Information Aggregation for Collaborative Sensing in Mobile Cloud Computing

• Published in: 2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering pp. 149 - 158
• Main Authors: Loomba, Radhika, Lei Shi, Jennings, Brendan, Friedman, Roy, Kennedy, John, Butler, Joe
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-04-2014
• Subjects: Algorithm design and analysis; Batteries; frequent pattern mining; info aggregation; mobile application; mobile cloud; Mobile handsets; Mobile nodes; mobile sensing; optimization; Sensors
• DOI: 10.1109/MobileCloud.2014.23

The proliferation of smart mobile devices, having multiple sensing capabilities and significant computing power, enables their inclusion into mobile sensing systems. Sensor-driven mobile applications are drastically altering various sectors like healthcare, social networks and environmental monitoring. However, using a large number of mobile devices has an impact on the viability of techniques involved in sensing systems. Moreover, continuous sensing affects the battery performance of the mobile device. This motivates a need for energy efficient sensor-data collection with a minimum number of mobile devices. This paper presents an algorithm that makes a trade-off between the energy consumption and the number of involved mobile devices in the sensing environment, subject to satisfying the sensing needs of multiple applications. We compare our algorithm with an energy-efficient solution for sensor allocation. Results show that our algorithm suffers from less than 6% battery loss difference while reducing the number of involved mobile devices by more than 30%.