Understanding user behavior in large-scale video-on-demand systems Export

@article{citeulike:5368064, abstract = {Video-on-demand over IP (VOD) is one of the best-known examples of "next-generation" Internet applications cited as a goal by networking and multimedia researchers. Without empirical data, researchers have generally relied on simulated models to drive their design and developmental efforts. In this paper, we present one of the first measurement studies of a large VOD system, using data covering 219 days and more than 150,000 users in a VOD system deployed by China Telecom. Our study focuses on user behavior, content access patterns, and their implications on the design of multimedia streaming systems. Our results also show that when used to model the user-arrival rate, the traditional Poisson model is conservative and overestimates the probability of large arrival groups. We introduce a modified Poisson distribution that more accurately models our observations. We also observe a surprising result, that video session lengths has a weak inverse correlation with the video's popularity. Finally, we gain better understanding of the sources of video popularity through analysis of a number of internal and external factors.}, address = {New York, NY, USA}, author = {Yu, Hongliang and Zheng, Dongdong and Zhao, Ben Y. and Zheng, Weimin}, citeulike-article-id = {5368064}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1217968}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1218063.1217968}, doi = {10.1145/1218063.1217968}, issn = {0163-5980}, journal = {SIGOPS Oper. Syst. Rev.}, keywords = {trend, vod}, number = {4}, pages = {333--344}, posted-at = {2009-08-05 05:19:34}, priority = {5}, publisher = {ACM}, title = {Understanding user behavior in large-scale video-on-demand systems}, url = {http://dx.doi.org/10.1145/1218063.1217968}, volume = {40}, year = {2006} }

TY - JOUR ID - citeulike:5368064 L3 - citeulike-article-id:5368064 N2 - Video-on-demand over IP (VOD) is one of the best-known examples of "next-generation" Internet applications cited as a goal by networking and multimedia researchers. Without empirical data, researchers have generally relied on simulated models to drive their design and developmental efforts. In this paper, we present one of the first measurement studies of a large VOD system, using data covering 219 days and more than 150,000 users in a VOD system deployed by China Telecom. Our study focuses on user behavior, content access patterns, and their implications on the design of multimedia streaming systems. Our results also show that when used to model the user-arrival rate, the traditional Poisson model is conservative and overestimates the probability of large arrival groups. We introduce a modified Poisson distribution that more accurately models our observations. We also observe a surprising result, that video session lengths has a weak inverse correlation with the video's popularity. Finally, we gain better understanding of the sources of video popularity through analysis of a number of internal and external factors. IS - 4 JF - SIGOPS Oper. Syst. Rev. SN - 0163-5980 AD - New York, NY, USA EP - 344 TI - Understanding user behavior in large-scale video-on-demand systems PB - ACM VL - 40 SP - 333 KW - trend KW - vod AU - Yu, Hongliang AU - Zheng, Dongdong AU - Zhao, Ben AU - Zheng, Weimin PY - 2006/// UR - http://dx.doi.org/10.1145/1218063.1217968 ER -