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Transmitting objects in images with service differentiation based source coding in wireless sensor networks

机译:在无线传感器网络中使用基于服务差异化的源代码传输图像中的对象

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Multimedia data transmission over sensor networks is crucial in monitoring and surveillance applications, such as object tracking. In these applications, several sensor nodes are equipped with cameras, and placed on pre-selected locations. When an event occurs, cameras around event capture images and transfer them to the sink over a multi hop path. Since sensor nodes operate with limited CPU, memory and bandwidth, resource utilization is needed for feasible processing and transmission of useful parts in an image. In this study, we provide network performance trade-offs for an object tracking application. In our experimental setup, the application utilizes cost-effective coding of image macro-blocks into “high” and “low” classes based on the object information they contain. We then investigate resource trade-offs for achieving the highest object transmission rate when only “high” blocks are injected into the service differentiated network. We conclude with some remarks on the tuning of network buffer length and retransmission count parameters, for the optimization of macro-block reliability in the given object tracking scenario.
机译:通过传感器网络的多媒体数据传输对于监视和监视应用(例如对象跟踪)至关重要。在这些应用中,几个传感器节点配备了摄像头,并放置在预先选择的位置。当事件发生时,事件周围的摄像机会捕获图像并将其通过多跳路径传输到接收器。由于传感器节点在有限的CPU,内存和带宽下运行,因此需要资源利用来对图像中的有用部分进行可行的处理和传输。在这项研究中,我们提供了对象跟踪应用程序的网络性能折衷。在我们的实验设置中,该应用程序根据图像宏块包含的对象信息将它们划算为“高”和“低”类别,从而进行了具有成本效益的编码。然后,当仅将“高”块注入到区分服务的网络中时,我们将研究资源折衷以实现最高的对象传输速率。最后,我们对网络缓冲区长度和重传计数参数的调整进行了总结,以优化给定对象跟踪情况下的宏块可靠性。

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