Comparison of Distributed Diagnosis Methods on Networks with Different Properties

We conduct a performance comparison between two algorithms for distributed diagnosis of discrete event systems. We are particularly interested in the time and memory requirements as the shape and size of the system are varied. To this end, we consider different classes of systems as can be found in the complex network literature [3]. We analyse and compare how certain properties of the network affect the performance of the two diagnosers. Valuable insight is gained into how network characteristics affect diagnostic performance and allows us to choose appropriate strategies for electricity networks, which are our motivating application.