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

Yu, Hongfang; Zheng, Dongdong; Zhao, Ben Y.; Zheng, Weimin

doi:10.1145/1217935.1217968

Cited by 437 publications

(284 citation statements)

References 16 publications

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“…present an analysis of a video-on-demand media server from China [745], and Tang et al present a similar analysis of two media servers belonging to HP [674]. Among their findings are the following:…”

Section: Media and Streamingmentioning

confidence: 97%

“…The diurnal cycle is a well-known and widely recognized phenomenon, which appears in practically all workloads (e.g., [326,320,524,63,761,745,756,381,192,42]). An example from parallel supercomputers is shown in Figure 6.34.…”

Section: Periodicity and The Diurnal Cyclementioning

confidence: 99%

“…However, details may differ among different types of workloads. For example, in work-related activities one often sees a dip in activity during lunchtime, but in recreational activities such as watching video-on-demand there may be a peak of activity during lunchtime [745]. Also, the peak activity may be in the morning, in the afternoon, or in the evening -as happens for Internet activity at some ISPs, where the peak activity occurs when people return home after work [745,381].…”

Section: Periodicity and The Diurnal Cyclementioning

confidence: 99%

“…An interesting study of web search behavior showed that the popularity of different search topics changes at different times of day, with music searches peaking at 3-4 AM, porn at 5-6 AM, and personal finance at 8-10 AM [63]. The largest shifts in popularity in video-on-demand also occur during the early morning hours [745].…”

Section: Categorical Datamentioning

confidence: 99%

“…[326,320,524,63,761,745,756,381,192]). Activity patterns typically peak during the day in the morning and afternoon and are low at night.…”

Section: Daily Activity Cyclementioning

confidence: 99%

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Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

196

131

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Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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Section: Media and Streamingmentioning

confidence: 97%