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Providing Persistence for Sensor Data Streams by Remote WAL

机译:通过远程WAL提供传感器数据流的持久性

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Rapidly changing environments such as robots, sensor networks, or medical services are emerging. To deal with them, DBMS should persist sensor data streams instantaneously. To achieve the purpose, data persisting process must be accelerated. Though write ahead logging (WAL) acceleration is essential for the purpose, only a few researches are conducted. To accelerate data persisting process, this paper proposes remote WAL with asynchronous checkpointing technique. Furthermore this paper designs and implements it. To evaluate the technique, this paper conducts experiments on an object relational DBMS called KRAFT. The result of experiments shows that remote WAL overwhelms performance disk based WAL. As for throughput evaluation, best policy shows about 12 times better performance compared with disk based WAL. As for logging time, the policy shows lower than 1000 micro seconds which is the period of motor data acquisition on conventional robots.
机译:迅速改变机器人,传感器网络或医疗服务等环境正在出现。要处理它们,DBMS应立即持续到传感器数据流。为了达到目的,必须加速数据持久性进程。虽然写入登录(WAL)加速至关重要,但仅进行了一些研究。为了加速数据持久性过程,本文提出了具有异步检查点技术的远程WAL。此外,本文设计并实现它。为了评估该技术,本文对称为牛皮纸的物体关系DBM进行进行实验。实验结果表明,远程WAL压倒性磁盘的WAL。对于吞吐量评估,与基于磁盘的WAL相比,最佳策略显示了更好的性能更好。对于伐木时间,策略显示低于1000微秒,这是传统机器人上的电机数据采集时段。

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