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A new task scheduling scheme based on dispersed computing is proposed to address the problem of poor utilization of idle computing resources in the network by the traditional computing paradigm. The scheme designs a dispersed computing task scheduling model to reduce the load pressure on NCPs in a recursive manner by combining the idea of multiple hops. For the characteristics of geographic dispersion and network dynamics in the dispersed computing environment, the time delay is selected as the optimization objective, and the task scheduling decision is made in a distributed manner by combining it with the artificial fish swarm algorithm. At the same time, the scheduling algorithm is designed mainly by setting variable step size and field of view so that the algorithm can guarantee the convergence speed while the solution accuracy is improved. The experiments show that the algorithm meets the high requirements of dispersed computing on time delay and achieves the expected goal of the system.

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