SYBASE replication server primer
SYBASE replication server primer
Parallelism in relational data base systems: architectural issues and design approaches
DPDS '90 Proceedings of the second international symposium on Databases in parallel and distributed systems
A new approach to developing and implementing eager database replication protocols
ACM Transactions on Database Systems (TODS)
Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
A Scalable and Highly Available Networked Database Architecture
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Fast Algorithms for Maintaining Replica Consistency in Lazy Master Replicated Databases
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
Data placement in shared-nothing parallel database systems
The VLDB Journal — The International Journal on Very Large Data Bases
The failure and recovery problem for replicated databases
PODC '83 Proceedings of the second annual ACM symposium on Principles of distributed computing
Understanding Replication in Databases and Distributed Systems
ICDCS '00 Proceedings of the The 20th International Conference on Distributed Computing Systems ( ICDCS 2000)
Query Processing in a Device Database System
Query Processing in a Device Database System
Approximate Aggregation Techniques for Sensor Databases
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
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In sensor networks, a huge amount of data is collected by millions of sensors and small mobile devices need to be processed fast. And database which stores those data always should be able to response for any requirement. Spatial database cluster provides high performance and high availability. That suits sensor networks because spatial database cluster can efficiently manage and process much amount of data. The previous system, however, should write external logs every transaction for high availability in all nodes. So, all of update transactions are slowly processed because of writing external logs. Also, recovery time of the failed node is increased because external logs for all of database are written in only single storage. In this paper, we propose the cluster recovery of spatial database cluster. The proposed method has cluster logs in each table unit for consistency among nodes. Also, the cluster log is written just in case any node is failed. Therefore the proposed method is processed more fast because all update transactions don't write cluster logs. And the proposed method provides fast recovery because each table can be recovered concurrently.