LAUSR

The proliferation of portable embedded cameras makes it easy for mobile users to collaboratively collect environmental sensing videos in network-underdeveloped or disaster-affected zones. Compared with in other scenes, the video upload in disaster areas is more challenging due to intermittent wireless connections and moving transmission destinations. Deduplication (redundancy elimination) and cooperative video transmission are two effective ways to ensure timely video collection in damaged networks. However, deduplication in mobile crowd sensing (MSC) is primarily performed on texts and images. Furthermore, most of deduplication technologies require global information and are separated from video transmission routing. To solve such problems, this paper proposes a collaborative upload method of sensing videos, which performs the local video deduplication without excessive comparisons and feature exchanges. Also, we combine the two-round deduplication with the content-aware dynamic routing to avoid the propagation of redundant items caused by the content-free video routing. Besides, we integrate a novel mutual-assisted mechanism into our method to motivate relay cooperation and achieve load balance. We formulate the deduplication-supported collaborative video upload as a multi-stage decision problem. To tackle the time-varying destinations and the local deduplication during transmission in the decision problem, we develop a stepwise Mutual-Assisted Video Upload Algorithm (MAVUA) to route videos and remove duplicates. Extensive numerical validations are conducted to compare MAVUA with the existing algorithms. The numerical results demonstrate that MAVUA can save roughly 11% transmission time and achieve 80% load balancing improvement.