Exploiting Temporal-Spatial Characteristics for Function Scheduling in Serverless Computing

Jin Xin; Wu Bingyang; Liu Fangyue; Zhang Zili; Jia Yunshan

doi:10.7544/issn1000-1239.202330410

Journal of Computer Research and Development > 2023 > 60(9): 2000-2014. > DOI: 10.7544/issn1000-1239.202330410

Jin Xin, Wu Bingyang, Liu Fangyue, Zhang Zili, Jia Yunshan. Exploiting Temporal-Spatial Characteristics for Function Scheduling in Serverless Computing[J]. Journal of Computer Research and Development, 2023, 60(9): 2000-2014. DOI: 10.7544/issn1000-1239.202330410

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Exploiting Temporal-Spatial Characteristics for Function Scheduling in Serverless Computing

School of Computer Science, Peking University, Beijing 100871
Key Laboratory of High Confidence Software Technologies(Peking University), Ministry of Education, Beijing 100871

Funds: This work was supported by the National Key Research and Development Program of China (2022YFB4500700).

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Author Bio:
Jin Xin: born in 1989. PhD, associate professor. Senior member of CCF. His main research interests include systems software, computer networks, and cloud computing

Wu Bingyang: born in 2000. PhD candidate. Student member of CCF. His main research interests include machine learning systems, video conferencing, and cloud computing

Liu Fangyue: born in 2002. Undergraduate. His main research interests include cloud computing and machine learning systems

Zhang Zili: born in 2000. Undergraduate. His main research interests include machine learning systems and cloud computing

Jia Yunshan: born in 1999. PhD candidate. Student member of CCF. Her main research interests include wireless networks and cloud computing
Received Date: May 29, 2023
Revised Date: July 20, 2023
Available Online: July 31, 2023

Graphical Abstract

Abstract

Abstract

Serverless computing is an emerging function-centric cloud computing paradigm. It exposes a high-level function abstraction for users to write and deploy applications on cloud computing platforms. Serverless computing allocates resources based on the granulation of functions. Function scheduling is critical to function performance. It faces two difficulties, which are large problem space and high dynamism. Existing schedulers for serverless computing use a first-come-first-serve (FCFS) algorithm, which has head-of-line blocking and results in long function completion time. In order to highly utilize system resources and reduce function completion time, it is important to study the problem of function scheduling in serverless computing. First, we analyze the problem of function scheduling in serverless computing, and identify two factors that affect function completion time, which are queueing time, start time and execution time. Based on the analysis, we propose a mathematical model to formalize the problem of function scheduling in serverless computing. Second, we propose a scheduling algorithm, called FuncSched, based on temporal-spatial characterstics for serverless computing. The algorithm considers function execution time and function start time in the time dimension, and function resource consumption in the space dimension. Finally, we implement a system prototype, and evaluate it with real-world serverless computing workload datasets. Experimental results show that the proposed algorithm can effectively reduce average function completion time, thus effectively improving function execution efficiency in serverless computing.
- serverless computing,
- function scheduling,
- temporal-spatial characteristics,
- cold start,
- cloud computing

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References (43)

References

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