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Distributed Medium Access for Camera Sensor Networks: Theory and Practice

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Theory and Applications of Smart Cameras

Part of the book series: KAIST Research Series ((KAISTRS))

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Abstract

Camera sensor networks (CSN) have recently emerged as an important class of sensor networks, where each node is equipped with a camera and has a capability of visually detecting events in its neighborhood. The applications of CSN are highly diverse, including surveillance, environmental monitoring, smart homes, and telepresence systems. In this article, we focus on one of the key unique characteristics of CSN: An event detected by a sensor node can trigger a large amount of sensing data generation, which should be delivered in a distributed manner, whereas in “traditional” sensor networks the volume of sensing data is typically small. Networking protocols to convey the captured image from sensors to decision making modules consist of from distributed and energy-efficient layers accessed via a high-throughput and low-delay MAC to fancy routing and transport protocols. In this article, we focus on the MAC layer and survey the theory and the practical implementation efforts of CSMA-based MAC mechanisms, referred to as optimal CSMA, that are fully distributed with the goal of guaranteeing throughput and delay.

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Notes

  1. 1.

    Let \( [x_{i} :i \in {\mathscr{L}}] \) denote the vector whose ith element is \( x_{i} . \) For notational convenience, instead of \( [x_{i} :i \in {\mathscr{L}}] \), we use \( [x_{i} ] \) in the remainder of this paper.

  2. 2.

    We use j to index the state updates, and \( T(j) \) is the time of j-th update.

  3. 3.

    Note that the notations on the network model in this Sect. 4.1 slightly differ from those in other sections, e.g., in Sects. 2.1 and 4.2. For example, in Sects. 2.1 and 4.2, we use \( {\mathscr{L}} \) to refer to the set of nodes in the interference graph G, and \( {\mathscr{V}} \) was not used there.

  4. 4.

    The results can be readily extended to the case where the interference matrix may be different on different channels. In such case, interference would be modelled by \( A \in \{ 0,1\}^{L \times L \times C} \) where \( A_{klc} = 1 \) iff link k and l interfere each other on channel c.

  5. 5.

    We say \( t \equiv k \) (mod T) if t − k is an integer multiple of T. It is called congruent modulo.

  6. 6.

    This per-link optimality is much stronger than the ‘network-wide’ optimality defined by the averaged delay over all links.

  7. 7.

    CW sizes are one of values in \( \{ 2^{i + 1} - 1:i = 0, \ldots ,9\} \).

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Acknowledgments

This work is supported by the Center for Integrated Smart Sensors funded by the Ministry of Science, ICT and Future Planning as the Global Frontier Project.

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Authors and Affiliations

  1. Electrical Engineering, KAIST, Daejeon, South Korea

    Hojin Lee, Donggyu Yun & Yung Yi

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  1. Hojin Lee
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  2. Donggyu Yun
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  3. Yung Yi
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Correspondence to Hojin Lee .

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Editors and Affiliations

  1. Electrical Engineering Center for Integrated Smart Sensors, KAIST, Daejoen, Korea, Republic of (South Korea)

    Chong-Min Kyung

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Lee, H., Yun, D., Yi, Y. (2016). Distributed Medium Access for Camera Sensor Networks: Theory and Practice. In: Kyung, CM. (eds) Theory and Applications of Smart Cameras. KAIST Research Series. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9987-4_14

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  • DOI: https://doi.org/10.1007/978-94-017-9987-4_14

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