Optimization: algorithms and consistent approximations
Optimization: algorithms and consistent approximations
Maintaining Temporal Consistency: Pessimistic vs. Optimistic Concurrency Control
IEEE Transactions on Knowledge and Data Engineering
Scheduling Transactions with Temporal Constraints: Exploiting Data Semantics
IEEE Transactions on Knowledge and Data Engineering
Maintaining Temporal Consistency of Discrete Objects in Soft Real-Time Database Systems
IEEE Transactions on Computers
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
Similarity-based load adjustment for real-time data-intensive applications
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
Statistical Rate Monotonic Scheduling
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Real-Time Primary-Backup (RTPB) Replication with Temporal Consistency Guarantees
ICDCS '98 Proceedings of the The 18th International Conference on Distributed Computing Systems
Slack Stealing Job Admission Control Scheduling
Slack Stealing Job Admission Control Scheduling
Deriving Deadlines and Periods for Real-Time Update Transactions
IEEE Transactions on Computers
Statistical Quality of Service Guarantee for Temporal Consistency of Real-Time Data Objects
RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
Journal of Systems and Software
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The More-Less (ML) scheme has been shown to be an efficient approach for maintaining temporal consistency of real-time data objects. Although ML provides a deterministic guarantee in temporal consistency, the number of update transactions that can be supported in a system is limited. This is due to its use of the worst-case computation time in deriving deadlines and periods of update transactions. This paper studies the problem of temporal consistency maintenance where a certain degree of temporal inconsistency is tolerable. A suite of Statistical More-Less (SML) approaches are proposed to explore the trade-off between quality of service (QoS) of temporal consistency and the number of supported transactions. It begins with a base-line algorithm, SML-BA, which provides the requested QoS of temporal consistency. Then, SML with Optimization (SML-OPT) is proposed to further improve the QoS by better utilizing the excess processor capacity. Finally, SML-OPT is enhanced with a Slack Reclaiming scheme (SML-SR). The reclaimed slacks are used to process jobs whose required computation time is larger than the guaranteed computation time. Simulation experiments are conducted to compare the performance of these schemes (SML-BA, SML-OPT, and SML-SR) together with the deterministic More-Less and Half-Half schemes. The results show that the SML schemes are effective in trading the schedulability of transactions for the QoS guaranteed. Moreover, SML-SR performs best and offers a significant QoS improvement over SML-BA and SML-OPT.