๋Ÿฌ์šด ๊ฒฝํ—˜์„ ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๋์œผ๋กœ, ๋„ค๋ฒˆ์งธ ์—ฐ๊ตฌ๋Š” ๋ณด๋‹ค ์‹ค์šฉ์ ์ธ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ์ œ์ž‘ํ•˜์—ฌ ์ด์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž ์ธํ„ฐ๋ž™์…˜์„ ์ดํ•ดํ•˜๊ณ ์ž ํ•˜์˜€์œผ๋ฉฐ, ์ด์— ์ตœ๊ทผ ํฐ ๊ฐ๊ด‘์„ ๋ฐ›๊ณ  ์žˆ๋Š” ๋กœ๋ด‡์ €๋„๋ฆฌ์ฆ˜ ๊ธฐ์ˆ ์„ ๊ตฌํ˜„ํ•œ NewsRobot์„ ์ œ์ž‘ํ•˜์˜€๋‹ค. NewsRobot์€ 2018 ํ‰์ฐฝ๋™๊ณ„์˜ฌ๋ฆผํ”ฝ์˜ ์ฃผ์š” ๊ฒฝ๊ธฐ ๊ฒฐ๊ณผ๋ฅผ ์ž๋™์œผ๋กœ ์ˆ˜์ง‘ํ•˜๊ณ  ์š”์•ฝํ•˜๋ฉฐ, ๋‚ด์šฉ๊ณผ ํ˜•์‹์„ ๊ฐ๊ฐ ์ข…ํ•ฉ๋‰ด์Šค-์„ ํƒ๋‰ด์Šค, ํ…์ŠคํŠธ-์นด๋“œ-๋™์˜์ƒ์œผ๋กœ ๋‹ฌ๋ฆฌํ•˜์—ฌ ๋‰ด์Šค๋ฅผ ์ƒ์„ฑํ•œ๋‹ค. ์ •๋Ÿ‰ ๋ฐ ์ •์„ฑ์  ๋ฐฉ๋ฒ•์˜ ์‚ฌ์šฉ์ž ํ‰๊ฐ€ ๊ฒฐ๊ณผ, ์„ ํƒ๋‰ด์Šค๊ฐ€ ์ข…ํ•ฉ๋‰ด์Šค์— ๋น„ํ•ด ๋‚ฎ์€ ์‹ ๋ขฐ๋„๋ฅผ ๋ณด์˜€์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์„ ํƒ๋‰ด์Šค์— ๋Œ€ํ•œ ์‚ฌ์šฉ์ž์˜ ๋†’์€ ์„ ํ˜ธ๋„๋ฅผ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๋ฉ€ํ‹ฐ๋ฏธ๋””์–ด ๋ชจ๋‹ฌ๋ฆฌํ‹ฐ๊ฐ€ ๋†’์•„์งˆ์ˆ˜๋ก ์‚ฌ์šฉ์ž์˜ ๋‰ด์Šค์— ๋Œ€ํ•œ ๋งŒ์กฑ๋„๊ฐ€ ๋†’์•„์ง€์ง€๋งŒ ์‚ฌ์šฉ์ž์˜ ๊ธฐ๋Œ€์ˆ˜์ค€์— ์–ด๊ธ‹๋‚œ ๊ฒฝ์šฐ ์˜คํžˆ๋ ค ๋‚ฎ์€ ํ‰๊ฐ€๋ฅผ ๋ฐ›๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‚ฌ์šฉ์ž๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ž๋™์œผ๋กœ ์ƒ์„ฑํ•œ ๋‰ด์Šค์— ๋Œ€ํ•ด ์ •ํ™•ํ•˜๊ณ  ๊ฐ๊ด€์ ์ด๋ผ๊ณ  ํ‰๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ๋น ๋ฅธ ๋‰ด์Šค ์ƒ์„ฑ ์†๋„์™€ ๋‹ค์–‘ํ•œ ์ •๋ณด ์‹œ๊ฐํ™” ์š”์†Œ์— ๋Œ€ํ•ด์„œ๋„ ๋งŒ์กฑ๊ฐ์„ ๋“œ๋Ÿฌ๋ƒˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด ๋„ค ๊ฐ€์ง€ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋“ค์„ ๋ฐ”ํƒ•์œผ๋กœ ์ธ๊ฐ„-์ธ๊ณต์ง€๋Šฅ ์ƒํ˜ธ์ž‘์šฉ์— ๋Œ€ํ•œ ๋‹ค์–‘ํ•œ ์‹œ์‚ฌ์ ๋“ค์„ ๋„์ถœํ•˜์˜€์œผ๋ฉฐ, ์ธ๊ณต์ง€๋Šฅ์„ ์ด์šฉํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฐ˜์˜ ์‹œ์Šคํ…œ์˜ ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค ๋””์ž์ธ์„ ์œ„ํ•œ ํ•จ์˜์ ๋“ค์„ ์ œ์•ˆํ•œ๋‹ค.The recent development of artificial intelligence (AI) algorithms is affecting our daily lives in numerous areas. Moreover, AI is expected to evolve rapidly, bringing tremendous economic value. However, compared to the attention these technological improvements receive, there is relatively little discussion on human factors and user experience related to AI algorithms. Thus, this thesis aims to better understand how users interact with AI algorithms. Specifically, this work examined algorithm-based humanโ€“AI interaction in four stages, through various modes of human-computer interaction: The first study investigated how people perceive algorithm-based systems using AI, finding that people tend to anthropomorphize as well as alienate them, which is distinct from their perceptions of computers. The second study investigated how people interpret and evaluate the output from AI algorithms through a prototype, AI Mirror, which assigned aesthetic scores to images based on a neural network algorithm. The results revealed that people interpret AI algorithms differently based on their backgrounds, and that they want to understand and communicate with AI systems. The third study investigated how people build a sequence of actions with AI algorithms through a mixed method study using a research prototype called