Abstract
One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.
Highlights
In recent years, Wireless Visual Sensor Networks (WVSNs) have emerged as an interesting field.Popular applications are environmental monitoring, seismic detection, military surveillance, medical monitoring, video surveillance, or the Internet of Things (IoT), etc. [1]
According to the arc weight on each link is the combination of end-to-end delay from the user perspective and average delay from the system perspective, Near-Optimal Distributed QoS Constrained (NODQC) can choose other less or non-congested paths for the sessions and balance network-wide the traffic loading
In wireless visual sensor networks for real time video surveillance, sensor nodes need to be forwarded the packets to the sinks within an acceptable delay under limited resource constraints, including embedded vision processing, data communication, battery energy issues
Summary
Wireless Visual Sensor Networks (WVSNs) have emerged as an interesting field. As compared to a WSN, the camera equipped sensor nodes in WVSNs can capture, process and transmit the real time visual data (images, video). Since the visual data is much larger and complicated than scalar data, delay Quality of Service (QoS) is a challenging issue resource for constrained WVSNs. WVSNs attract more attention on how the camera sensor nodes can cooperatively pass their data more efficiently with minimum delay through the network on a large scale or under realistic physical environmental conditions [2,3]. For real-time video surveillance applications, meeting the end-to-end delay QoS is the most important criteria. Due to the limited resources of WVSNs, delay QoS routing decisions should consider overall resource utilization so that the future video surveillance applications could be satisfied. Strategy in WVSNs to meet the end-to-end delay QoS for each application and at the same time minimize the average delay
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