Terminal Micro-service Discovery Algorithm based on attractor model

Li Wang, Siyu Tang, Jiageng Zhang, Heshan Wang, Jiawei Han, Jianxiang Cao
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Abstract

In the intensive computing scenario with the application of micro-service framework, it is too costly to allocate resources centrally to the micro-service instance on the server side, and it cannot adapt to the changes of the environment in real time. Therefore, allocating resource for micro-service instance distributed on the terminal becomes an effective way to solve the problem mentioned above. A client-based micro-service discovery algorithm with attractor selection model is proposed in this paper, which has the characters of simple and intelligent evolution. At first, this paper models micro-service discovery problem, defines optimization object and constraints; then, it re-defines the parameters of attractor selection and proposes the client-based micro-service discovery algorithm with attractor selection model; and at last, it analyzes the performance of the proposed algorithm with the compared ones in the really productive environment. The experiment results show that the proposed algorithm reduces almost 32 % resource fragments and 70% running time than the compared ones.
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基于吸引子模型的终端微服务发现算法
在应用微服务框架的密集计算场景中,将资源集中分配给服务器端的微服务实例成本过高,且不能实时适应环境的变化。因此,为分布在终端上的微服务实例分配资源成为解决上述问题的有效途径。提出了一种基于吸引子选择模型的基于客户端的微服务发现算法,该算法具有简单、智能进化的特点。首先对微服务发现问题进行建模,定义优化对象和约束条件;然后,重新定义了吸引子选择的参数,提出了基于吸引子选择模型的基于客户端的微服务发现算法;最后,在实际生产环境中,对比分析了所提算法的性能。实验结果表明,该算法比对比算法减少了近32%的资源碎片和70%的运行时间。
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