Research Of Resource Allocation Strategy In TT&C Network

Telemetry, Track and Command (TT&C) network resource allocation problem is to assign limited ground station resources and time windows reasonably according to satellites'tasks for solving the serious problem about"multiple satellites conflict". In this thesis, the model of resource distribution and scheduling algorithms are studied. The main achievements are as follows:Firstly, this thesis analyses the main constraint conditions in TT&C network. Based on time window, some basic indicators such as utilization rate are analyzed. On the basis of the conflicts among the tasks, the conflict degree is put forward as a evaluating index, which offer support for reducing correlative dependence among the tasks. At last, network bandwidth and time delay are taken into consideration, the indexes can be needed to support reliable and secure transmission.Secondly, the constraint conditions of resource distribution in TT&C network are formalized, and then this thesis points out the main allocation problems about the current model and objective function. Based on above, a new representation form and scheduling model is designed, which provides a framework for designing the algorithms of resource distribution.Thirdly, based on the above model, this thesis designs two resource allocation algorithms. For improving genetic algorithm, task set is divided into some subsets, task allocation strategy is proposed, and then the improved genetic algorithm is studied. In quantum genetic algorithm, this thesis presents different scheduling algorithm based on static and dynamic rotation strategy. Meanwhile, the way of probability partition is utilized for initializing task set, and the quantum catastrophe and quantum crossover operator are used to escape the local optimum.In the end, the system of resource allocation is designed. The software of STK is utilized for calculating the usable time window between satellites and ground stations. And then several scenarios and process are designed for analyzing and validating the efficiency of these two scheduling algorithms. The experiment results indicate that,quantum genetic algorithm can allocate TT&C resource effectively,and solve the problem of conflicts reasonably.