Priority management for concurrent execution of real-time and on-line transactions

This paper presents priority management methods for concurrent execution of real-time transactions with timing constraints and on-line transactions without timing constraints in a real-time database system (RTDBS). The aim of this study is the meeting of deadlines of real-time transactions and shortening the response time of on-line transactions at the same time. The proposed methods are Simple Mix, Biased Mix, and Balanced Mix, each of which differs in its strategy for assigning priorities to on-line transactions. Simulation results show that Balanced Mix, which determines priorities dynamically according to the slack of real-time transactions, can shorten the response time of on-line transactions while keeping the deadline-missing ratio of real-time transactions low.

[1]  Hector Garcia-Molina,et al.  Scheduling real-time transactions , 1988, SGMD.

[2]  Donald F. Towsley,et al.  Experimental evaluation of real-time transaction processing , 1989, [1989] Proceedings. Real-Time Systems Symposium.

[3]  Sang Hyuk Son,et al.  Real-Time Database Scheduling: Design, Implementation, and Performance Evaluation , 1991, DASFAA.

[4]  Jaideep Srivastava,et al.  Processor scheduling and concurrency control in real-time main memory databases , 1991, [Proceedings] 1991 Symposium on Applied Computing.

[5]  Hector Garcia-Molina,et al.  Scheduling real-time transactions: a performance evaluation , 1988, TODS.

[6]  Miron Livny,et al.  Earliest deadline scheduling for real-time database systems , 1991, [1991] Proceedings Twelfth Real-Time Systems Symposium.

[7]  John A. Stankovic,et al.  On real-time transactions , 1988, SGMD.

[8]  Sang Hyuk Son,et al.  Approaches to Design of Real-Time Database Systems , 1989, DASFAA.

[9]  John T. Robinson,et al.  Limitations of concurrency in transaction processing , 1985, TODS.

[10]  Alexander Thomasian,et al.  Wait depth limited concurrency control , 1991, [1991] Proceedings. Seventh International Conference on Data Engineering.