Network overload avoidance by traffic engineering and content caching

The Internet traffic volume continues to grow at a great rate, now driven by video and TV distribution. For network operators it is important to avoid congestion in the network, and to meet service level agreements with their customers. This thesis presents work on two methods operators can use to reduce links loads in their networks: traffic engineering and content caching. This thesis studies access patterns for TV and video and the potential for caching. The investigation is done both using simulation and by analysis of logs from a large TV-on-Demand system over four months. The results show that there is a small set of programs that account for a large fraction of the requests and that a comparatively small local cache can be used to significantly reduce the peak link loads during prime time. The investigation also demonstrates how the popularity of programs changes over time and shows that the access pattern in a TV-on-Demand system very much depends on the content type. For traffic engineering the objective is to avoid congestion in the network and to make better use of available resources by adapting the routing to the current traffic situation. The main challenge for traffic engineering in IP networks is to cope with the dynamics of Internet traffic demands. This thesis proposes L-balanced routings that route the traffic on the shortest paths possible but make sure that no link is utilised to more than a given level L. L-balanced routing gives efficient routing of traffic and controlled spare capacity to handle unpredictable changes in traffic. We present an L-balanced routing algorithm and a heuristic search method for finding L-balanced weight settings for the legacy routing protocols OSPF and IS-IS. We show that the search and the resulting weight settings work well in real network scenarios

