A temporally oriented data model
ACM Transactions on Database Systems (TODS)
A homogeneous relational model and query languages for temporal databases
ACM Transactions on Database Systems (TODS)
Principles of distributed database systems
Principles of distributed database systems
An extended temporal system based on points and intervals
Information Systems
Modelling of user preferences and needs in Boolean retrieval systems
Information Processing and Management: an International Journal
Supporting valid-time indeterminacy
ACM Transactions on Database Systems (TODS)
Maintaining knowledge about temporal intervals
Communications of the ACM
AIMSA '00 Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Using Consensus Methods for Solving Conflicts of Data in Distributed Systems
SOFSEM '00 Proceedings of the 27th Conference on Current Trends in Theory and Practice of Informatics
Consensus-based Methods for Restoring Consistency of Replicated Data
Proceedings of the IIS'2000 Symposium on Intelligent Information Systems
Consensus system for solving conflicts in distributed systems
Information Sciences—Informatics and Computer Science: An International Journal
Deriving consensus for conflict data in web-based systems
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
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Up to now in the field of temporal database systems there have been investigated 3 kinds of time: valid time, transaction time and indeterminate valid time. Indeterminate valid time serves to describe the timestamps and possibility event occurrences in the future. In this paper the author assumes that in distributed temporal database systems it often happens that for the same event the sites may associate different scenarios in their fragments. Thus after making the union of these fragments there may exist such inconsistency that the proper scenario for the event is not known. The author proposes solving of this kind of uncertainty by developing a representation of the tuples representing the scenarios of this event. For this purpose a distance function between tuples referring to the same event is defined, and the representation choice functions are proposed and analyzed. Next an algorithm is worked out and some of its properties are given.