基于大数据HDFS改进的心跳模型

Improved Heartbeat Model Based on Hadoop Distributed File System of Big Data

分布式文件存储可有效缓解庞大数据对传统文件存储方式以及数据挖掘带来的压力,而心跳机制则是保证分布式文件存储主节点与子节点之间通信、正常运行的关键部分。针对传统心跳机制无法快速判断网络拥堵与宕机两种连接状态的问题,提出了一种子节点互联通信的改进心跳模型,旨在通过多子节点互相监控降低主节点误判率。通过仿真验证,该心跳模型减少了分布式存储系统在网络繁忙情况下对于两种通信状态的误判,提高了数据通信处理速度,同时增强了系统通信的可靠性。

Distributed file storage can effectively relieve the pressure of huge data on traditional file storage and data mining. Heartbeat mechanism isa key part to ensure the communication and operation of distributed file storage between primary and secondary nodes. Aiming at the problem that the traditional heartbeat mechanism can not quickly determine the connection state of network congestion and downtime, an improved heartbeat model of sub node interconnection communication is proposed, which aims to reduce the false positive rate of the master node by monitoring each other with sub nodes. Through the simulation of stand-alone model, this model reduces the misjudgment between the two communication states in distributed storage system to a certain extent, improves the data communication processing speed and enhances the reliability of system communication.