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In a conventional finite state machine, the transition is associated with a set of input Boolean conditions and a set of output Boolean functions. In an extended finite state machine (EFSM) model, the transition can be expressed by an “if statement” consisting of a set of trigger conditions. If trigger conditions are all satisfied, the transition is fired, bringing the machine from the current state to the next state and performing the specified data operations.
A Finite State Machine-Based Cooperative Service Allocation Method for Low-Earth Orbit Satellite Clusters
This invention proposes a collaborative service allocation method for low-Earth orbit (LEO) satellite constellations based on finite state machines, belonging to the field of LEO satellite constellation technology. First, this invention constructs an extended finite state machine spatiotemporal graph model to accurately represent on-board resources and state transitions while shielding the dynamics of LEO satellites. Then, a directed acyclic graph (DAG) model is used to represent services, establishing a graph mapping relationship between the DAG and the extended finite state machine spatiotemporal graph, and establishing a latency optimization problem. Finally, a constrained selection adaptive binary particle swarm optimization algorithm is used to solve the latency optimization problem of the graph mapping relationship, finding the mapping strategy with the lowest latency to complete the collaborative service allocation of the satellite constellation. This invention is designed for LEO satellite constellation scenarios. The service collaborative computation based on finite state machines meets the computational requirements of latency-sensitive services in these scenarios, effectively overcomes the heterogeneity of LEO satellite networks, and achieves latency optimization for LEO satellites during simultaneous transmission and computation.
Owner:THE 54TH RESEARCH INSTITUTE OF CHINA ELECTRONICS TECHNOLOGY GROUP CORPORATION