Title: Information scheduling method of big data platform based on ant colony algorithm

Authors: Xindi Tong; Yanming Wan

Addresses: Information Centre, Xinxiang Vocational and Technical College, Xinxiang, China ' Information Centre, Xinxiang Vocational and Technical College, Xinxiang, China

Abstract: This paper proposes an information security scheduling method for big data platforms based on ant colony algorithm. First, collect big data platform information and conduct noise reduction and compression processing on the information. Then, determine the priority of the big data platform information scheduling task, refer to the task priority, and use the ant colony algorithm for task scheduling and resource allocation. Finally, build the information scheduling function of big data platform, use the pheromone update mechanism to constrain the scheduling function and achieve the goal function solution through the volatilisation of ant colony pheromone, so as to achieve the safe scheduling of information. The experimental results show that the data acquisition accuracy of the proposed method can reach 0.95, the transmission delay cannot exceed 0.3 s and the information security can reach 99.99%, effectively improving the information security scheduling effect of big data platforms.

Keywords: ant colony algorithm; information denoising and compression; big data platform; information scheduling; task priority.

DOI: 10.1504/IJCAT.2024.141353

International Journal of Computer Applications in Technology, 2024 Vol.74 No.1/2, pp.1 - 9

Received: 16 Nov 2023
Accepted: 13 Feb 2024
Published online: 09 Sep 2024 *

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