• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5673-5691
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• 2019

Information centric mobile network can significantly improve the data retrieving efficiency by caching contents at mobile edge. However, the cache pollution attack can affect the data obtaining process severely by requiring unpopular contents deliberately. To tackle the problem, we design an algorithm of mitigating cache pollution attacks in information centric mobile network. Particularly, the content popularity distribution statistic is proposed to detect abnormal behavior. Then a probabilistic caching strategy based on abnormal behavior is applied to dynamically maintain the steady-state distribution for content visiting probability and achieve the purpose of defense. The experimental results show that the proposed scheme can achieve higher request hit ratio and smaller latency for false locality content pollution attack than the CacheShield approach and the baseline approach where no mitigation approach is applied.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.523-524
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• 2009

Peer-to-Peer(P2P) 시스템은 분산된 대용량 데이터를 효율적으로 공유하게 하여 사용자들에게 제공되는 killer application 으로 최근까지 여러 분야에서 연구가 되고 있다. 하지만 P2P 네트워크에서 피어가 소유한 데이터나 공통 관심사 또는 사회적인 관계를 고려하지 않고 무작위로 오버레이가 구성되기 때문에 검색 결과의 제약이 발생한다. 따라서 본 논문에서는 P2P 오버레이상의 효율적인 데이터 검색을 위해서 각 피어가 가지고 있는 데이터와 공통의 관심사를 기반으로 유사성을 측정하여 semantic overlay를 구성하는 기법을 제안한다. 그리고 피어들 간의 semantic proximity는 데이터 요약 기법을 사용하여 측정되며 측정 과정상에서 popular content을 고려하여 semantic proximity의 왜곡현상을 방지하여 semantic link quality의 향상을 가져오는 방안을 도입한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3635-3654
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• 2015

With the rapid development of smart devices and mobile Internet, the video application plays an increasingly important role on mobile devices. Understanding user behavior patterns is critical for optimized operation of mobile live streaming systems. On the other hand, volume based billing models on cloud services make it easier for video service providers to scale their services as well as to reduce the waste from oversized service capacities. In this paper, the watching behaviors of a commercial mobile live streaming system are studied in a content-centric manner. Our analysis captures the intrinsic correlation existing between popularity and watching intensity of programs due to the synchronized watching behaviors with program schedule. The watching pattern is further used to estimate traffic volume generated by the program, which is useful on data volume capacity reservation and billing strategy selection in cloud services. The traffic range of programs is estimated based on a naive popularity prediction. In cross validation, the traffic ranges of around 94% of programs are successfully estimated. In high popularity programs (>20000 viewers), the overestimated traffic is less than 15% of real happened traffic when using upper bound to estimate program traffic.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.135-137
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• 2022

이동성 기반의 기존 엣지 캐싱 연구에서는 인기도가 짧은 시간 급격하게 변화하는 SNM(Shot Noise Model) 콘텐츠를 반영하지 않았다. 동적 인기도 특성을 다루지 않는 경우, 잦은 캐시 미스가 발생하므로 SNM 콘텐츠를 고려하는 것은 중요하다. 이에 본 논문은 이동성을 고려한 기존 연구에 SNM 콘텐츠를 함께 고려하고, 시뮬레이션을 통해 기존 연구 대비 제안 알고리즘의 향상된 캐시 적중률을 확인한다.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

• ETRI Journal
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• v.36 no.3
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• pp.418-428
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• 2014

In social network services, such as Facebook, Google+, Twitter, and certain postings attract more people than others. In this paper, we propose a novel method for predicting the lifespan and retweet times of tweets, the latter being a proxy for measuring the popularity of a tweet. We extract information from retweet graphs, such as posting times; and social, local, and content features, so as to construct prediction knowledge bases. Tweets with a similar topic, retweet pattern, and properties are sequentially extracted from the knowledge base and then used to make a prediction. To evaluate the performance of our model, we collected tweets on Twitter from June 2012 to October 2012. We compared our model with conventional models according to the prediction goal. For the lifespan prediction of a tweet, our model can reduce the time tolerance of a tweet lifespan by about four hours, compared with conventional models. In terms of prediction of the retweet times, our model achieved a significantly outstanding precision of about 50%, which is much higher than two of the conventional models showing a precision of around 30% and 20%, respectively.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.327-333
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• 2021

