Economic models for allocating resources in computer systems
Market-based control
Value-based scheduling in real-time database systems
The VLDB Journal — The International Journal on Very Large Data Bases
An Economic Paradigm for Query Processing and Data Migration in Mariposa
PDIS '94 Proceedings of the Third International Conference on Parallel and Distributed Information Systems
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
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
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
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Cardinality estimation in ETL processes
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Requirement-based query and update scheduling in real-time data warehouses
WAIM'11 Proceedings of the 12th international conference on Web-age information management
E-ETL: framework for managing evolving etl processes
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
HYBRIDJOIN for Near-Real-Time Data Warehousing
International Journal of Data Warehousing and Mining
Scheduling strategies for efficient ETL execution
Information Systems
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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 usually 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, which may 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 applies this information to balance and prioritize over both types of transactions -- queries and update -- according to the varying user needs. A simulation study shows that our proposed algorithm outperforms competitor baseline algorithms over the entire spectrum of workloads and user requirements.