DuetDraw, a drawing tool in which users and AI can draw pictures together. The results showed that people want to lead collaborations while hoping to get appropriate instructions from the AI algorithm. Lastly, a case study on a practical application of AI was conducted with a research prototype called NewsRobot, which automatically generated news articles with different content and styles. Findings showed that users prefer selective news and multimedia news that have more functionality and modality, but at the same time they do not want AI to boast about its ability. With these distinct but intertwined studies, this thesis argues the importance of understanding human factors in the user interfaces of AI-based systems and suggests design principles to this end.1 INTRODUCTION 1 1.1 Background 1 1.2 Research Goal 10 1.3 Research Questions 11 1.4 How People Perceive Algorithm-based Systems Using Artificial Intelligence 12 1.5 How People Interpret and Evaluate Algorithm-based Systems Using Artificial Intelligence 13 1.6 How People Build Sequential Actions with Algorithm-Based Systems Using Artificial Intelligence 15 1.7 How People Use a Practical Application of an Algorithm-based Systems Using Artificial Intelligence 17 1.8 Thesis Statement 18 1.9 Contributions 18 1.10 Thesis Overview 20 2 RELATED WORK 22 2.1 Human Perception of AI Algorithms 22 2.1.1 Technophobia 22 2.1.2 Anthropomorphism 23 2.2 Users Interpretation and Evaluation of AI Algorithms 24 2.2.1 Interpretability of Algorithms and Users Concerns 24 2.2.2 Sense-making and Gap between Users and AI algorithms 25 2.2.3 User Control in Intelligent Systems 26 2.3 How People Build Sequential Actions with AI Algorithms 26 2.3.1 AI, Deep Learning, and New UX in Creative Works 27 2.3.2 Communication and Leadership among Users and AI 28 2.4 Practical Design of Algorithm-based Systems Using AI 29 2.4.1 Automated Journalism 30 2.4.2 Personalization of News Content 31 2.4.3 Effect of Multimedia Modality on User Experience 32 3 HOW PEOPLE PERCEIVE ALGORITHM-BASED SYSTEMS USING ARTIFICIAL INTELLIGENCE 33 3.1 Motivation 34 3.2 Google DeepMind Challenge Match 36 3.3 Methodology 38 3.3.1 Participant Recruitment 38 3.3.2 Interview Process 39 3.3.3 Interview Analysis 40 3.4 Findings 41 3.4.1 Preconceptions about Artificial Intelligence 41 3.4.2 Confrontation: Us vs. Artificial Intelligence 43 3.4.3 Anthropomorphizing AlphaGo 47 3.4.4 Alienating AlphaGo 49 3.4.5 Concerns about the Future of AI 52 3.5 Limitations 55 3.6 Summary 56 4 HOW PEOPLE INTERPRET AND EVALUATE ALGORITHM-BASED SYSTEMS USING ARTIFICIAL INTELLIGENCE 57 4.1 Motivation 58 4.2 AI Mirror 60 4.2.1 Design Goal 60 4.2.2 Image Assessment Algorithm 61 4.2.3 Design of User Interface 61 4.3 Study Design 62 4.3.1 Participant Recruitment 63 4.3.2 Experimental Settings 64 4.3.3 Procedure 65 4.3.4 Analysis Methods 66 4.4 Result 1: Quantitative Analysis 67 4.4.1 Difference 68 4.4.2 Interpretability 69 4.4.3 Reasonability 70 4.5 Result 2: Qualitative Analysis 71 4.5.1 People Understand AI Based on What They Know 71 4.5.2 People Reduce Difference Using