自动云适应的生物形态模型

G. Stoykov, A. Yazidi
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引用次数: 4

摘要

尽管在云计算领域有大量的研究,但与一般研究领域相比,生物启发云计算领域的研究不足。本研究试图找到如何在云中实现生物形态模型以实现自适应云行为的答案。细胞从一种类型转化为另一种类型的细胞分化过程被选为已开发的技术模型的基础模型。我们定义了与云的类比,其中干细胞是空白服务器,而web服务器是具有特定功能的细胞。通过组合配置管理、版本控制和云部署系统,在云中应用了对这种生物过程的模仿。使用自动云扩展作为自适应行为的一个案例是研究的主要目标。已经开发了一种将生物模型映射到云的方法,云由一个原型组成,其中信号检测和节点激活是通过使用随机生成的计时器的概念触发的。所获得的性能结果是不同的,这取决于一般的定时器分布,为未来的改进和不同的算法建议提供了新的思路。
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A Biomorphic Model for Automated Cloud Adaptation
Although there is an extensive amount of research covering in the area of Cloud computing, the field of bioinspired cloud computing is underinvestigated when compared to the general research area. This study tries to find answers on how a biomorphic model can be implemented in the cloud in order to achieve adaptive cloud behaviour. The process of cellular differentiation where cells transform from one type to another, is chosen to be the foundation model for a developed technical model. We define analogies to the cloud where stem cells are blank servers and web servers are cells with a specific function. With a combination of configuration management, version control and cloud deployment systems, an imitation of this biological process is applied in the cloud. The use of automated cloud scaling as a case of adaptive behaviour is the main goal of the research. One approach has been developed for mapping the biological model to the cloud which consists of a prototype where the signal detection and node activation is being triggered by using the concept of random generated timers. The obtained performance results were varying, depending on the general timer distribution, providing new ideas for future improvements and different algorithm proposals.
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