Distributed Monitoring of Topological Events via Homology
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Topological event detection allows for the distributed computation of homology by focusing on local changes occurring in a network over time. In this paper, a model for the monitoring of topological events in dynamically changing regions will be developed. Regions are approximated as the connected components of the communication graph of a sensor network, reducing homology computation to graph homology. Betti number differences together with cyclic neighbor-rings are used to categorize topological event types. The focus lies on the correct detection of non-incremental (i.e., multiple concurrently occurring) events and the necessary region update process. Network number differences between a network's state before and after events are spread from event nodes into network regions, allowing for the conflict-free updating of regions independent of the update messages' order of arrival.
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