The purpose of this study is to explore what elements and measures are necessary to grasp the content influence and competitiveness of each OTT platform, which is difficult to measure only with the existing TV broadcast ratings indicator, on the same basis. In this study, based on the RACOI, the daily Top 10 list provided by Netflix was scored to determine the correlation with the viewers' reaction to TV dramas, and a meaningful comparison criterion index was derived. Based on this, the study tried to analyze the share of content provided by the top 3 OTT platforms in Korea. Spearman's correlation analysis was performed for each indicator of RACOI and the Netflix popularity score. It was confirmed that the Netflix popularity score was correlated with the digital video views indicator of RACOI. As a result of analyzing the platforms, it was found that the popularity of the content provided by Netflix and Tving was relatively high. This study did not secure the company's sales data, and there is a limitation in that long-term tracking analysis could not be performed. However, the study extracted the viewer response indicators of TV that are correlated with popularity within Netflix. It is valuable as a basic study of an extended study that compares and confirms the long-term impact of content provided by each OTT platform in the future.

• Journal of Community Nutrition
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• v.8 no.2
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• pp.102-106
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• 2006

The purposes of this study were to investigate the effects of the popularity of menu items in nutrient consumption of school-aged children participating in a School Breakfast Program. The weighed plate waste method was used to determine the nutrient intake of students. The nutrient intake was evaluated based on the popularity of the menu item, gender, and grades. The average intakes of all nutrients except energy, fiber, and sodium were well within the goals. Actual nutrient intake varied based upon the popularity of $entr{\acute{e}}es$ and the popularity of menu items was a main effect in nutrient content of meals. When the most popular $entr{\acute{e}}es$ were served, school-aged children's energy intake and School Breakfast Program participation rate increased. Saturated fat and sodium intakes also were higher than the goal when the most popular $entr{\acute{e}}es$ were served. The significant main effect was grades for total fat (p < 0.05) and calcium (p < 0.05), which was qualified by the two-way interaction between gender and grades for saturated fat (p < 0.05), protein (p<0.1), iron (p<0.01), vitamin C (p<0.01) and carbohydrates (p<0.001). Gender itself was not a significant main effect. Based on the findings, the suggestions for educating school-aged children on more healthful breakfast food choices and reformulating recipes for the popular $entr{\acute{e}}es$ are made. (J Community Nutrition 8(2): 102-106, 2006)

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.113-120
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• 2012

Today, Internet users can easily create and share the digital contents with others through various online content sharing services such as YouTube. So, many portal sites are flooded with lots of user created contents (UCC) in various media such as texts and videos. Estimating popularity of UCC is a crucial concern to both users and the site administrators. This paper proposes a method to predict the popularity of Internet articles, a kind of UCC, using the dynamics of the online contents themselves. To analyze the dynamics, we regarded the access counts of Internet posts as the popularity of them and analyzed the variation of the access counts. We derived a model to predict the popularity of a post represented by the time series of access counts, which is based on an exponential function. According to the experimental results, the difference between the actual access counts and the predicted ones is not more than 10 for 20,532 posts, which cover about 90.7% of the test set.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.315-320
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• 2013

The content of emerging hero is a material of many roles in the development of video content. In recent years, the hero story taking advantage of the powered suit are appearing, and the popularity is also high. The powered suit was first advocated by Robert Anson Heinlein called science fiction writer, and he contributed to creation of diverse and numerous powered suit content. In particular, the powered suit content combined with epic heroes has become popular with many crush to audiences. In this study, what is the powered suit content and analyzed characteristics within the content of the powered suit by content analysis of utilizing the powered suit materials. It is thought that the powered suit content is gaining popularity to a large audience because it focused on realistic, scientific storyline than a traditional hero narrative.