Kindt, Philipp; Naranayaswamy, Swaminathan; Saur, Marco; Chakraborty, Samarjit
Optimizing BLE-like Neighbor Discovery
IEEE Transactions on Mobile Computing
2020
to appear

Shamsa, E.;Kanduri, A.;TaheriNejad, N.;Pröbstl, A.;Chakraborty, S.;Rahmani, A. M.;Liljeberg, P.
User-centric Resource Management for Embedded Multi-core Processors
2020 33rd International Conference on VLSI Design and 2020 19th International Conference on Embedded Systems (VLSID)
2020

Pröbstl, A.;Islam, B.;Nirjon, S.;Chang, N.;Chakraborty, S.
Intelligent Chargers Will Make Mobile Devices Live Longer
IEEE Design Test
2020
1-1

Christian Gentner, Daniel Günther, Philipp H. Kindt
Identifying the BLE Advertising Channel for Reliable Distance Estimation on Smartphones
As a response to the global COVID-19 surge in 2020, many countries have implemented lockdown or stay-at-home policies. If, however, the contact persons of every infected patient could be identified, the number of virus transmissions could be reduced, while the more incisive measures could be softened. For this purpose, contact tracing using smartphones is being considered as a promising technique. Here, smartphones emit and scan for Bluetooth Low Energy (BLE) signals for detecting devices in range. When a device is detected, its distance is estimated by evaluating its received signal strength. The main insight that is exploited for distance estimation is that the attenuation of a signal increases with the distance along which it has traveled. However, besides distance, there are multiple additional factors that impact the attenuation and hence disturb distance estimation. Among them, frequency selective hardware and signal propagation belong to the most significant ones. For example, a BLE device transmits beacons on three different frequencies (channels), while the transmit power and the receiver sensitivity depend on the frequency. As a result, the received signal strength varies for each channel, even when the distance remains constant. However, the information on which wireless channel a beacon has been received is not made available to a smartphone. Hence, this error cannot be compensated, e.g., by calibration. In this paper, we for the first time provide a solution to detect the wireless channel on which a packet has been received on a smartphone. We experimentally evaluate our proposed technique on multiple different smartphone models. Our results help to make contact tracing more robust by improving the accuracy of distance estimation.
2020

Heitmann, Nadja;Pirker, Benedikt;Park, Sangyoung;Chakraborty, Samarjit
Towards Building Better Mobile Web Browsers for Ad Blocking: The Energy Perspective (WiP Paper)
ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES ’20)
2020

Kindt, Philipp H.;Ghosh, Sumana;Chakraborty, Samarjit
Configuring loosely time-triggered wireless control software
Proceedings of the 23th International Workshop on Software and Compilers for Embedded Systems
ACM
2020

Kindt,Philipp H.; Chakraborty,Trinad;Chakraborty,Samarjit
How Reliable is Smartphone-based Electronic Contact Tracing for COVID-19?
tba
2020

Kindt,Philipp H.;Yunge, Daniel;Diemer, Robert;Chakraborty,Samarjit
Energy Modeling for the Bluetooth Low Energy Protocol
ACM Transactions on Embedded Computing Systems (TECS)
2020

Geier, Martin and Chakraborty, Samarjit
Challenges in IT Operations Management at a German University Chair – Ten Years in Retrospect
2019 ACM SIGUCCS Annual Conference on - SIGUCCS '19
ACM Press
2019

Geier, Martin and Faller, Dominik and Brandle, Marian and Chakraborty, Samarjit
Cost-Effective Energy Monitoring of a Zynq-Based Real-Time System Including Dual Gigabit Ethernet
2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)
IEEE
2019