MOBILE SENSING: Retrospectives and Trends

It is difficult to think back to a time before smartphones existed, with their ubiquitous computing and communication capabilities, and with detailed location sensing easily available from Global Positioning Systems (GPS). In the late 1990s, when my research group began work on mobile sensing, smartphones had not yet been invented. While GPS did exist, GPS receivers were expensive, power-hungry and not widely available. Our first mobile computing project started as a powerefficiency study for a GPS-based interactive campus tour. GPS-based tour applications are familiar now, but were unheard of then, and the physical implementation was a challenge. We used a Palm Pilot PDA (personal digital assistant) connected to an external GPS receiver and an external Wi-Fi card. In those days, PDAs had neither GPS nor any wireless communication capability! Given the bulkiness of the various pieces of our "app," we carried them and their batteries around in a shoebox. Since both the GPS and the radio were quite high power (over 1W), they greatly impacted the system's battery life. Our power-efficiency work explored methods to locally cache maps on the PDA, and to power down modules when not in use.

[1]  Margaret Martonosi,et al.  Data compression algorithms for energy-constrained devices in delay tolerant networks , 2006, SenSys '06.

[2]  Margaret Martonosi,et al.  Location-based trust for mobile user-generated content: applications, challenges and implementations , 2008, HotMobile '08.

[3]  Margaret Martonosi,et al.  Energy adaptation techniques to optimize data delivery in store-and-forward sensor networks , 2006, SenSys '06.

[4]  Margaret Martonosi,et al.  Low-infrastructure methods to improve internet access for mobile users in emerging regions , 2011, WWW.

[5]  Margaret Martonosi,et al.  Identifying Important Places in People's Lives from Cellular Network Data , 2011, Pervasive.

[6]  Margaret Martonosi,et al.  Human mobility modeling at metropolitan scales , 2012, MobiSys '12.

[7]  Vijay Janapa Reddi,et al.  Mobile CPU's rise to power: Quantifying the impact of generational mobile CPU design trends on performance, energy, and user satisfaction , 2016, 2016 IEEE International Symposium on High Performance Computer Architecture (HPCA).

[8]  Margaret Martonosi,et al.  Potential for collaborative caching and prefetching in largely-disconnected villages , 2008, WiNS-DR '08.

[9]  Margaret Martonosi,et al.  DP-WHERE: Differentially private modeling of human mobility , 2013, 2013 IEEE International Conference on Big Data.

[10]  Margaret Martonosi,et al.  LOCALE: Collaborative Localization Estimation for Sparse Mobile Sensor Networks , 2008, 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008).

[11]  Margaret Martonosi,et al.  SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory , 2011, MobiSys '11.

[12]  Margaret Martonosi,et al.  Implementing software on resource-constrained mobile sensors: experiences with Impala and ZebraNet , 2004, MobiSys '04.

[13]  Margaret Martonosi,et al.  ON CELLULAR , 2022 .

[14]  Margaret Martonosi,et al.  Ranges of human mobility in Los Angeles and New York , 2011, 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).