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Temporal network analysis and time evolution of network characteristics arepowerful tools in describing the changing topology of dynamic networks. Thispaper uses such approaches to better visualize and provide analytical measuresfor the changes in performance that we observed in Voronoi-type spatialcoverage, particularly for the example of time evolving networks with achanging number of wireless sensors being deployed. Specifically, our analysisfocuses on the role different combinations of impenetrable obstacles andenvironmental noise play in connectivity and overall network structure. It isshown how the use of (i) temporal network graphs, and (ii) network centralityand regularity measures illustrate the differences between various optionsdeveloped for the balancing act of energy and time efficiency in networkcoverage. Lastly, we compare the outcome of these measures with the lessabstract classification variables, such as percent area covered, and cumulativedistance travelled.

Temporal Graphs and Temporal Network Characteristics for Bio-Inspired Networks During Optimization