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Computing cumulative measures of stiff Markov chains using aggregation

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2 Author(s)
Bobbio, A. ; Dept. of Comput. Sci., Duke Univ., Durham, NC, USA ; Trivedi, T.

An aggregation method for computing transient cumulative measures of large, stiff Markov models is presented. The method is based on classifying the states of the original problem into slow, fast-transient, and fast-current states. The authors aggregate fast-transient states and fast-recurrent states so that an approximate value to the desired cumulative measure can be obtained by solving a nonstiff set of linear differential equations defined over a reduced subset of slow states only. Several examples are included to illustrate how stiffness arises naturally in actual queuing and reliability models, and to show that cumulative measures provide a better characterization of the time-dependent system behavior

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Computers, IEEE Transactions on  (Volume:39 ,  Issue: 10 )