Various Strategies 73 4.5.3 People Want to Actively Communicate with AI 76 4.6 Limitations 78 4.7 Conclusion 78 5 HOW PEOPLE BUILD SEQUENTIAL ACTIONS WITH ALGORITHM-BASED SYSTEMS USING ARTIFICIAL INTELLIGENCE 80 5.1 Motivation 81 5.2 Duet Draw 84 5.2.1 Five AI Functions of DuetDraw 84 5.2.2 Initiative and Communication Styles of DuetDraw 85 5.3 Study Design 86 5.3.1 Participants 87 5.3.2 Tasks and Procedures 87 5.3.3 Drawing Scenarios 88 5.3.4 Survey 89 5.3.5 Think-aloud and Interview 89 5.3.6 Analysis Methods 90 5.4 Result 1: Quantitative Analysis 92 5.4.1 Detailed Instruction is Preferred over Basic Instruction 93 5.4.2 UX Could Be Worse with Lead-Basic than Assist-Detailed 94 5.4.3 AI is Fun, Useful, Effective, and Efficient 94 5.4.4 No-AI is more Predictable, Comprehensible, and Controllable 95 5.4.5 Even if Predictability is Low, Fun and Interest Can Increase 96 5.5 Result 2: Qualitative Analysis 96 5.5.1 Just Enough Instruction 97 5.5.2 Users Always Want to Lead 99 5.5.3 AI is Similar to Humans But Unpredictable 101 5.5.4 Co-Creation with AI 102 5.6 Limitations 105 5.7 Conclusion 105 6 HOW PEOPLE USE A PRACTICAL APPLICATION OF AN ALGORITHM-BASED SYSTEM USIGN ARTIFICIAL INTELLIGENCE 107 6.1 Motivation 108 6.2 News Robot 110 6.2.1 Selecting Main Event and Data Source 111 6.2.2 Designing News Article Structure 113 6.2.3 Content and Style 113 6.2.4 Generating News Articles 115 6.2.5 Designing NewsRobot User Interface 116 6.3 Study Design 117 6.3.1 Participants 117 6.3.2 Procedures 118 6.3.3 Analysis Methods 119 6.4 Results 1: Quantitative Analysis 120 6.4.1 Selective News Is Less Credible 120 6.4.2 Users Like Both Multimedia and Personalization 121 6.4.3 Quality of Video Is Not Rated Highest 122 6.4.4 NewsRobot Is Accurate but Not Sensational 123 6.5 Results 2: Qualitative Analysis 124 6.5.1 Users Evaluate NewsRobot Features Highly 124 6.5.2 NewsRobot Is Unbiased but Predictable 127 6.5.3 Benefits and Drawbacks of Using Multimedia 128 6.6 Limitations 130 6.7 Conclusion 130 7 DISCUSSION 131 7.1 Human Perception of AI Algorithms 131 7.1.1 Cognitive Dissonance 131 7.1.2 Beyond Technophobia 132 7.1.3 Toward a New Chapter in Human-Computer Interaction 134 7.1.4 Coping with the Potential Danger 135 7.2 Users Interpretation and Evaluation of AI Algorithms 135 7.2.1 Integrate Diverse Expertise and User Perspectives 136 7.2.2 Take Advantage of Peoples Curiosity about AI Principles 137 7.2.3 Provide AI and Users with Mutual Communication 138 7.3 How People Build Sequential Actions with AI Algorithms 139 7.3.1 Let the User Take the Initiative 140 7.3.2 Provide Just Enough Instruction 140 7.3.3 Embed Interesting Elements in the Interaction 141 7.3.4 Ensure Balance 142 7.4 Practical Design of Algorithm-based Systems Using AI 142 7.4.1 Provide Selective news with Adaptable Interface 142 7.4.2 Present Various Multimedia Elements but Not Too Many 144 7.4.3 Importance of Quality Data and Algorithm Refinement 145 7.5 Principles 146 8 CONCLUSION 148 8.1 Summary of Contributions 149 8.2 Future Directions 150 Bibliography 153 ๋…ผ๋ฌธ์ดˆ๋ก 173 ๊ฐ์‚ฌ์˜ ๊ธ€ 176Docto

