Abstract : Graphs change over time, and typically variations on the small multiples or animation pattern is used to convey this dynamism visually. However, both of these classical techniques have significant drawbacks, so a new approach, Storyline Visualization of Events on a Network (SVEN) is proposed. SVEN builds on storyline techniques, conveying nodes as contiguous lines over time. SVEN encodes time in a natural manner, along the horizontal axis, and optimizes the vertical placement of storylines to decrease clutter (line crossings, straightness, and bends) in the drawing. This paper demonstrates SVEN on several different flavors of real-world dynamic data, and outlines the remaining near-term future work.
To the author's knowledge, the earliest portrayal of events on a network with a spatial encoding of time are sequence diagrams,'' developed in the 1970s, which are used to understand timing and synchronization in distributed systems @cite_6 . These visualizations were originally hand drawn; nodes were represented as vertical parallel lines with time moving from the bottom to the top of the page. Communication events between processes were represented as wavy lines connecting connecting the processes sending and receiving the message at the local times the message was sent and received. Sequence diagrams are effective for understanding trivially small networks, but become difficult to scale up as more nodes are added. The ordering of nodes in the diagram can be chosen to minimize crossings, but this is the Traveling Salesman Problem, and even if an optimal solution was found, there is no guarantee that the resulting diagram would be interpretable for large or dense networks.
@cite_6
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The concept of one event happening before another in a distributed system is examined, and is shown to define a partial ordering of the events. A distributed algorithm is given for synchronizing a system of logical clocks which can be used to totally order the events. The use of the total ordering is illustrated with a method for solving synchronization problems. The algorithm is then specialized for synchronizing physical clocks, and a bound is derived on how far out of synchrony the clocks can become.