Genetic Algorithm for mulit-Objective Optimization of containers allocation in cloud architecture

The use of containers in cloud architectures has become widespread, owing to advantages such as limited overheads, easier and faster deployment, and higher portability. Moreover, they present a suitable architectural solution for the deployment of applications created using a microservice development pattern. But the remain open issue is that ----- container resource allocation influences system performance and resource consumption, and so it is a key factor for cloud providers. In this paper, they propose a genetic algorithm approach, using the Non-dominated Sorting Genetic Algorithm 2

DataSketches Research Directions

在分析海量数据集时,即使对数据进行非常基本的查询,也可能需要巨大的计算资源(内存和计算时间)。这种查询的例子包括识别频繁项目,唯一计数查询,分位数和直方图查询,矩阵分析任务(例如主成分分析和潜在语义分析)以及更复杂的下游机器学习任务。一旦数据量大了之后,这些计算任务将变得十分困难。也达不到实时性的要求。
|