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Function Delivery Network: Extending Serverless Computing for Heterogeneous Platforms
arXiv - CS - Performance Pub Date : 2021-02-03 , DOI: arxiv-2102.02330 Anshul Jindal, Michael Gerndt, Mohak Chadha, Vladimir Podolskiy, Pengfei Chen
arXiv - CS - Performance Pub Date : 2021-02-03 , DOI: arxiv-2102.02330 Anshul Jindal, Michael Gerndt, Mohak Chadha, Vladimir Podolskiy, Pengfei Chen
Serverless computing has rapidly grown following the launch of Amazon's
Lambda platform. Function-as-a-Service (FaaS) a key enabler of serverless
computing allows an application to be decomposed into simple, standalone
functions that are executed on a FaaS platform. The FaaS platform is
responsible for deploying and facilitating resources to the functions. Several
of today's cloud applications spread over heterogeneous connected computing
resources and are highly dynamic in their structure and resource requirements.
However, FaaS platforms are limited to homogeneous clusters and homogeneous
functions and do not account for the data access behavior of functions before
scheduling. We introduce an extension of FaaS to heterogeneous clusters and to support
heterogeneous functions through a network of distributed heterogeneous target
platforms called Function Delivery Network (FDN). A target platform is a
combination of a cluster of homogeneous nodes and a FaaS platform on top of it.
FDN provides Function-Delivery-as-a-Service (FDaaS), delivering the function to
the right target platform. We showcase the opportunities such as varied target
platform's characteristics, possibility of collaborative execution between
multiple target platforms, and localization of data that the FDN offers in
fulfilling two objectives: Service Level Objective (SLO) requirements and
energy efficiency when scheduling functions by evaluating over five distributed
target platforms using the FDNInspector, a tool developed by us for
benchmarking distributed target platforms. Scheduling functions on an edge
target platform in our evaluation reduced the overall energy consumption by 17x
without violating the SLO requirements in comparison to scheduling on a
high-end target platform.
中文翻译:
功能交付网络:扩展异构平台的无服务器计算
随着Amazon Lambda平台的推出,无服务器计算已迅速发展。功能即服务(FaaS)是无服务器计算的关键实现因素,它允许将应用程序分解为在FaaS平台上执行的简单独立功能。FaaS平台负责为功能部署和促进资源。当今的几种云应用程序分布在异构的连接计算资源上,并且在结构和资源要求方面具有很高的动态性。但是,FaaS平台仅限于同类集群和同类功能,并且在调度之前不考虑功能的数据访问行为。我们将FaaS扩展到异构集群,并通过称为功能交付网络(FDN)的分布式异构目标平台的网络来支持异构功能。目标平台是同类节点群集和位于其顶部的FaaS平台的组合。FDN提供功能交付即服务(FDaaS),将功能交付给正确的目标平台。我们展示了机会,例如目标平台的特性各不相同,多个目标平台之间进行协作执行的可能性以及FDN在实现两个目标时提供的数据本地化:服务水平目标(SLO)要求和通过评估五个以上功能来调度功能时的能源效率使用FDNInspector的分布式目标平台,我们开发的用于对分布式目标平台进行基准测试的工具。与在高端目标平台上进行调度相比,我们评估中的边缘目标平台上的调度功能将总体能耗降低了17倍,而没有违反SLO要求。
更新日期:2021-02-05
中文翻译:
功能交付网络:扩展异构平台的无服务器计算
随着Amazon Lambda平台的推出,无服务器计算已迅速发展。功能即服务(FaaS)是无服务器计算的关键实现因素,它允许将应用程序分解为在FaaS平台上执行的简单独立功能。FaaS平台负责为功能部署和促进资源。当今的几种云应用程序分布在异构的连接计算资源上,并且在结构和资源要求方面具有很高的动态性。但是,FaaS平台仅限于同类集群和同类功能,并且在调度之前不考虑功能的数据访问行为。我们将FaaS扩展到异构集群,并通过称为功能交付网络(FDN)的分布式异构目标平台的网络来支持异构功能。目标平台是同类节点群集和位于其顶部的FaaS平台的组合。FDN提供功能交付即服务(FDaaS),将功能交付给正确的目标平台。我们展示了机会,例如目标平台的特性各不相同,多个目标平台之间进行协作执行的可能性以及FDN在实现两个目标时提供的数据本地化:服务水平目标(SLO)要求和通过评估五个以上功能来调度功能时的能源效率使用FDNInspector的分布式目标平台,我们开发的用于对分布式目标平台进行基准测试的工具。与在高端目标平台上进行调度相比,我们评估中的边缘目标平台上的调度功能将总体能耗降低了17倍,而没有违反SLO要求。