We consider a continuous-time, inhomogeneous Markov chain M taking values in {0, 1} n . Processes of this type arise in finance as models of correlated default timing in a portfolio of firms, in reliability as models of failure timing in a system of interdependent components, and in many other areas. We develop a logarithmically efficient importance sampling scheme for estimating the tail of the distribution of the total transition count of M at a fixed time horizon.

Sensor and actor population within future smart distribution grids is much denser than within transmission grids. Thereby, future grid management systems have to cope with larger amounts of data than today's grid management systems. Also, future high-level applications for network management must be suited for use within automatic control loops. This results in new challenges for designing high-level application components for power grid management. This paper addresses related software engineering challenges and presents solutions for designing software within the context of grid management.

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