Some aspects of physical prototyping in Pervasive Computing

TL;DR

This paper reviews research on physical sensors in Pervasive Computing, focusing on RF channels and ambient audio, exploring adaptive beamforming, environmental sensing, and security applications, with emphasis on algorithmic efficiency and environmental sensitivity.

Contribution

It introduces a simple distributed optimization method for phase alignment in sensor networks and highlights the potential of physical layer signals for environmental sensing and security in Pervasive Computing.

Findings

Derived asymptotic bounds on optimization time.

Demonstrated environmental sensitivity of RF signals.

Explored security applications of physical layer signals.

Abstract

This document summarises the results of several research campaigns over the past seven years. The main connecting theme is the physical layer of widely deployed sensors in Pervasive Computing domains. In particular, we have focused on the RF-channel or on ambient audio. The initial problem from which we started this work was that of distributed adaptive transmit beamforming. We have been looking for a simple method to align the phases of jointly transmitting nodes (e.g. sensor or IoT nodes). The algorithmic solution to this problem was to implement a distributed random optimisation method on the participating nodes in which the transmitters and the receiver follow an iterative question-and-answer scheme. We have been able to derive sharp asymptotic bounds on the expected optimisation time of an evolutionary random optimiser and presented an asymptotically optimal approach. One thing that we have learned from the work on these physical layer algorithms was that the signals we work on are fragile and perceptive to physical environmental changes. These could be obstacles such as furniture, opened or closed windows or doors as well as movement of individuals. This observation motivated us to view the wireless interface as a sensor for environmental changes in Pervasive Computing environments. Another use of physical layer RF-signals is for security applications. We are currently working to further push these mentioned directions and novel fields of physical prototyping. In particular, the calculation of mathematical operations on the wireless channel at the time of transmission appears to contain good potential for gains in efficiency for communication and computation in Pervasive Computing domains.