Aggregation and Multicast Coded Repair Technique for LEO Cloud Storage Constellation

LEO cloud storage constellation (LCSC) has gained significant popularity thanks to its on-board data storage capability and extensive inter-satellite connectivity. Unfortunately, the satellite disks will fail occasionally due to cosmic radiation and energy depletion, which leads to data loss and network unavailable. However, multi-node repair in the LCSC leads to the larger repair delay and the higher energy cost. To address this, we introduced the aggregation and multicast coded repair (AMCR) to fast recover the stored data using Reed-Solomon (RS) codes. We first propose the multi-weight multinode repair tree (MWNRT) model, i.e., a staged tree graph containing edge weights, to measure the multiple factors affecting repair performance. Next, we analyze the repair delay and the energy cost associated with multi-node repair leveraging AMCR. Then, to minimize repair delay while reducing energy cost, the aggregation-based multiple single-node repair trees construction (A-MSRT) algorithm is designed to construct multiple single-node repair trees based on the shortest-path principles. While the multicast-based aggregation of multiple repair trees (M-AMRT) algorithm is designed to select the repair tree with the longest delay from the output of A-MSRT as the initial repair tree, then adds the remaining replacement nodes. And the complexity of the two algorithms is elaborated and proven to be reasonable. Simulations show that AMCR scheme outperforms other schemes under different network conditions in LCSC.