Towards Elastic and Sustainable Data Stream Processing on Edge Infrastructure

Marcos Dias de Assunção
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Abstract

Much of the data produced today is processed as it is generated by data stream processing systems. Although the cloud is often the target infrastructure for deploying data stream processing applications, resources located at the edges of the Internet have increasingly been used to offload some of the processing performed in the cloud and hence reduce the end-to-end latency when handling data events. In this work, I highlight some of the challenges in executing data stream processing applications on edge computing infrastructure and discuss directions for future research on making such applications more elastic and sustainable.
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面向边缘基础设施的弹性和可持续数据流处理
今天产生的大部分数据都是由数据流处理系统处理的。尽管云通常是部署数据流处理应用程序的目标基础设施,但位于互联网边缘的资源已越来越多地用于卸载在云中执行的一些处理,从而减少处理数据事件时的端到端延迟。在这项工作中,我强调了在边缘计算基础设施上执行数据流处理应用程序的一些挑战,并讨论了使此类应用程序更具弹性和可持续性的未来研究方向。
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Sampling-based Label Propagation for Balanced Graph Partitioning ICPE '22: ACM/SPEC International Conference on Performance Engineering, Bejing, China, April 9 - 13, 2022 The Role of Analytical Models in the Engineering and Science of Computer Systems Enhancing Observability of Serverless Computing with the Serverless Application Analytics Framework Towards Elastic and Sustainable Data Stream Processing on Edge Infrastructure
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