Strategies for optimal allocation of cloud computing resources for innovation and entrepreneurship education in industry-teaching integration environment

Abstract Relying on cloud computing technology, this paper builds a creative and entrepreneurial education platform in the environment of industry-education fusion, with the intention of promoting the development of creative and entrepreneurial education in universities and even in the society. The functional modules, platform framework and business support service architecture of the innovation and creativity education platform are designed, the ant colony algorithm is used to solve the cloud computing resource allocation problem of the platform, and the ant perimeter model is adopted as the updating strategy of pheromone. For the combinatorial optimization problem of cloud computing resource allocation, an annealing simulation algorithm is introduced to optimize the ant colony algorithm and a new improved algorithm (HGAACO) is proposed. Matching factor is introduced to define the matching degree of tasks and resource nodes, and the calculation methods of load balance degree, objective function and fitness function are proposed and determined. With the help of CloudSim, we carry out simulation experiments on the application of innovative and creative education platform, comparing with the GAAA algorithm and ACO algorithm, the HGAACO algorithm in this paper consumes a shorter time on the resource allocation scheduling, only 73.6ms, and the standard deviation of the matching results is always less than 5. When the number of resource allocation tasks is 20, 40, 60, 80, 100 respectively, the execution time of HGAACO algorithm in this paper is 75ms, 141ms, 199ms, 268ms, 322ms correspondingly, and the execution time is less than that of the comparative GAAA algorithm and ACO algorithm, which demonstrates a good performance of cloud computing resource allocation.