The usage of mobile devices like cell phones, navigation systems, or laptop computers, is limited by the lifetime of the included batteries. This lifetimes depends naturally on the rate at which energy is consumed, however, it also depends on the usage pattern of the battery. Continuous drawing of a high current results in an excessive drop of residual capacity. However, during intervals with n...

Randomization is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well-controlled computation error and ability to specify the computation error in advance. However, the fact that the method can be computationally expensive limits its applicability. Recently, a variant of the (standard) randomizatio...

The mission time analysis of large dependable systems that can be described by Markov Reward Models (MRM) with phase type distributed impulse and constant rate rewards is considered in the paper. A single Laplace transform domain description of the distribution of completion time is provided through a new analysis approach. Based on this description an effective numerical method is introduced w...

We describe the use of stochastic Petri nets (SPNs) and stochastic reward nets (SRNs) which are SPNs augmented with the ability to specify output measures as reward-based functions, for the evaluation of reliability for complex systems. The solution of SRNs involves generation and analysis of the corresponding Markov reward model. The use of SRNs in modeling complex systems is illustrated throu...

Analysis of Markov Reward Models (MRM) with preemptive resume (prs) policy usually results in a double transform expression, whose solution is based on the inverse transformations both in time and reward variable domain. This paper discusses the case when the reward rates can be either 0 or a positive value c. These systems are called on-o MRMs. We analyze the completion time of on-o MRMs and p...

This paper is a sequel to Kurano et al [9], [10], in which the fuzzy perceptive models for optimal stopping or discounted Markov decision process is given. We proposed a method of computing the corresponding fuzzy perceptive values. Here, we deal with the average case for Markov decision processes with fuzzy perceptive transition matrices and characterize the optimal average expected reward, ca...

This paper is a sequel to Kurano et al [9], [10], in which the fuzzy perceptive models for optimal stopping or discounted Markov decision process are proposed and the methods of computing the corresponding fuzzy perceptive values are given. Here, we deal with the average case for Markov decisin processes with fuzzy perceptive transition matrices and characterize the optimal average expected rew...

Introduction Stochastic Petri net based Markov modeling is a potentially very powerful and generic approach for evaluating the performance and depend ability of many di erent systems such as computer systems communication networks manufacturing sys tems etc As a consequence of their general appli cability SPN based Markov models form the basic solution approach for several software packages tha...

We present an approach to reward maximiza-tion in a non-stationary mobile robot environment. The approach works within the realistic constraints of limited local sensing and limited a priori knowledge of the environment. It is based on the use of augmented Markov models (AMMs), a general modeling tool we have developed. AMMs are essentially Markov chains having additional statistics associated ...