A Hybrid Distributed Centralized System Structure for Transaction Processing

A hybrid system structure comprised of distributed systems to take advantage of locality of reference and a central system to handle transactions that access non-local data is examined. Several transaction processing applications, such as reservation systems, insurance and banking have such regional locality of reference. A concurrency and coherency control protocol that maintains the integrity of the data and performs well for transactions that access local or non-local data is described. It is shown that the performance of the hybrid system is much less sensitive to the fraction of remote accesses than the distributed system and offers similar performance to the distributed system for local transactions. >

[1]  Y. C. Tay,et al.  A mean value performance model for locking in databases: the waiting case , 1984, PODS '84.

[2]  Len Bos,et al.  A model of transaction blocking in databases , 1983, Perform. Evaluation.

[3]  Jim Gray,et al.  An approach to decentralized computer systems , 1986, IEEE Transactions on Software Engineering.

[4]  Erol Gelenbe,et al.  Optimization of the Number of Copies in a Distributed Data Base , 1981, IEEE Trans. Software Eng..

[5]  Donald F. Towsley,et al.  Modeling the effects of data and resource contention on the performance of optimistic concurrency control protocols , 1988, Proceedings. Fourth International Conference on Data Engineering.

[6]  Philip S. Yu,et al.  Modelling of centralized concurrency control in a multi-system environment , 1985, SIGMETRICS '85.

[7]  Debasis Mitra,et al.  Probabilistic Models of Database Locking: Solutions, Computational Algorithms, and Asymptotics , 1984, JACM.

[8]  Peter P. Uhrowczik,et al.  IMS/VS: An Evolving System , 1982, IBM Syst. J..

[9]  Philip S. Yu,et al.  Performance Comparison of IO Shipping and Database Call Shipping: Schemes in Multisystem Partitioned Databases , 1989, Perform. Evaluation.

[10]  Keki B. Irani,et al.  Queueing network models for concurrent transaction processing in a database system , 1979, SIGMOD '79.

[11]  Hector Garcia-Molina,et al.  How Expensive is Data Replication? An Example , 1982, ICDCS.

[12]  J. T. Robinson,et al.  On coupling multi-systems through data sharing , 1987, Proceedings of the IEEE.

[13]  Philip S. Yu,et al.  Tradeoffs Between Coupling Small and Large Processors for Transaction Processing , 1988, IEEE Trans. Computers.

[14]  Randolph D. Nelson,et al.  Analysis of a Replicated Data Base , 1985, Perform. Evaluation.

[15]  Philip S. Yu,et al.  Load sharing in hybrid distributed-centralized database systems , 1988, [1988] Proceedings. The 8th International Conference on Distributed.

[16]  James A. Larson,et al.  Tutorial--Distributed Database Management , 1985 .

[17]  Miron Livny,et al.  Distributed Concurrency Control Performance: A Study of Algorithms, Distribution, and Replication , 1988, VLDB.

[18]  James A. Larson,et al.  Distributed Database Management , 1985 .

[19]  Dean Daniels,et al.  R*: An Overview of the Architecture , 1986, JCDKB.

[20]  C. J. Date An Introduction to Database Systems , 1975 .

[21]  Philip S. Yu,et al.  On multisystem coupling through function request shipping , 1986, IEEE Transactions on Software Engineering.

[22]  Philip S. Yu,et al.  On Centralized versus Geographically Distributed Database Systems , 1987, IEEE International Conference on Distributed Computing Systems.

[23]  Dominique Potier,et al.  Analysis of locking policies in database management systems , 1980, CACM.