Abstract

Aim: A data structure visualisation system uses object-oriented thinking and COM technology to dynamically and interactively simulate and track data structure algorithms and realize the dynamic synchronisation and visualisation of abstract data structures and algorithms using the data modelling function and self-test function. Background: Teaching data structures and algorithms is difficult because of their abstraction and dynamics; the use of icons in classroom teaching can be partially abstracted into intuition, but analysing the instantaneous dynamic characteristics of the object and the dynamic execution process of the algorithm is difficult. Objective: A data structure visualisation system employs a data modelling function, visual data structures, a user-friendly and flexible interface, and multipath features for multilevel users. Such systems can be designed more effectively by using the ant colony algorithm. Methods: The more the ants pass by a certain path, the higher the concentration of residual pheromone, and the higher the probability of the subsequent ant selecting that path. Therefore, the individuals in an ant colony communicate messages and cooperate with each other for foraging. Results: The resulting speedup ratio indicates that the speedup is smaller when the number of nodes is 100 or more; the acceleration is higher when the node reaches a certain scale, and the speedup ratio does not change considerably. In this study, the traffic simulation software VISSIM was used to generate road network data; the generated traffic data were analysed and used to design a traffic network data structure. Conclusion: The traffic network data model oriented to the ant colony algorithm was established through abstraction. Accordingly, a parallel ant colony algorithm based on cloud computing was implemented. Finally, a Hadoop cloud computing platform was established and used to run and test the parallel ant colony algorithm program; several experiments were conducted, and the experimental results were analysed concurrently.

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