Probability of Task Completion and Energy Consumption in Cooperative Pervasive Mobile Computing

It is challenging for multiple smartphones to complete a given task in large-scale pervasive sensing systems cooperatively. Sensing paradigms such as opportunistic sensing, participatory sensing, and hybrid sensing have been used for smartphones to work together seamlessly under different contexts. However, these existing paradigms do not incorporate the energy problem and sharing sensory resources of applications. In this paper, we revisit sensing paradigms regarding the probability of task completion and energy consumption for smartphones to cooperatively complete a sensing task. In addition, we propose a symbiotic sensing paradigm that can significantly save smartphone batteries while maintaining equivalent performance to existing paradigms, provided that the smartphones allow applications to share sensing resources. We also quantitatively evaluate our probabilistic models with a realistic case study. This work is a useful aid to designing and evaluating large-scale smartphone-based sensing systems before deployment, which saves money and effort