Jinyoung Han

A Survey on content-oriented networking for efficient content delivery

As multimedia contents become increasingly dominant and voluminous, the current Internet architecture will reveal its inefficiency in delivering time-sensitive multimedia traffic. To address this issue, there have been studies on contentoriented networking (CON) by decoupling contents from hosts at the networking level. In this article, we present a comprehensive survey on content naming and name-based routing, and discuss further research issues in CON. We also quantitatively compare CON routing proposals, and evaluate the impact of the publish/subscribe paradigm and in-network caching.

Collecting, organizing, and sharing pins in pinterest: interest-driven or social-driven?

Pinterest, a popular social curating service where people collect, organize, and share content (pins in Pinterest), has gained great attention in recent years. Despite the increasing interest in Pinterest, little research has paid attention to how people collect, manage, and share pins in Pinterest. In this paper, to shed insight on such issues, we study the following questions. How do people collect and manage pins by their tastes in Pinterest? What factors do mainly drive people to share their pins in Pinterest? How do the characteristics of users (e.g., gender, popularity, country) or properties of pins (e.g., category, topic) play roles in propagating pins in Pinterest? To answer these questions, we have conducted a measurement study on patterns of pin curating and sharing in Pinterest. By keeping track of all the newly posted and shared pins in each category (e.g., animal, kids, womens fashion) from June 5 to July 18, 2013, we built 350 K pin propagation trees for 3 M users. With the dataset, we investigate: (1) how users collect and curate pins, (2) how users share their pins and why, and (3) how users are related by shared pins of interest. Our key finding is that pin propagation in Pinterest is mostly driven by pins properties like its topic, not by users characteristics like her number of followers. We further show that users in the same community in the interest graph (i.e., representing the relations among users) of Pinterest share pins (i) in the same category with 94% probability and (ii) of the same URL where pins come from with 89% probability. Finally, we explore the implications of our findings for predicting how pins are shared in Pinterest.

Bundling practice in BitTorrent: what, how, and why

We conduct comprehensive measurements on the current practice of content bundling to understand the structural patterns of torrents and the participant behaviors of swarms on one of the largest BitTorrent portals: The Pirate Bay. From the datasets of the 120K torrents and 14.8M peers, we investigate what constitutes torrents and how users participate in swarms from the perspective of bundling, across different content categories: Movie, TV, Porn, Music, Application, Game and E-book. In particular, we focus on: (1) how prevalent content bundling is, (2) how and what files are bundled into torrents, (3) what motivates publishers to bundle files, and (4) how peers access the bundled files. We find that over 72% of BitTorrent torrents contain multiple files, which indicates that bundling is widely used for file sharing. We reveal that profit-driven BitTorrent publishers who promote their own web sites for financial gains like advertising tend to prefer to use the bundling. We also observe that most files (94%) in a bundle torrent are selected by users and the bundle torrents are more popular than the single (or non-bundle) ones on average. Overall, there are notable differences in the structural patterns of torrents and swarm characteristics (i) across different content categories and (ii) between single and bundle torrents.

MASERATI: mobile adaptive streaming based on environmental and contextual information

Wireless/mobile video streaming has become increasingly popular, which makes wireless link bandwidth scarce. To provide streaming services to mobile users, it is crucial to adapt to the link condition and traffic fluctuation. We investigate which factors in natural environments and user contexts affect the available link bandwidth. To this end, we conduct a measurement study which contains 38 repeated trips along the same 5~km circular road in the campus of Seoul National University in April and May 2013. We measure the download throughput of video streaming from two different networks (3G and 4G LTE) with varying location, time, humidity, and speed. Our measurement results reveal that the humidity and location are the more important factors in the 3G network, while the speed, time, and location are the more important ones in the 4G LTE network to predict the available link bandwidth. We then propose an adaptive video streaming framework, MASERATI, where the information of environments and contexts is used to predict the available bandwidth. We demonstrate that MASERATI significantly improves the QoE of mobile streaming users in terms of the playout success rate, video quality, and stability, in comparison to DASH.

How to Mitigate Signal Dragging during Wardriving

In wardriving, test devices in moving vehicles measure received signal strengths (RSSs) from nearby base stations (BSs) and record them with location information, which is a key component in localization technologies. In this article, the authors analyze the wardriving data in real WCDMA, GSM, and Wi-Fi networks and describe how signal dragging degrades their performance. They also propose three methods for postprocessing wardriving data to filter out any outdated BS information, thereby mitigating this effect.

