Tackling Cold Start of Serverless Applications by Efficient and Adaptive Container Runtime Reusing
Tackling Cold Start of Serverless Applications by Efficient and Adaptive Container Runtime Reusing
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DOI：
10.1109/cluster48925.2021.00018
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发表时间：
2021-09
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影响因子：
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通讯作者：
Kun Suo;Junggab Son;Dazhao Cheng;Wei Chen;S. Baidya
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文献类型：
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作者：
Kun Suo;Junggab Son;Dazhao Cheng;Wei Chen;S. Baidya
在过去的几年中，无服务器计算由于其独特的优势，包括易于管理，自动扩展，内置容错等，改变了云和边缘应用程序开发和部署的范式。在本文中，我们提出了一个深入的性能分析的冷启动在无服务器的框架，并提出了HotC，一个基于容器的运行时管理框架，利用轻量级容器，以减轻冷启动，提高网络性能的无服务器应用程序。HotC维护一个实时容器运行时池，分析用户输入或配置文件，并提供可用的运行时以供立即重用。为了准确预测请求和有效管理热容器，我们设计了一个自适应活容器控制算法结合指数平滑模型和马尔可夫链方法。我们的评估结果表明，HotC引入的开销可以忽略不计，并且可以有效地提高云服务器和边缘设备中具有不同网络流量模式的各种应用程序的性能。
During the past few years, serverless computing has changed the paradigm of application development and deployment in the cloud and edge due to its unique advantages, including easy administration, automatic scaling, built-in fault tolerance, etc. Nevertheless, serverless computing is also facing challenges such as long latency due to the cold start. In this paper, we present an in-depth performance analysis of cold start in the serverless framework and propose HotC, a container-based runtime management framework that leverages the lightweight containers to mitigate the cold start and improve the network performance of serverless applications. HotC maintains a live container runtime pool, analyzes the user input or configuration file, and provides available runtime for immediate reuse. To precisely predict the request and efficiently manage the hot containers, we design an adaptive live container control algorithm combining the exponential smoothing model and Markov chain method. Our evaluation results show that HotC introduces negligible overhead and can efficiently improve the performance of various applications with different network traffic patterns in both cloud servers and edge devices.