Data acquisition and data fusion systems are becoming increasingly complex, being in fact systems of systems, where
every component may be a system with varying levels of autonomy by themselves. Possible changes in system
configuration by entities joining or being removed from the system make the system complex. As synchronous operation
cannot be expected in such a system configuration, the temporal and spatial correctness of data must be achieved via
This paper presents the concept of mediated interactions as a method for ensuring correctness of computation in a
distributed system. The mediator associated with each computing entity is responsible for online checking of the data
both before it is sent out at the sender side and before it is received at the receiver side, ensuring that only data satisfying
the validity constraints of the receiver-side data processing algorithm is used in computation. This assumes that each data
item is augmented with metadata, which enables online data validation. The validity and quality dimensions in use
depend on the system requirements defined by a specific problem and situational context; they may be temporal, spatial
and involve various data quality dimensions, such as accuracy, confidence, relevance, credibility, and reliability. Among
other capabilities, the mediator is able to cope with the unknowns in the temporal dimension that occur at runtime and
are not predictable, such as channel delay, jitter of clocks and processing delays. This capability becomes an especially
relevant factor in multi-tasking systems and in configurations in which a computing entity may have to process a variable
number of parallel streams of data.
Both the architecture and a simulation case study of a distributed data fusion scenario are presented in the paper.