• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.518-531
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• 2004

This paper discusses a testbed architecture for implementing scalable service differentiation in the Internet. The differentiated services (DiffServ) testbed architecture is based on a model in which a bandwidth broker (BB) can control network resources, and the ALTQ can reserve resources in a router to guarantee a Quality of Service (QoS) for incoming traffic to the testbed. The reservation and releasemessage for the ALTQ is contingent upon a decision message in the BE. The BB has all the information in advance, which is required for a decision message, in the form of PIB. A signaling protocol between the BB and the routers is the COPS protocol proposed at the IETF. In terms of service differentiation, a user should make an SLA in advance, and reserve required bandwidth through an RAR procedure. The SLA and RAR message between a user and the BB has implemented with the COPS extension which was used between a router and the BB. We evaluates the service differentiation for the video streaming in that the EF class traffic shows superb performance than the BE class traffic where is a network congestion. We also present the differentiated service showing a better packet receiving rate, low packet loss, and low delay for the EF class video service.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.140-148
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• 2009

Recent advances in communication and multimedia technologies make it possible to provide video-on-demand(VOD) services and people can access video servers over the Internet at any time using their electronic devices, such as PDA, mobile phone and digital TV. Each device has different processing capabilities, energy budgets, display sizes and network connectivities. To support such diverse devices, multiple versions of videos are needed to meet users' requests. In general cases, VOD servers cannot store all the versions of videos due to the storage limitation. When a device requests a stored version, the server can send the appropriate version immediately, but when the requested version is not stored, the server first converts some stored version to the requested version, and then sends it to the client. We call this conversion process transcoding. If transcoding occurs frequently in a VOD server, the CPU resource of the server becomes insufficient to response to clients. Thus, to admit as many requests as possible, we need to maximize the CPU availability. In this paper, we propose a new algorithm to select versions from those stored on disk using a branch and bound technique to maximize the CPU availability. We also explore the impact of these storage management policies on streaming to heterogeneous users.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.95-104
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• 2007

Mobile multimedia services such as TV-call or video streaming are gradually becoming popular in the 3rd or more generation mobile network (IMT-2000). Multimedia traffic is expected to continue increasing into the coming years, and IP technology is considered to be the efficient way of transporting such huge volumes of multimedia traffic. IP-based IMT network platform represents an evolution from IMT-2000. The structure of IP-based IMT network as ubiquitous platform is three-layered model : Middleware including Network Control PlatForm (NCPF) and Service Support PlatForm (SSPF), IP-BackBone (IP-BB), access network including sensor network. Mobility Management (MM) architecture in NCPF is proposed for IP-based IMT network in order to manage routing information and location information separately. The generous existing method of multicast control in IP-based IMT network is Remote Subscription. But Remote Subscription has problem that should be reconstructed whole multicast tree when sender in multicast tree moves to another area. To solve this problem, we propose the way to put Multicast-manager in NCPF.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.1
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• pp.9-18
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• 2018

Enhancing performance of big data analytics in distributed environment has been issued because most of the big data related applications such as machine learning techniques and streaming services generally utilize distributed computing frameworks. Thus, optimizing performance of those applications at Spark has been actively researched. Since optimizing performance of the applications at distributed environment is challenging because it not only needs optimizing the applications themselves but also requires tuning of the distributed system configuration parameters. Although prior researches made a huge effort to improve execution performance, most of them only focused on one of three performance optimization aspect: application design, system tuning, hardware utilization. Thus, they couldn't handle an orchestration of those aspects. In this paper, we deeply analyze and model the application processing procedure of the Spark. Through the analyzed results, we propose performance optimization schemes for each step of the procedure: inner stage and outer stage. We also propose appropriate partitioning mechanism by analyzing relationship between partitioning parallelism and performance of the applications. We applied those three performance optimization schemes to WordCount, Pagerank, and Kmeans which are basic big data analytics and found nearly 50% performance improvement when all of those schemes are applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.914-923
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• 2015

Recently, as the number of smart devices (such as smart TV or Web based IPTV) increases, the way of digital broadcast contents is changed. This change leads that conventional broadcast media accepts Web platform and its services to provide more quality contents. Based on this change, in education field, education broadcasting also follows the trend. The traditional education broadcasting platforms, which just delivered the lecture in one-way, are utilized the Web technology to make interaction between teacher and student. Current education platforms, however, are insufficient to satisfy users' demands for two-way interactions. This paper proposes a new remote collaborative learning platform which able to provide high interactivity among users. Based on new functional requirements from original use case, the platform provides collaborative contents sharing and collaborative video streaming techniques by utilizing WebRTC (Web Real-Time Communication) technology. The implementation demonstrates the operability of proposed system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.16-27
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• 2017

IEEE 802.15.6 standard, a Wireless Body Area Network, aims to transfer not only medical data but also non-medical data, such as physical activity, streaming, multimedia game, living information, and entertainment. Services which transfer those data have very various data rates, intervals and frequencies of continuous access to a medium. Therefore, an efficient anti-collision operations and medium assigning operation have to be carried out when multiple nodes with different data rates are accessing shared medium. IEEE 802.15.6 standard for CSMA/CA medium access control method distributes access to the shared medium, transmits a control packet to avoid collision and checks status of the channel. This method is energy inefficient and causes overhead. These disadvantages conflict with the low power, low cost calculation requirement of wireless body area network, shall minimize such overhead for efficient wireless body area network operations. Therefore, in this paper, we propose a medium access scheduling scheme, which adjusts the time interval for accessing to the shared transmission medium according to the amount of data for generating respective sensor node, and a priority control algorithm, which temporarily adjusts the priority of the sensor node that causes transmission concession due to the data priority until next successful transmission to ensure fairness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.453-463
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• 2021

The purpose of this study is to establish the most severe impacts of Covid-19 in the field of the performing arts and to explore countermeasures taken both at home and abroad. This study has been conducted through literature surveys. The conclusion is as follows. First, since the outbreak of Covid-19, theater venues around the world have actively taken part in uploading recorded performances to streaming services. Secondly, these performance visualizings are generally considered as being complimentary goods rather than a substitute for live performance. Thirdly, although more audiences are tuning into watch on-line performances, consumption is concentrated on a few theaters which have a worldwide reputation and a broad range of content. Fourthly, to tackle the impact that Covid-19, the UK government announced a series of job protection schemes in the field of the Arts. In addition, Arts Council England prepared an emergency response package. In Korea, some countermeasures such as government support for artists and cultural establishments have also been implemented. Lastly, some suggestions for the sector. I conclude that there is an need for domestic companies to secure core contents of significant quality and to make strategic alliances with leading overseas performance companies so that they may cooperate together.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.149-156
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• 2021

OTT service, which allows video content to be viewed as a streaming service on the Internet network, has recently attracted a lot of attention, and the number of users is also increasing rapidly. It would be a natural strategy for OTT companies to acquire more content to gain a competitive advantage in relations with traditional media companies and other OTT companies. However, there are research results to show that the investment in facilities by Internet service providers who must transport the increasing Internet traffic from OTT provider to end users should increase as the amount of Internet traffic originated by OTT services also increases. This study empirically analyzed how content investment by Netflix, a leading OTT company, affects its revenue growth and network investment by Internet service providers through a polynomial distributed lag model. And the analysis results show that Netflix's content investment contributes to the company's increase in revenue, and also has an effect on the increase in network investment by Internet service providers. This result confirms that OTT operators' content acquisition strategy is a valid management strategy, and empirically supports the study results that OTT operators need to share the cost of Internet network facility investment.