VeSense: High-Performance and Energy-Efficient Vehicular Sensing Platform

Although vehicular sensing where mobile users in vehicles continuously gather, process, and share location-sensitive and context-sensitive sensor data (e.g., street images, road condition and traffic flow) is emerging, little effort has been investigated in a model-based energy-efficient network paradigm of sensor information sharing in vehicular environments. Upon these optimization frameworks, a suite of optimization sub-problems: a program partitioning and network resource allocation problem, the authors propose a distributed vehicular sensing platform, called VeSense where mobile users in vehicles publish/access sensor data via a cloud computing-based distributed P2P overlay network.

Provided by: Elsevier Topic: Cloud Date Added: May 2013 Format: PDF

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