Complex Real-Time Network Topology Generation Optimization Based on Message Flow Control

There are high requirements for real-time performance of some complex systems, such as in-vehicle systems, avionics systems and so on. Large-scale message interaction within these systems constitutes a complex message interaction network, and the topology of the interaction network has a great impact on its real-time performance as different topologies can cause dramatic differences in message transmission delays. Community discovery and topological grouping are the mainly methods for network topology generation. However, these methods cannot directly guarantee real-time performance. This paper proposes a complex real-time network topology generation algorithm based on message flow control, and compares its real-time performance with manually designed network topology based on balanced strategy. Considering that the control mechanism of message flow is the main influencing factor for network real-time performance, frame length and bandwidth allocation gap (BAG) of the message in the network are measured as the influence factors in the process of network topology construction. The nodes in the network are clustered according to the tightness of communication to ensure the real-time performance of the network. Analytic methods are used to verify the real-time performance of network topology. In the detailed comparison process, the queuing strategy of message in the nodes is divided into two cases: First-In-First-Out (FIFO) and Static Priority (SP). The results show that the real-time performance of almost 74% of the message flow in the algorithm generated network topology based on flow control is better than the artificially designed network topology for the two different queuing strategies.