Multi-Task Scheduling Method for Information Security of Heterogeneous Big Data Networks Based on Artificial Intelligence Technology

Multi-task scheduling of heterogeneous big data network information is proposed to improve the optimal configuration and application ability of network big data resources. A multi-task scheduling method of heterogeneous big data network information security based on artificial intelligence technology is proposed. A distributed storage and transmission structure model of heterogeneous big data is established under the task scheduling framework of cloud computing, and the heterogeneous mapping relationship is described according to the task submitted by users and the network information distribution between virtual machines. This paper establishes a scheduling channel between virtual machines and hosts, reasonably places and migrates heterogeneous big data network information to suitable hosts through artificial intelligence technology, and realizes reasonable allocation of computing resources and multi-task scheduling by using weighted polling scheduling method, so as to realize load-balanced scheduling of heterogeneous network information. The simulation results show that this method has good load balance in information task scheduling of heterogeneous big data networks, and the scheduling method has excellent global search and parallel search capabilities, which can adapt to large-scale information optimization of heterogeneous big data networks.