A characterization of broadband user behavior and their e-business activities

  • Authors:

  • Humberto T. Marques Neto;Jussara M. Almeida;Leonardo C. D. Rocha;Wagner Meira;Pedro H. C. Guerra;Virgilio A. F. Almeida

  • Affiliations:

  • Federal University of Minas Gerais, Brazil;Federal University of Minas Gerais, Brazil;Federal University of Minas Gerais, Brazil;Federal University of Minas Gerais, Brazil;Federal University of Minas Gerais, Brazil;Federal University of Minas Gerais, Brazil

  • Venue:
  • ACM SIGMETRICS Performance Evaluation Review
  • Year:
  • 2004

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Abstract

This paper presents a characterization of broadband user behavior from an Internet Service Provider standpoint. Users are broken into two major categories: residential and Small-Office/Home-Office (SOHO). For each user category, the characterization is performed along four criteria: (i) session arrival process, (ii) session duration, (iii) number of bytes transferred within a session and (iv) user request patterns.Our results show that both residential and SOHO session inter-arrival times are exponentially distributed. Whereas residential session arrival rates remain relatively high during the day, SOHO session arrival rates vary much more significantly during the day. On the other hand, a typical SOHO user session is longer and transfers a larger volume of data. Furthermore, our analysis uncovers two main groups of session request patterns within each user category. The first group consists of user sessions that use traditional Internet services, such as e-mail, instant messenger and, mostly, www services. On the other hand, sessions from the second group, a smaller group, use typically peer-to-peer file sharing applications, remain active for longer periods and transfer a large amount of data. Looking further into the e-business services most commonly accessed, we found that subscription-based and advertising services account for the vast majority of user HTTP requests in both residential and SOHO workloads. Understanding these user behavior patterns is important to the development of more efficient applications for broadband users.