Monthly Archives: July 2016

Energy consumption models for smart-camera networks

Energy consumption models for smart-camera networks

  • Juan C. SanMiguel and Andrea Cavallaro. Energy consumption models for smart-camera networks. IEEE Transactions on Circuits and Systems for Video Technology, 99:1-14, 2016. doi:10.1109/TCSVT.2016.2593598
    [BibTeX] [Abstract]

    Camera networks require heavy visual-data processing and high-bandwidth communication. In this paper, we identify key factors underpinning the development of resourceaware algorithms and we propose a comprehensive energy consumption model for the resources employed by smart-camera networks, which are composed of cameras that process data locally and collaborate with their neighbours. We account for the main parameters that influence consumption when sensing (framesize and framerate), processing (dynamic frequency scaling and task load) and communication (output power and bandwidth) are considered. Next we define an abstraction based on clock frequency and duty cycle that accounts for active, idle and sleep operational states. We demonstrate the importance of the proposed model for a multi-camera tracking task and show how one may significantly reduce consumption with only minor performance degradation when choosing to operate with an appropriately reduced hardware capacity. Moreover, we quantify the dependency on local computation resources and on bandwidth availability. The proposed consumption model can be easily adjusted to account for new platforms, thus providing a valuable tool for the design of resource-aware algorithms and further research in resource-aware camera networks.

    @Article{2016-07-SANMIGUEL,
    author = {Juan C. SanMiguel and Andrea Cavallaro},
    journal = {{IEEE Transactions on Circuits and Systems for Video Technology}},
    title = {{Energy consumption models for smart-camera networks}},
    date = {2016-07-20},
    year = {2016},
    volume = {99},
    pages = {1-14},
    doi = {10.1109/TCSVT.2016.2593598},
    abstract = {Camera networks require heavy visual-data processing and high-bandwidth communication. In this paper, we identify key factors underpinning the development of resourceaware algorithms and we propose a comprehensive energy consumption model for the resources employed by smart-camera networks, which are composed of cameras that process data locally and collaborate with their neighbours. We account for the main parameters that influence consumption when sensing (framesize and framerate), processing (dynamic frequency scaling and task load) and communication (output power and bandwidth) are considered. Next we define an abstraction based on clock frequency and duty cycle that accounts for active, idle and sleep operational states. We demonstrate the importance of the proposed model for a multi-camera tracking task and show how one may significantly reduce consumption with only minor performance degradation when choosing to operate with an appropriately reduced hardware capacity. Moreover, we quantify the dependency on local computation resources and on bandwidth availability. The proposed consumption model can be easily adjusted to account for new platforms, thus providing a valuable tool for the design of resource-aware algorithms and further research in resource-aware camera networks.}
    }

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