https://scholars.lib.ntu.edu.tw/handle/123456789/642188
標題: | Function Clustering to Optimize Resource Utilization on Container Platform | 作者: | Lee, Chao Yu Hong, Ding Yong PANGFENG LIU Wu, Jan Jan |
關鍵字: | cold-start | container platform | Function-as-a-Service | serverless | 公開日期: | 1-一月-2023 | 來源出版物: | Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS | 摘要: | In recent years, container technology has gained significant attention in the software industry, with many businesses opting for its elasticity, cost-effectiveness, and ease of implementation. The most common way to ensure a seamless user experience is to keep a substantial number of containers active throughout the day, which causes resource over-provision. Conversely, closing the container right after handling the requests can reduce memory consumption but generate a cold start whenever the request arrives. Cold start occurrence and resource usage is a trade-off and presents a significant challenge on the container platform.To address this challenge, we observe that serving consecutive requests with the same container can notably decrease the number of cold starts. We propose TAC, a Temporal Adjacency Function Clustering algorithm, to meet the challenge. TAC selects the functions with time adjacency requests into a cluster from the historical data. TAC packs functions serving time adjacency requests into a cluster to reduce cold starts and enable efficient resource utilization. The experiment result shows that TAC reduces 8% cold start occurrences and 53% memory usage with the real-world traces compared to the state-of-the-art methods, e.g., Defuse [1] and Hybrid histogram policy [2]. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/642188 | ISBN: | 9798350330717 | ISSN: | 15219097 | DOI: | 10.1109/ICPADS60453.2023.00361 |
顯示於: | 資訊工程學系 |
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