Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (9): 124-135.doi: 10.11896/jsjkx.260100146

• Database & Big Data & Data Science • Previous Articles     Next Articles

Consensus Protocol Framework of Distributed Time-series Database for Internet of Things Scenarios

GU Xinhao1, XU Jingyi2, LI Yongjin2, ZHAO Xinyi3, QIAO Jialin3   

  1. 1 School of Software,Tsinghua University,Beijing 100084,China
    2 Advanced Institute of Big Data,Beijing 100085,China
    3 Timecho Technology(Beijing) Co.,Ltd.,Beijing 100085,China
  • Received:2026-01-25 Revised:2026-04-30 Online:2026-09-15 Published:2026-09-10
  • About author:GU Xinhao,born in 2001,Ph.D candidate,is a member of CCF(No.J8265G).His main research interests include distributed system and machine learning system.
    ZHAO Xinyi,born in 1993,master.Her main research interest is time series management.
  • Supported by:
    National Key Research and Development Program of China(SQ2024YFB3300117),Project of National Key Laboratory(231-HF-D01-01) and Open Research Project of Key Laboratory of Meteorological Software,China Meteorological Administration(KLMS-OK-202506).

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Abstract: With the rapid development of the Internet of Things(IoT),device status monitoring data is becoming increasingly va-luable.This data primarily includes static attribute information,which does not change over time,and dynamic time-series data,which varies with time.These two types of data exhibit significant differences in read/write workloads and value density.Traditional distributed time-series databases typically employ a single consensus protocol to manage all data,which limits overall system performance by failing to adequately consider the distinct characteristics and value of different data types.To address this issue,this paper proposes a distributed consensus protocol framework for heterogeneous IoT data.This framework offers diverse consensus protocol options through module decoupling and standardized interface definitions,allowing for the integration of different consensus protocols based on various application scenarios and specific data types.Specifically,the framework enables the system to configure strong consistency consensus protocols for high-value,low-fault-tolerance static attribute information,ensuring its accuracy and reliability.Simultaneously,it allows for the configuration of weak consistency consensus protocols for large-volume,low-conflict dynamic time-series data to enhance write performance.To validate the flexibility and universality of this framework,it is implemented based on the open-source distributed time-series database Apache IoTDB and evaluated its differentiated performance with various consensus protocol implementations.By integrating appropriate consensus protocols,the framework improves the write throughput of the IoTDB cluster by 2.5 times,effectively meeting the diverse consensus protocol requirements of heterogeneous IoT data.This research enhances the flexibility and adaptability of distributed time-series databases in handling heterogeneous IoT data,provides customized consensus guarantees for data of different values,and offers a reliable platform for comparing different consensus protocols,thus holding significant theoretical importance and practical value.

Key words: Internet of Things, Time-series database, Consensus protocol, Unified framework, Configurable consistency, Heterogeneous data

CLC Number: 

  • TP311
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