Delay-Optimal Cooperation Transmission in Remote Sensing Satellite Networks

Many remote sensing applications, such as the forest fire monitoring, need to send a large volume of data to the ground with low delay. Therefore, the cooperation transmission, which relies on cooperation among satellites to achieve continuous transmission, emerges as an indispensable technique. Most existing work cannot optimize the delay through dynamic cooperation transmission. In this paper, we investigate how to optimize the delay in remote sensing satellite networks based on cooperation transmission, where cooperation hotspots refer to the satellites with ground-satellite links to the Earth Stations (ESs). First, we propose the cooperation capability model to quantify capabilities of cooperation hotspots, based on the joint control of the dynamic topology and time-varying available resources. Then, we uniformly model the inter-satellite routing and satellite-ES transmission scheduling, formulate the satellite cooperation transmission problem and prove its NP-hardness. To solve the problem, we propose the delay-optimal cooperation transmission scheme, including the cooperation routing principle based on topology features, the centralized cooperation transmission (CCT) algorithm based on randomized rounding and the distributed cooperation transmission (DCT) based on local information. Both algorithms take advantage of the cooperation capability model and adapt well to the dynamic topology and time-varying available resources. Finally, we formally analyze the approximation ratios and the time complexities of both the CCT and the DCT algorithms. We also prove that the DCT algorithm always setups loop-free paths. NS2-based simulation results demonstrate that our schemes have good scalability, and both CCT and DCT algorithms reduce the end-to-end delay on average by more than 21.77% compared to work in the state-of-the-art, and significantly improve throughput, packet loss rate and flow completion time.