DocumentCode :
651931
Title :
Enabling Real-Time In-Situ Processing of Ubiquitous Mobile-Application Workflows
Author :
Viswanathan, Harish ; Eun Kyung Lee ; Pompili, Dario
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers Univ., New Brunswick, NJ, USA
fYear :
2013
fDate :
14-16 Oct. 2013
Firstpage :
324
Lastpage :
332
Abstract :
The heterogeneous sensing and computing capabilities of sensor nodes, mobile handhelds, as well as computing and storage servers in remote data centers can be harnessed to enable innovative mobile applications that rely on real-time in-situ processing of data generated in the field. There is, however, uncertainty associated with the quality and quantity of data from mobile sensors as well as with the availability and capabilities of mobile computing resources on the field. Data and computing-resource uncertainty, if unchecked, may propagate up the "raw-data→information→knowledge" chain and have an adverse effect on the relevance of the generated results. A unified uncertainty-aware framework for data and computing-resource management is proposed to enable in-situ processing of application workflows on mobile sensing and computing platforms and, hence, to generate actionable knowledge from raw data within realistic time bounds. A two-phase solution that captures the propagation of data-uncertainty up the data-processing chain using interval arithmetic in the first phase and that employs multi-objective optimization for task allocation in the second phase is presented and evaluated in detail.
Keywords :
data integrity; mobile computing; optimisation; computing resource uncertainty; data processing chain; data uncertainty propagation; heterogeneous sensing; in-situ processing; interval arithmetic; mobile computing resource; mobile sensor; multiobjective optimization; raw data; real time processing; realistic time bound; remote data center; storage server; task allocation; ubiquitous mobile application workflow; unified uncertainty aware framework; Batteries; Computational modeling; Data models; Mobile communication; Resource management; Sensors; Uncertainty; autonomic management; mobile grids; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mobile Ad-Hoc and Sensor Systems (MASS), 2013 IEEE 10th International Conference on
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/MASS.2013.86
Filename :
6680257
Link To Document :
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