A Scalable and Energy-Efficient Context Monitoring Framework for Mobile Personal Sensor Networks

The key feature of many emerging pervasive computing applications is to proactively provide services to mobile individuals. One major challenge in providing users with proactive services lies in continuously monitoring users' context based on numerous sensors in their PAN/BAN environments. The context monitoring in such environments imposes heavy workloads on mobile devices and sensor nodes with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the mobile device can proactively understand users' contexts and react appropriately. This paper proposes a novel context monitoring approach that provides efficient processing and sensor control mechanisms. We implement and test a prototype system on two mobile devices: a UMPC and a wearable device with a diverse set of sensors. Example applications are also developed based on the implemented system. Experimental results show that SeeMon achieves a high level of scalability and energy efficiency.

1 Introduction

Proactively providing services to mobile users is essential for many emerging pervasive computing applications. Provision of situation-specific services without user intervention requires an involved process for acquiring users' contexts. Such services require different types of contexts with different degrees of context awareness. Individual users have different service requirements and preferences, personalized to their own needs. Increasingly, a number of wearable and wireless sensors with diverse capabilities are being densely deployed on users' bodies or in their personal areas. To provide much broader coverage and higher accuracy in recognized contexts, personal sensor networks will grow much in scale, diversity, and complexity. In such environments, the mobile device plays a key role as a full-fledged, integrated personal service agent, incorporating personal sensor networks and running multiple applications simultaneously. An effective personal mobile system must continuously process a large volume of sensor data while supporting a number of applications.