Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks
This work addresses video transmission bottlenecks for applications like surveillance and traffic monitoring in wireless sensor networks, but it appears incremental as it builds on existing compression and routing methods.
The paper tackles the problem of video transmission delays in Wireless Multimedia Sensor Networks by compressing video tracking using a CamShift-based algorithm and implementing a bandwidth balancing strategy that dynamically selects next-hop nodes based on predicted bandwidth capacity, resulting in significantly increased data received by the sink node and decreased transmission delay.
There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by big size of video data and fixed bandwidth allocation in constant routing path. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for next hop with the highest potential bandwidth capacity to resume communication. Key to the strategy is that each node merely maintains two parameters that contains its historical bandwidth varying trend and then predicts its near future bandwidth capacity. Then forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environment.