Maintaining data consistency using timestamp ordering in real-time broadcast environments

Broadcast-based data dissemination in wireless environments poses new challenging issues on data consistency of transaction processing. In this paper, we first adapt the optimistic concurrency control with forward validation to the broadcast environments. The adapted protocol gives autonomy between the mobile clients and the server such that the mobile clients can read consistent data off the air without contacting the server. However, it suffers from excessive transaction restart that affects the timeliness of mobile transactions. Therefore, we propose a new protocol based on timestamp ordering that can show significant performance improvement. The timestamp ordering technique enjoys a number of benefits from flexible adjustment of serialization order by exploiting the semantics of read-only transactions, which comprise most of the existing applications. The simulation results confirmed that the proposed protocol could be an efficient and effective approach to transaction processing in real-time broadcast environments for meeting transaction deadlines.

[1]  Bharat K. Bhargava,et al.  Building information systems for mobile environments , 1994, CIKM '94.

[2]  Krithi Ramamritham,et al.  Efficient concurrency control for broadcast environments , 1999, SIGMOD '99.

[3]  Sang Hyuk Son,et al.  Using dynamic adjustment of serialization order for real-time database systems , 1993, 1993 Proceedings Real-Time Systems Symposium.

[4]  S. Zdonik,et al.  Are "disks in the air" just pie in the sky? , 1994, Workshop on Mobile Computing Systems and Applications.

[5]  Tomasz Imielinski,et al.  Mobile wireless computing: challenges in data management , 1994, CACM.

[6]  Miron Livny,et al.  On being optimistic about real-time constraints , 1990, PODS '90.

[7]  Jiandong Huang Real-time transaction processing: design, implementation, and performance evaluation , 1991 .

[8]  Tomasz Imielinski,et al.  Sleepers and workaholics: caching strategies in mobile environments , 1994, SIGMOD '94.

[9]  Hector Garcia-Molina,et al.  Read-only transactions in a distributed database , 1982, TODS.

[10]  Jitendra Padhye,et al.  Transaction Processing in Broadcast Disk Environments , 1997, Advanced Transaction Models and Architectures.

[11]  Evaggelia Pitoura Supporting read-only transactions in wireless broadcasting , 1998, Proceedings Ninth International Workshop on Database and Expert Systems Applications (Cat. No.98EX130).

[12]  Evaggelia Pitoura,et al.  Scalable processing of read-only transactions in broadcast push , 1999, Proceedings. 19th IEEE International Conference on Distributed Computing Systems (Cat. No.99CB37003).

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

[14]  Tei-Wei Kuo,et al.  Load adjustment in adaptive real-time systems , 1991, [1991] Proceedings Twelfth Real-Time Systems Symposium.

[15]  Gita Gopal,et al.  The Architecture , 2022 .

[16]  Miron Livny,et al.  Dynamic real-time optimistic concurrency control , 1990, [1990] Proceedings 11th Real-Time Systems Symposium.

[17]  Rafael Alonso,et al.  Database system issues in nomadic computing , 1993, SIGMOD Conference.

[18]  Abdelsalam Helal,et al.  A mobile transaction model that captures both the data and movement behavior , 1997, Mob. Networks Appl..

[19]  Gita Gopal,et al.  The datacycle architecture for very high throughput database systems , 1987, SIGMOD '87.

[20]  Victor C. S. Lee,et al.  Transaction processing in wireless distributed real-time databases , 1998, Proceeding. 10th EUROMICRO Workshop on Real-Time Systems (Cat. No.98EX168).

[21]  Rafael Alonso,et al.  Broadcast Disks: Data Management for Asymmetric Communication Environments , 1994, Mobidata.

[22]  Jörgen Hansson,et al.  Misconceptions About Real-Time Databases , 1999, Computer.