PitchD 2022 edition: the 1st PitchD [ONLINE]

26 January 2022 – 5.30 PM

YouTube Live Broadcast

The event has not started yet. Come back on the day of the event to watch the event.

Here’s the 1st PitchD – the PhD’s pitch. Our PhD IEEE Student Members explain to students, colleagues and professors their research.

Development of low-power and low-cost electronic systems for Smart Agriculture

Mr. Stefano Calvo
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino
Climate change is probably the biggest challenge humanity has ever faced. As it is widely known, factors causing it have mainly anthropic origins. Among these factors, one of the most impactful is agricultural activity. It is responsible for about 30% of greenhouse gases emission and 70% of freshwater withdrawals. Agricultural’s environmental impact is destined to increase in the following decades since the world population is expected to grow dramatically. Therefore, producing enough food for the entire population while reducing production footprint will be a crucial goal that must be achieved. Smart agriculture aims at merging together both engineering and farming knowledges to increase harvests and, at the same time, reducing their impact.

Efficient TCAD Large-Signal temperature-dependent variability analysis of a FinFET power amplifier

Ms. Eva Catoggio
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino
Physics-based device simulations represent an ideal environment to accurately model the behaviour of active devices in RF/microwave circuits, as they keep trace of technological and physical parameters. The frequency domain analysis of electron devices in highly nonlinear conditions has proved to be a fairly manageable task in TCAD simulators, especially using the Harmonic Balance technique for mixed-mode simulations. To be successfully used for circuit analysis, physics-based models must be able to predict the sensitivity of a nonlinear stage towards the variations of: temperature, physical/technological parameters and the embedding circuit. In this talk, the problem of temperature variations, especially relevant in the scenario of power devices (e.g. GaAs or GaN based HEMTs) and nanoscale devices (e.g. FinFETs), is addressed. In particular, an efficient approach to the temperature-dependent physics-based variability analysis of a FinFET-based power amplifier in Large Signal (LS) nonlinear conditions is presented. The method extends, with negligible numerical overhead, the Green’s Function approach and allows to calculate the LS device response to the temperature variation from a nominal”cold” condition with concurrent variations of the external load or technological parameters.

α-Mon: Traffic Anonymizer for Passive Monitoring

Mr. Thomas Favale
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino
Packet measurements at scale are essential for several applications, such as cyber-security, accounting and troubleshooting. They, however, threaten users’ privacy by exposing sensitive information. Anonymization has been the answer to this challenge, however, it comes with some challenges and drawbacks. First, it reduces the value of data. Second, it requires to consider diverse protocols because information may leak from non-encrypted fields. Third, it must be performed at high speeds directly at the monitor, to prevent data leakage. We present α-Mon, a flexible tool for privacy-preserving packet monitoring. It replicates input packet streams to different consumers while anonymizing according to flexible policies covering all protocol layers. α-Mon supports α-anonymization, a novel solution to obfuscate rare values: it works on a streaming fashion, with zero delay, operating at high-speed links on a packet-by-packet basis. We quantify the impact of α-anonymization on traffic measurements, finding that it introduces minimal error when it comes to finding heavy-hitter services. We evaluate α-Mon performance using packet traces collected from an ISP network on a Commercial Off-the Shelf server.

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