Unsatisfied today, satisfied tomorrow: A simulation framework for performance evaluation of crowdsourcing-based network monitoring
نویسندگان
چکیده
Network operators need to continuously upgrade their infrastructures in order keep customer satisfaction levels high. Crowdsourcing-based approaches are generally adopted, where customers directly asked answer surveys about experience. Since the number of collaborative users is low, network rely on Machine Learning models predict levels/QoE rather than measuring it through surveys. Finally, combining true/predicted labels with information each user mobility (e.g, which sites has visited and for how long), an operator may reveal critical areas drive/prioritize investments properly. In this work, we propose empirical framework tailored assess quality detection under-performing cells starting from subjective experience grades. The allows simulate diverse networking scenarios, a characterized by small set heterogeneous moving according realistic models. simulates both processes delivery prediction, considering different strategies evaluating prediction algorithms performance. We use simulation test empirically performance general scenarios density obtain insights generalizable that provide interesting guidelines operators.
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ژورنال
عنوان ژورنال: Computer Communications
سال: 2022
ISSN: ['1873-703X', '0140-3664']
DOI: https://doi.org/10.1016/j.comcom.2021.11.004