Location, Proximity, Affinity – The key factors in FaaS

IF 0.9 Q4 TELECOMMUNICATIONS Infocommunications Journal Pub Date : 2020-01-01 DOI:10.36244/ICJ.2020.4.3
Dávid Haja, Z. Turányi, László Toka
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引用次数: 4

Abstract

The Function-as-a-Service paradigm emerged not only as a pricing technique, but also as a programming model promising to simplify developing to the cloud. Interestingly, while placing functions across hosts under the service platform is believed to be flexible, currently the available platforms pay little attention to co-locate connected functions, or data with the respective processing function in order to improve performance. Even though the local function invocation and data access might be an order of magnitude faster than their remote intra-cloud counterparts. In this paper, we therefore propose a Function-asa- Service platform design that reaps the performance benefits of co-location. We build the platform on WebAssembly, a secure and flexible tool for efficient local function invocations, and on a distributed in-memory database, which allows arbitrary data placement. On top we advocate smart placement strategies for function executions and data, decoupled from the functions. Hence we envision good horizontal scaling of functions while keeping the experienced processing latency to that of a single machine case.
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位置、邻近性、亲和性——FaaS的关键因素
功能即服务范式不仅作为一种定价技术出现,而且还作为一种编程模型出现,有望简化面向云的开发。有趣的是,虽然在服务平台下跨主机放置功能被认为是灵活的,但目前可用的平台很少关注为了提高性能而将连接的功能或数据与各自的处理功能放在一起。尽管本地函数调用和数据访问可能比云内远程函数调用和数据访问快一个数量级。因此,在本文中,我们提出了一个功能即服务的平台设计,以获得协同定位的性能优势。我们在WebAssembly上构建平台,WebAssembly是一种安全灵活的工具,用于高效的本地函数调用,而WebAssembly是一个分布式内存数据库,它允许任意放置数据。最重要的是,我们提倡函数执行和数据的智能放置策略,与函数解耦。因此,我们设想良好的水平扩展功能,同时将经验处理延迟保持在单个机器情况下。
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来源期刊
Infocommunications Journal
Infocommunications Journal TELECOMMUNICATIONS-
CiteScore
1.90
自引率
27.30%
发文量
0
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