Focusing on the production process of major agencies

학위논문(석사) -- 서울대학교대학원 : 국제대학원 국제학과(국제지역학전공), 2023. 2. 박지환.As BTS became an undisputable sales juggernaut, the Korean idol industry also get global attention. When looking at the share of each country in the global idol market, Japan dominated until the early 2000s. However, the Korean idol industry, which grew through benchmarking Japan, has been receiving attention in Asia since the 2000s, and in the 2020s, it is receiving worldwide attention. The economic ramifications of Korean idols are huge, and what they eat, use, and the places they visit to attract the attention of fans and extend to other industries such as K-beauty and K-foods. This thesis analyzed the idol industry in South Korea and Japan. Among the three main actors that make up the idol industry which is 'idols (celebrities) - fans - agency', this research subject is limited to the agency or the production side. The research also focused on the management aspects of the agency, that is, the activities of the agency in the production process, to analyze the success factors of the two countries. It proves that the process of developing the idol industry in the two countries is very different. Specifically, the success of idols in both countries was explained in the framework of thorough management strategies and training systems of major agencies, the producers. First, in the management strategies of agencies, it argued that Korea had grown in a strategy keeping pace with globalization, glocalization, and logalization, and a strategy of storytelling using global platforms like YouTube, while Japan had grown in a strategy keeping pace with localization, and storytelling strategy that focused analog methods. Second, in terms of the training system, it argued that the industry grew in Korea through boot-camp style training, the pursuit of perfect idols-total manufacturing-, and a rat-race system based on meritocracy while in Japan, it grew through individual training, the pursuit of developing type idols-consuming intimacy- and a rat-race system based on human egalitarianism.방탄소년단(BTS)의 세계적인 성공과 함께 21세기 아이돌 산업은 한국을 견인하는 산업의 하나로 해를 거듭할수록 그 규모가 커지고 있다. 글로벌 아이돌시장에 있어 각국의 점유율을 살펴보면 1980년대까지만 해도 일본이 압도적이었다. 그러나 일본을 벤치마킹하면서 성장해 온 한국의 아이돌 산업은 2000년대부터 아시아에서 주목을 받고, 2020년대 이르러서는 세계적인 관심을 받고 있다. 한국 아이돌이 갖는 경제적 파생 효과는 엄청나며 그들이 먹은 것, 사용한 것, 가본 곳 등이 팬들의 관심을 끌고, K-beauty, K-foods 등으로 타산업에까지 영향을 뻗친다. 본 연구의 목적은 한국 아이돌산업은 왜 성공하고, 일본은 왜 정체하는지를 알아보는 것이다. 특히 왜 일본은 지역화의 길을 걷고, 한국은 세계화의 길을 걸었는지, 한국의 대표 기획사들의 전략은 무엇이고, 일본의 대표 기획사들의 전략은 무엇인지를 보다 깊이 알아본다. 아이돌 산업을 구성하는 3대 주체는 아이돌(연예인) – 팬 – 기획사 이다. 이 가운데 연구 대상을 기획사로 한정하고, 연구 내용 또한 기획사의 경영적 측면, 즉 생산과정에서의 기획사의 활동을 중심으로 양국 아이돌의 성공 요인을 분석하며 양국의 아이돌 산업을 발전시켜온 과정이 매우 다르다는 사실을 입증한다. 구체적으로는 양국 아이돌의 성공을 생산자인 주요 기획사들의 철저한 경영전략과 훈련시스템이라는 틀에서 설명하는데, 첫째 기획사들의 경영전략에 있어 한국은 국제화와 세방화(glocalization)에 발맞춘 전략과 세계적인 플랫폼 YouTube를 이용한 SNS스토리텔링 전략으로, 일본은 국내화와 아날로그 방식에 치중한 스토리텔링 전략으로 성장하였다고 주장했다. 둘째 훈련시스템 측면에서는 한국은 군대식 훈련, 완성형 아이돌 추구, 실력주의에 기반한 무한경쟁체제로, 일본은 개별 훈련, 성장형 아이돌을 추구하면서, 인간평등주의에 기반한 무한 경쟁체제로 산업을 키웠다고 주장한다.I. Introduction 1 1. Background 1 2. Literature Review 6 2.1 Hallyu (Korean Wave) and Japanese Culture 7 2.2 Localization, Globalization, Glocalization, and Logalization 14 2.3 Organizational Cultures 17 3. Research Methodology 20 II. Music Market Environment and Entertainment Agencies in Korea and Japan 23 1. Music Market Environment 23 2. Characteristics of Talent Agencies in Korea and Japan 29 2.1 JYP, YG, and HYBE in Korea & Hello Project! and AKB series in Japan 29 2.2 SM Entertainment and Johnny's Associates 38 2.2.1 SM Entertainment 39 2.2.2 Johnny's Associates 46 III. Strategies of Korea and Japan's Agencies 54 1. Management Strategies 55 1.1 Glocalization & Logalization (Korea) vs. Localization (Japan) 55 1.2 SNS Strategies of both countries 65 2. Organizational Cultures 72 2.1 NFOB vs. FOB 72 2.2 Modularization vs. Shokunin 75 3. Training Strategies 77 3.1 Boot-camp style training vs. Individual training 78 3.2 Total manufacturing vs. Consuming "Intimacy" 82 3.3 Rat-race 85 IV. Conclusion 90 Bibliography 93 Abstract in Korean 100석

