基于两步分配和动态扩展的FaaS平台高效调度算法设计

Youngho Kim, Gyuil Cha
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引用次数: 5

摘要

随着云计算范式的发展和对基于事件的计算模型的需求不断增长,功能即服务(FaaS)在云计算领域广泛流行。通过在一个简单的FaaS原型上测试一个虚拟函数的执行,我们分析了函数实际执行所需的准备负载,从函数执行漫步器的分配到在FaaS平台上加载函数。根据分析结果,我们发现即使使用轻量级容器,第一个worker分配的成本也需要1,850ms,然后在同一节点上重新分配worker的成本需要470ms。结果表明,函数服务不足以作为一个高效的处理计算平台。我们提出了一种新的worker调度算法,合理分配worker在函数执行过程中的准备负荷,使FaaS平台更适合于高效的计算环境。提出的算法是在请求发生前分两步分配工人的分配任务,并提前预测需要分配的工人数量。将提出的工人调度算法应用于正在开发的FaaS平台时,我们估计与FaaS原型相比,可以以低于3%的分配成本处理工人分配请求。因此,期望功能服务通过显著提高工人分配成本,成为一个高效的计算平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of the Cost Effective Execution Worker Scheduling Algorithm for FaaS Platform Using Two-Step Allocation and Dynamic Scaling
Function as a Service(FaaS) has been widely prevalent in the cloud computing area with the evolution of the cloud computing paradigm and the growing demand for event-based computing models. We have analyzed the preparation load required for the actual execution of a function, from assignment of a function execution walker to loading a function on the FaaS platform, by testing the execution of a dummy function on a simple FaaS prototype. According to the analysis results, we found that the cost of first worker allocation requires 1,850ms even though the lightweight container is used, and then the worker re-allocation cost require 470ms at the same node. The result shows that the function service is not enough to be used as a high efficiency processing calculation platform. We propose a new worker scheduling algorithm to appropriately distribute the worker's preparation load related to execution of functions so that FaaS platform is suitable for high efficiency computing environment. Proposed algorithm is to distribute the worker 's allocation tasks in two steps before the request occurs, and predict the number of workers required to be allocated in advance. When applying the proposed worker scheduling algorithm in FaaS platform under development, we estimate that worker allocation request can be processed with an allocation cost of less than 3% compared to the FaaS prototype. Therefore, it is expected that the functional service will become a high efficiency computing platform through the significant improvement of the worker allocation cost.
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