A Mobile Crowdsensing Ecosystem Enabled by a Cloud-Based Publish/Subscribe Middleware
Authors:
- Aleksandar AntonicAAAleksandar Antonic
- Kristijan RoankovicKRKristijan Roankovic
- Martina MarjanovicMMMartina Marjanovic
- Kreimir PripuicKPKreimir Pripuic
- Ivana Podnar ArkoIAIvana Podnar Arko
- 1 August 2014
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 107-114
Abstract
We are witnessing the rise of a novel class of wearable devices equipped with various sensing capabilities as well as further miniaturization of sensing components that are nowadays being integrated into mobile devices. The inherent mobility of such devices has the capacity to produce dense and rich spatiotemporal information about our environment creating the mobile Internet of Things (IoT). The management of mobile resources to enable sensor discovery and seamless integration of mobile geotagged sensor data with cloud-based IoT platforms creates new challenges due to device dynamicity, energy constraints, and varying sensor data quality. The paper presents an ecosystem for mobile crowdsensing applications which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a context-aware and energy-efficient manner. The ecosystem offers the means for location management of mobile Internet-connected objects and adaptive data acquisition from such devices. In addition, our solution enables filtering of sensor data on mobile devices in the proximity of a data producer prior to its transmission into the cloud. Thus it reduces both the network traffic and energy consumption on mobile devices. We evaluate the performance of our mobile CUPUS application to investigate its performance on mobile phones in terms of scalability and CPU, memory and energy consumption under high publishing load.Keywords
This publication has 11 references indexed in Scilit:
- Publish/subscribe middleware for energy-efficient mobile crowdsensing2013
- If you see something, swipe towards it2013
- Big data: A review2013
- ShareLikesCrowd: Mobile analytics for participatory sensing and crowd-sourcing applications2013
- MobiSens: A Versatile Mobile Sensing Platform for Real-World ApplicationsMobile Networks and Applications, 2012
- Capturing sensor data from mobile phones using Global Sensor Network middleware2012
- Citisense: Mobile Air Quality Sensing for Individuals and Communities. Design and deployment of the Citisense mobile air-quality system.2012
- Mobile crowdsensing: current state and future challengesIEEE Communications Magazine, 2011
- Accurate online power estimation and automatic battery behavior based power model generation for smartphones2010
- Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing2005