Movies, TV programs and Youtube channels

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2021.8. 조성준.The content market, including video content market, is a high-risk, high-return industry. Because the cost of copying and distributing the created video content is very low, large profit can be generated upon success. However, as content is an experience good, its quality cannot be judged before purchase. Hence, marketing has an important role in the content market because of the asymmetry of information between suppliers and consumers. Additionally, it has the characteristics of One Source Multi Use; if it is successful, additional profits can be created through various channels. Therefore, it is important for the content industry to correctly distinguish content with a high probability of success from the one without it and to conduct effective marketing activities to familiarize consumers with the product. Herein, we propose a methodology to assist in data-based decision-making using machine learning models and help in identifying problematic issues in video content markets such as movies, TV programs, and over-the-top (OTT) market. In the film market, although marketing is very important, decisions are still made based on the sense of practitioners. We used the market research data collected through online and offline surveys to learn a model that can predict the number of audiences on the opening-week Saturday, and then use the learned model to propose a method for effective marketing activities. In the TV program market, programming is performed to improve the overall viewership by matching TV programs and viewer groups well. We learn a model that predicts the audience rating of a program using the characteristics of the program and the audience-rating information of the programs before, after, and at the same time, and use the resulting data to assist in decision-making to find the optimal programming scenario. The OTT market is facing a new problem of user's perception bias caused by the “recent recommendation” system. In the fields of politics and news particularly, if the user does not have access to different viewpoints because of the recommendation service, it may create and/or deepen a bias toward a specific political view without the user being aware of it. In order to compensate for this, it is important to use the recommended channel while the user is well aware of what kind of channel it is. We built a channel network in the news/political field using the data extracted from the comments left by users on the videos of each channel. In addition, we propose a method to compensate for the bias by classifying networks into conservative and progressive channel clusters and presenting the topography of the political tendencies of YouTube channels.1 Introduction 1 2 Prediction of Movie Audience on First Saturday with Decision Trees 5 2.1 Background 5 2.2 Related work 9 2.3 Predictive model construction 15 2.3.1 Data 15 2.3.2 Target variable 17 2.3.3 Predictor variable 19 2.3.4 Decision Tree and ensemble prediction models 28 2.4 Prediction model evaluation 29 2.5 Summary 37 3 Prediction of TV program ratings with Decision Trees 40 3.1 Background 40 3.2 Related work 42 3.2.1 Research on the ratings themselves 42 3.2.2 Research on broadcasting programming 44 3.3 Predictive model construction 45 3.3.1 Target variable 45 3.3.2 Predictor variable 46 3.3.3 Prediction Model 48 3.4 Prediction model evaluation 50 3.4.1 Data 50 3.4.2 Experimental results 51 3.5 Optimization strategy using the predictive model 54 3.5.1 Broadcasting programming change process 56 3.5.2 Case Study 57 3.6 Summary 60 4 Relation detection of YouTube channels 62 4.1 Background 62 4.2 Related work 65 4.3 Method 67 4.3.1 Channel representation 68 4.3.2 Channel clustering with large k and merging clusters by keywords 71 4.3.3 Relabeling with RWR 73 4.3.4 Isolation score 74 4.4 Result 74 4.4.1 Channel representation 74 4.4.2 Channel clustering with large k and merging clusters by keywords 76 4.4.3 Relabeling with RWR 77 4.4.4 Isolation score 79 4.5 Discussion 80 4.5.1 On the Representativeness of the Channel Preferences of the Users from Their Comments 80 4.5.2 On Relabeling with RWR 82 4.6 Summary 83 5 Conclusion 85 5.1 Contribution 85 5.2 Future Direction 87 Bibliography 91 국문초록 110박

Combining machine-based and econometrics methods for policy analytics insights

National Research Foundation (NRF) Singapore under International Research Centre @ Singapore Funding Initiativ

