Satellite image data downlink scheduling problem with family attribute: Model &Algorithm
This addresses a specific operational bottleneck in satellite data management for space agencies or remote sensing applications, but it appears incremental as it extends existing scheduling problems with segmentation.
The paper tackles the satellite image data downlink scheduling problem by segmenting large images for transmission across multiple time windows, proposing a bi-objective model to minimize transmission failure rate and segmentation times, and developing a differential evolutionary algorithm that shows efficiency in simulations.
The asynchronous development between the observation capability and the transition capability results in that an original image data (OID) formed by one-time observation cannot be completely transmitted in one transmit chance between the EOS and GS (named as a visible time window, VTW). It needs to segment the OID to several segmented image data (SID) and then transmits them in several VTWs, which enriches the extension of satellite image data downlink scheduling problem (SIDSP). We define the novel SIDSP as satellite image data downlink scheduling problem with family attribute (SIDSPWFA), in which some big OID is segmented by a fast segmentation operator first, and all SID and other no-segmented OID is transmitted in the second step. Two optimization objectives, the image data transmission failure rate (FR) and the segmentation times (ST), are then designed to formalize SIDSPWFA as a bi-objective discrete optimization model. Furthermore, a bi-stage differential evolutionary algorithm(DE+NSGA-II) is developed holding several bi-stage operators. Extensive simulation instances show the efficiency of models, strategies, algorithms and operators is analyzed in detail.