Heterogeneous Resource Management for DAG-Based Task Offloading in Satellite Networks

Low earth orbit (LEO) satellite networks, which integrate with communication, sensing, and computing capabilities, have emerged as a promising approach to improve the performance of service quality and network utility. In that case, cooperative edge computing among several satellites and heterogeneous onboard resource management is viewed as a significant challenge, particularly since the task of data processing involves multiple functions with complex serial and parallel dependencies that need to be scheduled and executed in a particular order. Therefore, in this paper, the heterogeneous resource management for complex task offloading in LEO satellite networks is investigated by introducing directed acyclic graph (DAG). The problem of DAG-based task offloading is formulated to minimize the joint deployment costs in terms of computing, network bandwidth, and service delay. A neighborhood-based breadth first search (N-BFS) approach is proposed to obtain sub-optimal solutions of VNF placement and data routing in an acceptable computation complexity. The experiments with three baselines of Viterbi, BFS, and Gurobi are conducted to evaluate the performance of N-BFS. Simulation results demonstrate that the N-BFS approach is effective and efficient for solving the DAG-based task offloading problem by trade-off between quality of solution and time complexity.