Abstract
For satisfying the quality of service (QoS) requirements and image denoising services in wireless sensor network (WSN) applications, based on opportunistic networking technology and generalized Gaussian mixture algorithm, an adaptive image processing and transmission scheme is proposed in this paper. According to the real-time state record matrix, the multi-objective optimization scheme with equalizer coefficients and the opportunistic cooperative scheme in view of energy and computing ability are studied, respectively. Then, the generalized Gaussian mixture algorithm is used to reduce the image data and eliminate the noise interference from the WSN environment. Finally, Simulation results show that the proposed scheme has better QoS support capability results such as reliability, real-time performance, and energy efficiency, as well as the image decoding accuracy including peak signal to noise ratio.
Highlights
With the development of wireless communication technology, mobile technology, and decline of sensor hardware cost, image capture, and transmission, video communication has been widely developed in the wireless sensor network (WSN) applications [1], which include the traffic detection, license plate recognition, object tracking and location applications, [2] etc
We found that the quality of service (QoS) of GGMON is better than the image processing scheme with opportunistic networking alone (IPONA) obviously
Processing, and transporting the image big data, we study the image transmission with opportunistic networking technology, which select the optimal relay sensors based on the real-time status including remaining energy and computing ability
Summary
With the development of wireless communication technology, mobile technology, and decline of sensor hardware cost, image capture, and transmission, video communication has been widely developed in the wireless sensor network (WSN) applications [1], which include the traffic detection, license plate recognition, object tracking and location applications, [2] etc. Contrary to the lack of processing capability and the queue control and error detection capabilities, Duc Minh Pham et al [16] proposed an innovative architecture for object extraction and a robust application-layer protocol for energy efficient image communication over WSNs. In view of resource constraints and challenge of digital image transmission for image-sensor-based WSNs, the design and implementation of WSNs with low costs, low power, and based on a low rate ZigBee protocol was presented and evaluated in [17]. In order to improve link utilization rate and system resources, each sensor node would calculate the remaining energy capacity by sensing and obtain the statistical quality of the link, opportunistically access network for transmission of image information. In view of randomness in the physical layer of wireless links, limited resources, and the conditions under multipath routing, the target of image transmission in WSNs based on the opportunistic networking is to ensure the image information transmission quality while maintaining minimal transmission delay, energy efficient. (7)dTihreecitmedaggerarpohutdiniggrappahthÀGis. converted into the (8)When the transmission path is interrupted, execution of step (4)–(7) is to satisfy the opportunity to optimization target image transmission and reestablish the communication path
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