BearLoc: A Composable Distributed Framework for Indoor Localization Systems

Many indoor localization algorithms have been proposed to enable location-based applications in indoor environments. However, these systems are monolithic and not component-based. We present BearLoc, a distributed modular framework for indoor localization systems that provides (1) natural development abstractions for sensor, algorithm, and application components, and (2) easy and flexible component composition. We demonstrate the merits of BearLoc with an example use case. Our evaluation shows we can reduce developer lines of code by 60% while introducing acceptable network delay overhead.

[1]  Hyeonwoo Kim,et al.  Correlation analysis of MQTT loss and delay according to QoS level , 2013, The International Conference on Information Networking 2013 (ICOIN).

[2]  Jie Liu,et al.  Design and evaluation of a wireless magnetic-based proximity detection platform for indoor applications , 2012, 2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN).

[3]  Peter A. Dinda,et al.  Indoor localization without infrastructure using the acoustic background spectrum , 2011, MobiSys '11.

[4]  J. Krumm,et al.  Multi-camera multi-person tracking for EasyLiving , 2000, Proceedings Third IEEE International Workshop on Visual Surveillance.

[5]  Philipp Bolliger,et al.  Redpin - adaptive, zero-configuration indoor localization through user collaboration , 2008, MELT '08.

[6]  Moustafa Youssef,et al.  No need to war-drive: unsupervised indoor localization , 2012, MobiSys '12.

[7]  Xin Pan,et al.  ARIEL: automatic wi-fi based room fingerprinting for indoor localization , 2012, UbiComp.

[8]  Guobin Shen,et al.  Walkie-Markie: Indoor Pathway Mapping Made Easy , 2013, NSDI.

[9]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[10]  Hae Young Noh,et al.  Indoor Person Identification through Footstep Induced Structural Vibration , 2015, HotMobile.

[11]  Anne-Marie Kermarrec,et al.  The many faces of publish/subscribe , 2003, CSUR.