Redefining the anthology : forms and affordances in digital culture

Alors que le modèle économique de la télévision américaine, longtemps dominant, a été mis au défi de diverses manières par les changements industriels et technologiques de ces dernières années, des formes narratives de plus en plus hétérogènes sont apparues, qui se sont ajoutées aux structures sérielles originaires. La diversité des formes télévisuelles est devenue particulièrement évidente depuis que les paysages télévisuels nationaux et locaux ont commencé à s’ouvrir aux marchés étrangers situés en dehors des États-Unis, pour finalement adopter une perspective transnationale et globale. La transition vers la télévision distribuée sur Internet a joué un rôle central dans cette fragmentation formelle et la nouvelle dynamique de la diffusion en ligne a ouvert une different perspective pour comprendre le flux mondial de contenus télévisuels, qui reflète aujourd'hui un environnement multimédia et numérique hautement interconnecté et mis en réseau. En effet, la multiplication des services de vidéo à la demande oblige la sérialité à s’adapter au paysage médiatique contemporain, donnant naissance à des produits audiovisuels pouvant être transférés en ligne et présentant des spécificités de production, de distribution et de réception. L’un des résultats de tels changements dans les séries télévisées américaines à l’aube du XXIe siècle est la série anthologique divisée en différentes saisons avec des histoires distinctes, et pourtant liées par le ton et le style. Ma recherche se situe dans un tel contexte technologique, industriel et culturel, où le contenu télévisuel est de plus en plus fragmenté. Compte tenu de cette fragmentation des contenus, cette thèse examine la manière dont les contenus télévisuels contemporains sont distribués, dans l'interaction entre les processus de recommandation basés sur des algorithmes et les pratiques éditoriales plus traditionnelles. L’objectif de ce projet est donc d’étudier la manière dont certaines structures narratives typiques de la forme de l’anthologie apparaissent dans le contexte de la sérialité de la télévision nord-américaine, à partir de conditions spécifiques de production, de distribution et de consommation dans l’industrie des médias. En se concentrant sur l'évolution (dimension temporelle et historique) et sur la circulation numérique (dimension spatiale, géographique) des séries d'anthologies américaines, et en observant les particularités de leur production et de leur style, ainsi que leurs réseaux de distribution et les modes de consommation qu'elles favorisent, cette thèse s’inscrit finalement dans une conversation plus vaste sur les études culturelles et numériques. L’objectif final est d’étudier la relation entre les formes anthologiques, les plateformes de distribution et les modèles de consommation, en proposant une approche comparative de l’anthologie qui soit à la fois cross-culturelle, crosshistorique, cross-genre et qui prenne en consideration les pratiques pre- et post-numériques pour l’organisation de contenus culturels.As the longtime dominant U.S. television business model has been challenged in various ways by industrial and technological changes in recent years, more heterogeneous narrative forms have emerged in addition to original serial structures. The diversity of televisual forms became particularly evident since national, local television landscapes started opening up to foreign markets outside of the U.S., finally embracing a transnational, global perspective and tracing alternative value-chains. The transition to internet-distributed television played a pivotal role in this formal fragmentation and new dynamics of online streaming opened up another path for understanding the flow of television content, which today reflects a highly interconnected, networked media and digital environment. Indeed, the proliferation of video-on-demand services is forcing seriality to adapt to the contemporary mediascape, giving rise to audiovisual products that can be transferred online and present specificities in production, distribution and reception. One of the outcomes of such changes in U.S. television series at the dawn of the twenty-first century is the anthology series divided in different seasons with separate stories, yet linked by tone and style. My research positions itself in such a technological, industrial and cultural context, where television content is increasingly fragmented. Given such a fragmentation, this thesis considers the ways contemporary television content is distributed in the interaction between algorithmic-driven recommendation processes and more traditional editorial practices. The aim of the project is to investigate the way certain narrative structures typical of the anthology form emerge in the context of U.S. television seriality, starting from specific conditions of production, distribution and consumption in the media industry. By focusing on the evolution (temporal, historical dimension) and on the digital circulation (spatial, geographic dimension) of U.S. anthology series, and observing the peculiarities in their production and style, as well as their distributional networks and the consumption patterns they foster, this thesis ultimately insert itself into a larger conversation on digital-cultural studies. The final purpose is to examine the relation between anthological forms, distribution platforms and consumption models, by proposing a comparative approach to the anthology that is at the same time cross-cultural, cross-historical, cross-genre and accounting for both pre- and post-digital practices for cultural content organization

Digital tools in media studies: analysis and research. An overview

Digital tools are increasingly used in media studies, opening up new perspectives for research and analysis, while creating new problems at the same time. In this volume, international media scholars and computer scientists present their projects, varying from powerful film-historical databases to automatic video analysis software, discussing their application of digital tools and reporting on their results. This book is the first publication of its kind and a helpful guide to both media scholars and computer scientists who intend to use digital tools in their research, providing information on applications, standards, and problems

Digital Tools in Media Studies

Digital tools are increasingly used in media studies, opening up new perspectives for research and analysis, while creating new problems at the same time. In this volume, international media scholars and computer scientists present their projects, varying from powerful film-historical databases to automatic video analysis software, discussing their application of digital tools and reporting on their results. This book is the first publication of its kind and a helpful guide to both media scholars and computer scientists who intend to use digital tools in their research, providing information on applications, standards, and problems