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Data Deduplication in Wireless Multimedia Monitoring Network

DOI: 10.1155/2013/153034

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Wireless sensor network has been applied to many areas for a long time. A new kind of wireless sensors equipped with a camera and a microphone has been emerging recently. This kind of sensor is called wireless multimedia sensor (WMS) because it can capture and process multimedia data such as image, sound, and video. The visual monitoring network is a typical scenario of WMS application. Massive data would be produced in a short time because of the intensive WMS deployment. Many data aggregation and compression technologies have been proposed for addressing how to transfer data efficiently. However, data aggregation technologies need highly efficient router algorithm, and compression algorithms might consume more computation time and memory because of the high complexity. This paper applies data deduplication technology to this scenario. It can eliminate the redundant data from raw data to exploit the network bandwidth efficiently. Moreover, a chunking algorithm with low computation complexity is presented in this paper, and its efficiency has been proved through the experiments. 1. Introduction Wireless sensor network (WSN) consists of a large number of spatially distributed autonomous sensors which are connected by wireless communication. It is mainly used for dynamic acquisition of physical information within the network coverage which will be delivered to users later. Currently, WSN is widely applied to the capture, processing, and transmission of the data such as temperature, light intensity, humidity, and gas concentration [1, 2]. In the recent years, as the production level of sensors improves, additional camera, microphone, and other functional devices are installed on traditional wireless sensors and enable them to capture, process, and transfer multimedia information such as image, sound, and video, so that users can obtain improved physical information which is more vivid and more accurate. This new kind of sensor can be called wireless multimedia sensor (WMS). Wireless multimedia sensor network (WMSN) consists of WMS nodes, gateway nodes with storage, sink nodes, and so on. Then, a typical WMSN architecture is proposed in [3], as shown in Figure 1. WMSN is widely used in many areas including visual monitoring, individual positioning, industrial control, intelligent transportation, environmental monitoring, smart home, and telemedicine [3–5]. Figure 1: A typical system architecture of WMSN. Multimedia sensor nodes have limited resources such as energy capacity of battery, storage space, and computing power, while the information they acquire

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