    Signaling for conferencing in mobile ad hoc networks

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    Mobile Ad hoc NETworks (MANETs) are networks that do not need to be pre-configured. They are composed of transient nodes connected through wireless interfaces. Due to their flexibility, the ease to build and the associated low cost, they are gaining more and more momentum. They are also seen as part of the fourth generation wireless networks. New applications, such as conferencing, are emerging for such networks. Conferencing enables a set of applications such as audio/video conferencing, debating, distance-learning and multi-party gaming. The implementation of conferencing in MANETs is not an easy task due to scarce network resources, heterogeneous devices, frequently changing topology and unstable wireless connections. It challenges each technical aspect of conferencing: signaling, media handling and conference control. Signaling is the control component of conferencing. It handles the session initiation, modification and termination. In this work, we focus on signaling for conferencing in MANETs. Two types of MANETs are considered: standalone MANETs and integrated MANETs/3G networks. Background information is provided, requirements are derived and the state of the art, including signaling protocols such as SIP and H.323, are reviewed. Since there is no existing solution that meets all of the derived requirements, we propose a novel cluster-based signaling architecture that meets the requirements of signaling for standalone MANETs. The clusters are application-layer clusters that are dynamically created and deleted for a conference. We also propose a signaling architectures for integrated MANETs/3G networks. The solution is based on conference gateways. We implement the architectures using SIP extensions. Experimental results are obtained from prototypes and OPNET based simulations. In the prototype, we built the signaling system on a small scale network using IEEE 802.11 ad hoc settings. In the OPNET simulation, we use MANET features. From experiments, we found that clustering is a very promising approach for solving signaling problems in MANETs. Being aware of several performance issues of our signaling systems, we further propose optimization schemes that are based on cross-layer design. We also implement some of these schemes and apply them to our signaling systems. The evaluation shows that the schemes significantly improve the signaling performance

    A Semantic-Oriented Description Framework and Broker Architecture for Publication and Discovery in Cloud Based Conferencing

