Real-time transaction scheduling: a cost conscious approach
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Economic models for allocating resources in computer systems
Market-based control
On-line warehouse view maintenance
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
How to roll a join: asynchronous incremental view maintenance
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
An economic paradigm for query processing and data migration in mariposa
PDIS '94 Proceedings of the third international conference on on Parallel and distributed information systems
Active data warehouses: complementing OLAP with analysis rules
Data & Knowledge Engineering - Data warehousing
Value-based scheduling in real-time database systems
The VLDB Journal — The International Journal on Very Large Data Bases
A Transactional Model for Data Warehouse Maintenance
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Concurrent Warehouse Maintenance Without Compromising Session Consistency
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
A QoS-Sensitive Approach for Timeliness and Freshness Guarantees in Real-Time Databases
ECRTS '02 Proceedings of the 14th Euromicro Conference on Real-Time Systems
MTCache: Transparent Mid-Tier Database Caching in SQL Server
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Detection and Correction of Conflicting Source Updates for View Maintenance
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Relaxed currency and consistency: how to say "good enough" in SQL
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Managing Deadline Miss Ratio and Sensor Data Freshness in Real-Time Databases
IEEE Transactions on Knowledge and Data Engineering
UNIT: User-centric Transaction Management in Web-Database Systems
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Optimistic Coarse-Grained Cache Semantics for Data Marts
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Lottery scheduling: flexible proportional-share resource management
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Lazy maintenance of materialized views
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Journal of Artificial Intelligence Research
Hi-index | 0.00 |
The demand for so-called living or real-time data warehouses is increasing in many application areas such as manufacturing, event monitoring and telecommunications. In these fields, users normally expect short response times for their queries and high freshness for the requested data. However, meeting these fundamental requirements is challenging due to the high loads and the continuous flow of write-only updates and read-only queries that might be in conflict with each other. Therefore, we present the concept of workload balancing by election (WINE), which allows users to express their individual demands on the quality of service and the quality of data, respectively. WINE exploits these information to balance and prioritize both types of transactions-queries and updates-according to the varying user needs. A simulation study shows that our proposed algorithm outperforms competing baseline algorithms over the entire spectrum of workloads and user requirements.