This paper proposes a time-interval data model in which all temporal representation and operations can be expressed with time intervals. The model expresses not only real time intervals, in which an event exists, but also null time intervals, in which an event is suspended. We model the history of a real-world event as a composite time interval, which is defined in this paper. Operations on the composite time intervals are also defined, and it is shown how these operations can be used to express temporal constraints with time intervals.

This paper describes a way of implementing a conceptual model for temporal data on a commercial object database system. The implemented version is provided as a class library. The library enables applications to handle temporal data. Any application can employ the library because it does not depend on specific applications. Furthermore, we propose an enhanced version of Time Index. The index efficiently processes event queries in particular. These queries search time intervals in which given events are all valid. We also investigate the effectiveness of the enhanced Time Index.

Data accessed by many sites are replicated in distributed environments for performance and availability. In this paper, replication schemes are examined in parallel image convolution processing. This paper presents a system architecture that we have developed with CORBA (Common Object Request Broker Architecture) for the processing. Employing CORBA enables us to make use of a cluster of workstations, each of which has a different level of computing power. The paper also describes a parallel and distributed image convolution processing model using replicas stored in a network of workstations, and reports some experimental results showing that our analytical model can agree with practical situations.