蚁群算法的大数据计算引擎均衡部署数学建模研究

Research on Mathematical Modeling of Balanced Deployment of Ant Colony Algorithm Big Data Computing Engine

摘要: 随着大数据技术的迅猛发展，大数据计算引擎的性能优化和均衡部署问题成为研究热点。蚂蚁算法是一种模仿自然界中蚂蚁觅食的方法，它具有良好的全局寻优能力和较强的鲁棒性，非常适合求解复杂的优化问题。在此基础上，提出了一种基于蚁群算法的大规模数据挖掘方法，研究面向大数据计算引擎平衡配置问题的蚂蚁算法，通过建立数学模型，对计算资源进行优化配置。本项目的研究成果将为大数据处理引擎的平衡部署提供新的研究思路与方法。

Abstract: With the rapid development of big data technology, the performance optimization and balanced deployment of big data computing engine have become a research hotspot. Ant algorithm is a method that mimics ants foraging in nature. It has good global optimization ability and strong robustness, which is very suitable for solving complex optimization problems. Based on this, we propose a large-scale data mining method based on ant colony algorithm, studies the ant algorithm for the balanced configuration problem of big data computing engine, and optimizes the allocation of computing resources by establishing a mathematical model. The research results of this project will provide new research ideas and methods for the balanced deployment of the big data processing engine.