SYED Mohammad Imran

PhD student at Sorbonne University
Team : NPA
https://www.linkedin.com/in/mohammad-imran-syed-252a0558/

Supervision : Anne FLADENMULLER

Co-supervision : DIAS DE AMORIM Marcelo

Wireless passive measurements: tool, redundancy, measurements, and analyses

Understanding wireless traffic is fundamental for improving networks and designing advanced algorithms and protocols. In this context, passive measurements have the edge over active measurements, as there is no requirement for any modification in existing network devices. Passive measurements are often less expensive and easier to deploy than other methods. This approach involves monitoring the wireless medium and collecting data on various network parameters, such as signal strength, channel occupancy, and packet loss. It consists of deploying multiple sniffers throughout the target area (sniffers are devices operating in monitor mode that collect the wireless packets regardless of their nature). However, one of the main challenges with passive measurements is ensuring trace completeness, or the ability to collect a complete and accurate dataset. We know that a single sniffer cannot capture all the traffic due to the inherent characteristics of the wireless medium where the environment can be highly dynamic and unpredictable.
Several factors can impact trace completeness in wireless passive measurements. These include environmental factors, such as interference from other wireless devices, changes in the physical environment (such as moving objects), and variations in wireless signal propagation due to changes in atmospheric conditions. Additionally, issues with the measurement equipment itself, such as calibration errors or data processing issues, can also impact trace completeness.
The importance of trace completeness in wireless passive measurements cannot be overstated. Inaccurate or incomplete data can lead to incorrect conclusions about network performance, which can have significant implications for network planning, optimization, and troubleshooting. For example, incomplete data can result in missed opportunities to identify and address network issues, and incorrect or incomplete trajectory reconstruction.
In this thesis, we study the quality of traces captured by a sniffer and investigate the resulting improvements by introducing redundancy in the number of sniffers. We explore the impact of the following two aspects on the quality of wireless traces: the number of sniffing devices and the type of hardware used. We study the variation in the Received Signal Strength Indicator (RSSI) and its impact on distance estimation. The analysis is helped by the development of a readily-usable and easily-available tool, called PyPal, for the synchronization and merging of Wi-Fi traces collected simultaneously.

Defence : 09/05/2023

Jury members :

Luís Henrique MACIEL KOSMALSKI COSTA, Professeur des universités, Universidade Federal do Rio de Janeiro [Rapporteur]
Thi-Mai-Trang NGUYEN, Professeur des universités, Université Sorbonne Paris Nord [Rapporteur]
Lila BOUKHATEM, Maître de conférences, Université Paris-Saclay
Olivier FOURMAUX, Professeur des universités, Sorbonne Université
Emmanuel LOCHIN, Professeur des universités, École Nationale de l’Aviation Civile
Marcelo DIAS DE AMORIM, Directeur recherche, CNRS
Anne FLADENMULLER, Professeur des universités, Sorbonne Université
Lila BOUKHATEM, Maître de conférences, Université Paris-Saclay

Departure date : 09/30/2023

2022-2024 Publications