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    Cloud computing is an emerging paradigm for provisioning network, storage, and computing resources on demand using a pay-per-use model. Conferencing is the conversational exchange of media between several parties. Cloud-based conferencing services can provide benefits such as easy introduction of different types of conferences, resource usage efficiency and scalability. A business model has been recently proposed in a position paper for cloud-based conferencing with the following roles: conference substrate provider, conference infrastructure provider, conference platform provider, conference service provider, and broker. Conference substrates are generally atomic and served as elementary building blocks (e.g. signaling, mixing) of conferencing applications. They can be virtualized and shared for resource efficiency purposes. Multiple conferencing substrates can be combined to build a conferencing service (e.g. a dial-out audio signaling conference service composed from dial-out signaling and audio mixer substrates). The focus of this thesis is to design a semantic-oriented description framework for conferencing substrates and an architecture for their publication and discovery. The description framework is made up of a description language and a cloud-based conference ontology. The conference ontology is modeled on the basis of the interacting roles in the proposed cloud-based conferencing business model. The overall publication and discovery architecture for cloud-based conference substrates is made up of three brokers and the related publication and discovery interfaces. The publication and discovery interfaces are modelled using REpresentation State Transfer (REST) interfaces. A prototype is built to demonstrate the feasibility of this architecture. The effectiveness of the architecture is also proved using the performance measurements

    Proceedings of the Workshop on Knowledge Representation and Configuration, WRKP\u2796

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    Success Factors Impacting Artificial Intelligence Adoption --- Perspective From the Telecom Industry in China

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    As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding the external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The results indicate that compatibility, relative advantage, complexity, managerial support, government involvement, and vendor partnership are significantly related to AI adoption. Managerial capability impacts other organizational capabilities and innovation attributes of AI, but it is indirectly related to AI adoption. Market uncertainty and competitive pressure are not significantly related to AI adoption, but all the external environment factors positively influence managerial capability. The study provides support for firms\u27 decision-making and resource allocation regarding AI adoption. In addition, based on the resource-based view (RBV), this article conducts study 2 which explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from telecom companies in China. The results indicate that at the firm level, the customer value and operational expenses are significantly related to sustainable growth. Also, at the industry level, industry investment significant impacts sustainable growth. Study 2 provides insights for practitioners the way to keep sustainable growth

    A Cloud Platform-as-a-Service for Multimedia Conferencing Service Provisioning

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    Multimedia Conferencing is the real-time exchange of media content (e.g. voice, video and text) between multiple participants. It is the basis of a wide range of conferencing applications such as massively multi-player online games and distance learning applications. For faster development as well as cost efficiency, developers of such conferencing applications can use conferencing services (e.g. dial-in audio conference) provided by third-parties. However, the third-party service providers face several challenges with respect to conferencing service provisioning (i.e. service development, deployment and management). One challenge is mastering complex low-level details of conferencing technologies, protocols and their interactions. Another challenge is resource elasticity. Number of conference participants varies during runtime. So resource utilization in an elastic manner is a critical factor to achieve cost efficiency. Cloud Computing can help tackle these challenges. It is a paradigm for swiftly provisioning a shared pool of configurable resources (e.g. services, applications, network and storage) on demand. It has three main service models: Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). Using a PaaS, service providers can provision conferencing services easily and offer them as SaaS. Nonetheless, cloud-based provisioning of conferencing services still remains a big challenge due to the shortcomings of existing PaaS. In this thesis, a PaaS architecture for conferencing service provisioning is proposed. It is based on a business model from the state of the art. It relies on conferencing IaaSs that, instead of VMs, offer conferencing substrates (e.g. dial-in signaling, video mixer and audio mixer). The conferencing PaaS enables composition of new conferences from substrates on the fly. Moreover, it provides conferencing service providers, who are experienced in programming, with high-level interfaces to abstract the internal complexities of conferencing. In order for PaaS to scale ongoing conferences elastically, an algorithm is also presented in this thesis. The conferencing PaaS is prototyped and performance measurements are made. The proposed algorithmโ€™s performance is also evaluated
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