Online Container Scheduling for Data-intensive Applications in Serverless Edge Computing
Online Container Scheduling for Data-intensive Applications in Serverless Edge Computing
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DOI：
10.1109/infocom53939.2023.10229034
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Xiaojun Shang;Yingling Mao;Yu Liu;Yaodong Huang;Zhen Liu;Yuanyuan Yang
中科院分区：
文献类型：
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作者：
Xiaojun Shang;Yingling Mao;Yu Liu;Yaodong Huang;Zhen Liu;Yuanyuan Yang
将新兴的无服务器模式引入边缘计算可以避免有限边缘资源的过度和不足，并使复杂的边缘资源管理对应用程序开发人员透明，这在很大程度上促进了边缘应用程序的成本效益，可移植性和短时间上市。然而，边缘环境的计算/数据分散和设备/网络异构性阻止了当前的无服务器计算平台适应网络边缘。在本文中，我们通过制定容器放置和数据流路由问题来解决这些挑战，该问题充分考虑了边缘网络的异构性以及在资源有限的边缘服务器上操作无服务器平台的开销。我们设计了一个在线算法来解决这个问题。我们进一步展示了每个到达集装箱的局部最优解，并证明了其对最优离线解的理论保证。我们还进行了大量的模拟实验结果的基础上，显示所提出的算法的优势，现有的基线。
Introducing the emerging serverless paradigm into edge computing could avoid over- and under-provisioning of limited edge resources and make complex edge resource management transparent to application developers, which largely facilitates the cost-effectiveness, portability, and short time-to-market of edge applications. However, the computation/data dispersion and device/network heterogeneity of edge environments prevent current serverless computing platforms from acclimating to the network edge. In this paper, we address such challenges by formulating a container placement and data flow routing problem, which fully considers the heterogeneity of edge networks and the overhead of operating serverless platforms on resource-limited edge servers. We design an online algorithm to solve the problem. We further show its local optimum for each arriving container and prove its theoretical guarantee to the optimal offline solution. We also conduct extensive simulations based on practical experiment results to show the advantages of the proposed algorithm over existing baselines.