Predictive duty cycle adaptation for wireless camera networks

Paul J. Shin, Henry Medeiros, Johnny Park, A. Kak
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引用次数: 3

Abstract

Wireless sensor networks (WSN) typically employ dynamic duty cycle schemes to efficiently handle different patterns of communication traffic in the network. However, existing duty cycling approaches are not suitable for event-driven WSN, in particular, camera-based networks designed to track humans and objects. A characteristic feature of such networks is the spatially-correlated bursty traffic that occurs in the vicinity of potentially highly mobile objects. In this paper, we propose a concept of indirect sensing in the MAC layer of a wireless camera network and an active duty cycle adaptation scheme based on Kalman filter that continuously predicts and updates the location of the object that triggers bursty communication traffic in the network. This prediction allows the camera nodes to alter their communication protocol parameters prior to the actual increase in the communication traffic. Our simulations demonstrate that our active adaptation strategy outperforms TMAC not only in terms of energy efficiency and communication latency, but also in terms of TIBPEA, a QoS metric for event-driven WSN.
无线摄像机网络的预测占空比自适应
无线传感器网络(WSN)通常采用动态占空比方案来有效处理网络中不同模式的通信流量。然而,现有的占空比方法并不适用于事件驱动的WSN,特别是用于跟踪人和物体的基于摄像机的网络。这种网络的一个特征是发生在潜在高度移动对象附近的空间相关突发流量。在本文中,我们提出了无线摄像机网络MAC层的间接感知概念和一种基于卡尔曼滤波的主动占空比自适应方案,该方案持续预测和更新触发网络中突发通信流量的对象的位置。这种预测允许摄像机节点在通信流量实际增加之前更改其通信协议参数。我们的仿真表明,我们的主动自适应策略不仅在能效和通信延迟方面优于TMAC,而且在TIBPEA(事件驱动WSN的QoS度量)方面优于TMAC。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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