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FTLLS: A fault tolerant, low latency, distributed scheduling approach based on sparrow

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Abstract

Big data processing systems are developing towards larger degrees of parallelism and shorter task durations in order to achieve lower response time. Scheduling highly parallel tasks that complete in sub-seconds poses a great challenge to traditional centralized schedulers. Taking the challenge, researchers turn to distributed scheduling approaches to avoid the throughput limitation of centralized schedulers, among which Sparrow is a leading design. However, little effort is devoted to the fault tolerance of Sparrow and there are problems with Sparrow’s sample-based techniques, which gives rise to incomplete jobs and large scheduling latency. We then present Fault Tolerant, Low Latency Sparrow (FTLLS). It extends Sparrow with an assistant machine to handle worker failures and to make better scheduling decisions. Through simulations, it is proved that FTLLS can detect worker failures more quickly than a naive timeout approach and make better scheduling decisions than native Sparrow. Through implementation, the results show that FTLLS guarantees no incomplete jobs at the presence of worker failures and reduces scheduling latencies by over 1.5 × when compared to native Sparrow. In addition, the simplicity of the idea adopted by FTLLS makes it applicable to a wide variety of distributed scheduling approaches.

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Acknowledgements

It is my first time to submit my paper to a journal and I gain a lot. The research is supported in part by Professor Lin for insightful guidance. Also I am indebted to Yin Li for helpful comments on several drafts of this paper and for help with simulations of our mechanism. They are enthusiastic to offer me help and suggestions when I encountered problems in this research, which keeps me improving. I wish to thank all my teachers and seniors in my research lab for providing such valuable suggestions.

This work was supported by the National Natural Science Foundation of China (No. 61472199); the National Basic Research Program of China (973 Program) under grants 2010CB328105; Tsinghua University Initiative Scientific Research Program (No.20121087999).

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Authors and Affiliations

  1. Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, 30 Shuangqing Rd, Haidian Qu, Beijing Shi, China

    Wenzhuo Li & Chuang Lin

  2. Department of Computer Science and Technology, Tsinghua University, 30 Shuangqing Rd, Haidian Qu, Beijing Shi, China

    Wenzhuo Li & Chuang Lin

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  1. Wenzhuo Li
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  2. Chuang Lin
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Correspondence to Wenzhuo Li.

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This article is part of the Topical Collection: Special Issue on Big Data Networking

Guest Editors: Xiaofei Liao, Song Guo, Deze Zeng, and Kun Wang

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Li, W., Lin, C. FTLLS: A fault tolerant, low latency, distributed scheduling approach based on sparrow. Peer-to-Peer Netw. Appl. 11, 1129–1140 (2018). https://doi.org/10.1007/s12083-017-0590-4

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