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A hierarchical characterization of a live streaming media workload
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Source Internet Measurement Conference archive
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment table of contents
Marseille, France
SESSION: Session 5: P2P and streaming table of contents
Pages: 117 - 130  
Year of Publication: 2002
ISBN:1-58113-603-X
Authors
Eveline Veloso  Federal University of Minas Gerais, Brazil
Virgílio Almeida  Federal University of Minas Gerais, Brazil
Wagner Meira  Federal University of Minas Gerais, Brazil
Azer Bestavros  Boston University
Shudong Jin  Boston University
Sponsor
SIGCOMM: ACM Special Interest Group on Data Communication
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 75,   Citation Count: 21
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ABSTRACT

We present what we believe to be the first thorough characterization of live streaming media content delivered over the Internet. Our characterization of over 3.5 million requests spanning a 28-day period is done at three increasingly granular levels, corresponding to clients, sessions, and transfers. Our findings support two important conclusions. First, we show that the nature of interactions between users and objects is fundamentally different for live versus stored objects. Access to stored objects is user driven, whereas access to live objects is object driven. This reversal of active/passive roles of users and objects leads to interesting dualities. For instance, our analysis underscores a Zipf-like profile for user interest in a given object, which Is in contrast to the classic Zipf-like popularity of objects for a given user. Also, our analysis reveals that transfer lengths are highly variable and that this variability is due to the stickiness of clients to a particular live object, as opposed to structural (size) properties of objects. Second, by contrasting two live streaming workloads from two radically different applications, we conjecture that some characteristics of live media access workloads are likely to be highly dependent on the nature of the live content being accessed. In our study, this dependence is clear from the strong temporal correlations observed in the traces, which we attribute to the synchronizing impact of live content on access characteristics. Based on our analyses, we present a model for live media workload generation that incorporates many of our findings, and which we implement in Gismo [19].


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  21

Collaborative Colleagues:
Eveline Veloso: colleagues
Virgílio Almeida: colleagues
Wagner Meira: colleagues
Azer Bestavros: colleagues
Shudong Jin: colleagues