A Task-Driven Updated Discrete Graph Assisted Minimum Delivery Delay Routing for Remote Sensing Disruption-Tolerant Networks

Benefiting from the extensive coverage, remote sensing satellites have been playing important roles in surveillance for regions on the earth surface. In order to accommodate with intermittent connected and partitioned characteristics of satellite topology, disruption-tolerant network (DTN) develops a feasible solution for networking among such satellites. However, utilized widely and frequently in the future, numerous image covering hundreds of spectral bands and kilometers width is supposed to be delivered simultaneously. Due to the timeliness constrain, efficient routing design with minimum delivery delay for bulk and concurrent image data has become the bottleneck of remote sensing application. Considering data transmission initiated as different tasks, therefore, the Task-driven Updated Discrete Graph (TUDG) is designed to depict the topology evolution, with task data and edge capacity model for BP/LTP incorporated Remote Sensing DTN Network (RS-DTNet). In particular, the multitask-based delivery delay analytical framework is proposed based on the TUDG graph model, by solving a mixed integer Max-Min optimization problem. The Multi-Task Minimum Delay Routing (MTMDR) is designed with the delay-optimal flow distribution, dispatching appropriate bundle data to edges in the TUDG. This flow-based routing avoids the path selection procedure, which may degenerate the delivery delay performance. Through numerical simulation based on the representative RS-DTNet scene, the proposed MTMDR routing strategy shows to advantage on delivery delay, compared with typical path-based routing.