Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Transaction Processing: Concepts and Techniques
Transaction Processing: Concepts and Techniques
Repeating History Beyond ARIES
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The ClustRa Telecom Database: High Availability, High Throughput, and Real-Time Response
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Providing Persistence or Sensor Streams with Light Neighbor WAL
PRDC '02 Proceedings of the 2002 Pacific Rim International Symposium on Dependable Computing
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
P*TIME: highly scalable OLTP DBMS for managing update-intensive stream workload
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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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.