MobiCon: Next Generation Mobile and Ubiquitous Platforms A Mobile Context Monitoring Platform for Sensor-rich Dynamic Environments

The research driven technology presents MobiCon, a middleware platform for developing human activity applications in an energy efficient manner. Such application infer the user's patterns of activity by processing measurements streams collected by sensors placed on or around the user's body which are connected by a personal area network (PAN). The main insight behind MobiCon is that instead of sensing all the sensors all the time, the system determines the sensors that are required by the union of applications that are currently active. MobiCon supports writing human activity applications in the form of predicates (e.g. "location == 'library') connected by logic operators that are supposed to run for a specified duration of time. MobiCon decomposes these high-level programs into a set of requests to acquire sensor streams whose 'values' are periodically re-evaluated. MobiCon is an initial attempt to provide an active resource orchestration system, recognizing the PAN-scale sensor-rich mobile platform as a common underlying computing platform. Recently, many systems have been proposed for effective resource management of mobile devices [3][4][5][6][7] and sensors [8][9][10] comprising PAN. They are mostly designed to manage resources, especially battery in most cases, for applications on a single computing device. Such device-centric resource management, however, can hardly be utilized in our target environment, in which multiple sensors and a mobile device cooperatively serve multiple applications.

[1]  Amin Vahdat,et al.  ECOSystem: managing energy as a first class operating system resource , 2002, ASPLOS X.

[2]  Umar Saif,et al.  Structured decomposition of adaptive applications , 2008, Pervasive Mob. Comput..

[3]  Prashant J. Shenoy,et al.  Chameleon: Application-Level Power Management , 2008, IEEE Transactions on Mobile Computing.

[4]  Jani Mäntyjärvi,et al.  Managing Context Information in Mobile Devices , 2003, IEEE Pervasive Comput..

[5]  Mahadev Satyanarayanan,et al.  Predictive Resource Management for Wearable Computing , 2003, MobiSys '03.

[6]  Mahadev Satyanarayanan,et al.  Agile application-aware adaptation for mobility , 1997, SOSP.

[7]  J. Flinn,et al.  Energy-aware adaptation for mobile applications , 1999, SOSP.

[8]  Jason Williams,et al.  Emotion Recognition Using Bio-sensors: First Steps towards an Automatic System , 2004, ADS.

[9]  Pedro José Marrón,et al.  Meeting lifetime goals with energy levels , 2007, SenSys '07.

[10]  Emiliano Miluzzo,et al.  The BikeNet mobile sensing system for cyclist experience mapping , 2007, SenSys '07.

[11]  Shuichi Fukuda,et al.  Emotion in user interface, voice interaction system , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[12]  Daniel P. Siewiorek,et al.  Activity recognition and monitoring using multiple sensors on different body positions , 2006, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06).

[13]  Umar Saif,et al.  A dynamic platform for runtime adaptation , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[14]  Gregor Schiele,et al.  PCOM - a component system for pervasive computing , 2004, Second IEEE Annual Conference on Pervasive Computing and Communications, 2004. Proceedings of the.

[15]  Matt Welsh,et al.  Resource aware programming in the Pixie OS , 2008, SenSys '08.

[16]  Mirco Musolesi,et al.  Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application , 2008, SenSys '08.

[17]  Youngki Lee,et al.  SeeMon: scalable and energy-efficient context monitoring framework for sensor-rich mobile environments , 2008, MobiSys '08.

[18]  Mark D. Corner,et al.  Eon: a language and runtime system for perpetual systems , 2007, SenSys '07.

[19]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[20]  Gregor Schiele,et al.  BASE - a micro-broker-based middleware for pervasive computing , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..