Abstract
Wireless Multimedia Sensor Networks (WMSNs), that is, networks composed of a large number of wirelessly connected multimedia sensor nodes, are widely used in data collection, processing, and transmission. Due to the strict limitations of energy, in-network data processing techniques, such as data fusion, data aggregation, and data query, which can significantly improve the energy-efficiency of the networks, are very important. This special issue mainly focuses on the latest research in the area of data processing techniques in WMSNs. For this special issue, based on the review results we have selected five papers that address the major issues of data processing techniques in WMSNs and they are summarized as follows.
The paper “An Optimized Approach for Time-Constrained and Reliable Bursty Data Acquisition in WMSNs” proposes an optimized approach to reduce a bursty data acquisition time so that it can satisfy more applications with tighter time constraints. For this purpose, the authors devise a path reservation scheme for an energy-efficient and time-constrained data transmission and a frame-slot scheduling scheme using two channels that enables the concurrent data transmission. Simulation results show that the proposed approach reduces a bursty data acquisition time largely compared to other ones.
The paper “Wireless Multimedia Sensor Network Based Subway Tunnel Crack Detection Method” presents a convenient, fast, and automated crack detection method based on a wireless multimedia sensor subway tunnel network. This method primarily provides a solution for image acquisition, image detection, and identification of cracks. In order to quickly obtain a surface image of the tunnel, the authors use special train image sensor nodes to provide the high speed and high performance processing capability with a large-capacity battery. The proposed process can significantly reduce the amount of data transmission by compressing the binary image obtained by initial processing of the original image.
The paper “A Balance Privacy-Preserving Data Aggregation Model in Wireless Sensor Networks” proposes a balance privacy-preserving data aggregation (BPDA) model based on slicing and mixing technology. Compared to fixed or random slicing, BPDA model gives a balance slicing mechanism to ensure that slice can be sent to the nodes which have lower privacy preservation and enhance the privacy-preserving efficacy. Furthermore, according to the influence of the node degree and energy, three different schemes are presented to keep the privacy-preserving data aggregation balance. Theoretical analysis and simulation show that BPDA model demonstrates a good performance in terms of privacy-preserving efficacy and communication overhead and prolongs the lifetime of network.
The paper “A Novel Compression Technique for Multi-Camera Nodes through Directional Correlation” proposes an extension to the authors’ previous scheme that has been presented to accomplish performance goals of a multisensor environment. Standard MPEG codec has been used to accomplish distributed motion compensation in prespecified directions known as directional correlation. Video frame correlation has been estimated locally at the camera node as well as across different nodes, defined as node communication strategies. Further, receiver feedback assists in quality control after reconstitution by decoder assessment. Results analysis illustrates increased gains in frame quality and compression saving, achieved through reducing node displacement from the reference node (NR).
The paper “A High Efficient and Real Time Data Aggregation Scheme for WSNs” proposes a real time and high efficient data aggregation scheme based on clustering routing algorithm. DMLDA includes three procedures: activating nodes, clustering nodes, and filtering messages. In filtering procedure, a special data structure named dynamic list will be established in every filtering node, it is designed to store messages transmitted by filtering node, and, comparing current message with list's items, the message's redundancy can be judged without any delay. To improve the filtering efficiency, the message list can be adjusted dynamically. The three procedures of data aggregation are all introduced, and the filtering method is designed in detail in this paper. At last, a series of experiments are simulated to prove our scheme's performance, and the advantages are analyzed in theory.