June 03, 2018

Minimizing the impact of prediction errors during anticipatory resource allocation

  • Malanchini I.
  • Suryaprakash V.

By predicting changes in service requirements and future evolution of network states, anticipatory networking aims at improving the performance of decision making and optimization algorithms. In this paper, we propose a reliability-aware scheduling model which exploits information of upcoming users' channel states to proactively optimize the resource allocation. Along with the optimal formulation, proved to be NP-hard, a heuristic is also presented. The evaluation of the proposed optimization model and corresponding heuristic is carried out assuming both a perfect prediction and an error-prone prediction of the achievable users' channel states and show that both are robust to errors.

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© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Many of today's websites have recognised the importance of mobile friendly pages to keep users engaged and to provide a satisfying user experience. However, next to the experience provided by the sites themselves, ...

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  • Djuric N.
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© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Uber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist ...

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© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time, we extensively study this novel ...