Landing on the mobile web: From browsing to long-term modeling

Troy Johnson, Patrick Seeling

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Browsing the web has become a common task performed using personal mobile devices, resulting in significant access network and battery limitation challenges. Efforts to alleviate these challenges are commonly based around approaches incorporating elements of on-device and network optimizations. Energy-efficient mobile web content delivery has, in turn, attracted a significant body of research and practical developments. However, the efforts put forth today might not result in long-term applicable results should the underlying characteristics of the mobile content change drastically over time. As caching frequently used data locally is a common initial approach employed to limit network traffic and energy expenditures while on the go, we evaluate the long-term suitability of approximating a basic set of parameters for a cache and request behavior model using a popular large data set. We present a convenient approach that can employ a general approximation of parameters over time. Our long-term modeling of the underlying factors results in an acceptable level of peak inaccuracies in simulations for more than a year's time horizon. In turn, practitioners and researchers are enabled to readily employ modeling and simulation approaches over a significant period of time with only slight impacts on their approaches and results.

Original languageEnglish
Article number7402274
Pages (from-to)146-151
Number of pages6
JournalIEEE Communications Magazine
Issue number2
StatePublished - Feb 2016


  • Data models
  • Market research
  • Mobile communication
  • Mobile computing
  • Mobile handsets
  • Performance evaluation
  • Web pages


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