Unveiling group characteristics in online social games: a socio-economic analysis

Understanding the group characteristics in MMORPGs is important in user behavior studies since people tend to gather together and form groups due to their inherent nature. In this paper, we analyze the group activities of users in Aion, one of the largest MMORPGs, based on the records of the activities of 94,497 users. In particular, we focus on (i) how social interactions within a group differ from the ones across groups, (ii) what makes a group rise, sustain, or fall, (iii) how group members join and leave a group, and (iv) what makes a group end. We first find that structural patterns of social interactions within a group are more likely to be close-knit and reciprocative than the ones across groups. We also observe that members in a rising group (i.e., the number of members increases) are more cohesive, and communicate with more evenly within the group than the ones in other groups. Our analysis further reveals that if a group is not cohesive, not actively communicating, or not evenly communicating among members, members of the group tend to leave.

How prevalent is content bundling in BitTorrent

Despite the increasing interest in content bundling in BitTorrent systems, there are still few empirical studies on the bundling practice in real BitTorrent communities. In this paper, we conduct comprehensive measurements on one of the largest BitTorrent portals: The Pirate Bay. From the torrents data set collected for 38 days from April to May, 2010, we study how prevalent bundling is and how many files are bundled in a torrent, across different types of contents shared: Movie, Porn, TV, Music, Application, E-book, and Game.

Unveiling the adoption and cascading process of OSN-based gifting applications

This paper demystifies the adoption and cascading process of OSN-based applications that grow via user invitations. We analyze a detailed large-scale dataset of a popular Facebook gifting application, iHeart, that contains more than 2 billion entries of user activities generated by 190 million users during a span of 64 weeks. We investigate: (1) how users invite their friends to an OSN-based application, (2) what factors drive the cascading process of application adoptions, and (3) what are the good predictors of the ultimate cascade sizes. We find that sending or receiving a large number of invitations does not necessarily help to recruit new users to iHeart. We also identify a set of distinctive features that are good predictors of the growth of the application adoptions in terms of final population size. Finally, based on the insights learned from our analyses, we propose a prediction model to infer whether a cascade of application adoption will continue to grow in the future based on observing the initial adoption process. Results show our proposed model can achieve high precision (over 80%) in iHeart as well as in another OSN-based gifting application, Hugged.

Sharing Topics in Pinterest: Understanding Content Creation and Diffusion Behaviors

Pinterest provides a social curation service where people can collect, organize, and share content (pins in Pinterest) that reflect their interests. This paper investigates (1) the differences in pinning (i.e., the act of posting a pin) and repinning (i.e., the act of sharing other users pin) behaviors by topics and user gender, and (2) the relations among topics in Pinterest. We conduct a measurement study using a large-scale dataset (1.6 M pins shared by 1.1 M users) in Pinterest. We show that there is a notable discrepancy between pinning and repinning behaviors on different topics. We also show that male and female users show different behaviors on different topics in terms of dedication, responsiveness, and sentiment. By introducing the notion of a Topic Network (TN) whose nodes are topics and are linked if they share common users, we analyze how topics are related to one another, which can give a valuable implication on topic demand forecasting or cross-topic advertisement. Lastly, we explore the implications of our findings for predicting a users interests and behavioral patterns in Pinterest.

Systematic Support for Content Bundling in BitTorrent Swarming

Despite the tremendous success of BitTorrent, its swarming system suffers from a fundamental limitation: lower or no availability of unpopular contents. Menasche et al. showed that bundling is one solution to mitigate this availability problem; it improves the availability and reduces download times for unpopular contents by combining multiple files into a single swarm. While current content bundling is done by manually and in an ad-hoc manner decided by publishers, we propose a systematic content bundgling scheme based on content similarity in swarming systems to maximize the gain in availability and download speed. We evaluate three systematic bundling algorithms (cosine, Levenshtein distance, matching coefficient distance) and we find that our systematic bundling scheme increases the number of content files in a swarm, which improves content availability. To the best of our knowledge, this is the first work which raises and explores the possibilities and benefits of systematic content bundling in swarming systems.