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Channel reservation is used to decrease the drop ratio of secondary users caused by spectrum handover. This paper considers the maintainer of the reserved channels in one secondary system coexisting with multiple primary systems. The global channel reservation scheme, the user channel reservation scheme, and the user-updated channel reservation scheme are proposed, derived by different Markov models...
Wireless sensors have started being utilized for industrial application which is typical harsh environment due to complicated layout and plentiful stationary/moving obstacles. As two hot standards for wireless industrial, WiHART and ISA100.11a, both adopt the centralized wireless sensor network with mesh topology to enable the reliable monitoring of a variety of environments. This kind of network...
Discrete-Time Markov Chains (DTMCs) are a widely-used formalism to model probabilistic systems. On the one hand, available tools like PRISM or MRMC offer efficient model checking algorithms and thus support the verification of DTMCs. However, these algorithms do not provide any diagnostic information in the form of counterexamples, which are highly important for the correction of erroneous systems...
In recent years, the multi-dimensional risk model is a hot topic, and it is more realistic with the Markovian environment, which can be explained as the economic condition. In this paper, we propose the two-dimensional compound binomial model in a Markovian environment. And we obtain the explicit recursive formulae for three types of finite-time survival or ruin probabilities which are of fundamental...
Wireless networks equipped with CSMA are scheduled in a fully distributed manner. A disadvantage of such distributed control in multi-hop networks is the hidden node problem that causes the effect of stealing, in which a downstream node steals the channel from an upstream node with probability p. Aziz, Starobinski and Thiran have recently shown that the N-hop model with stealing is stable only in...
Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scant attention in this area, at least from the implementation perspective. This paper studies the problem of how to efficiently realize an algorithm for computing optimal long-run average reward values for concurrent probabilistic systems...
In this paper we develop a copula based approximation framework for scalable analysis of Stochastic Automata Networks (SAN) arising in reliability analysis, and can be described by CTMCs. Copulas provide a general approach to model joint distributions in terms of their marginals. Using copulas functions, the dependencies between the interacting automata in the SAN can be captured in terms of local...
We present a model-based environment for the probabilistic analysis of systems operating under uncertain conditions. This uncertainty may result from either the environments in which they operate or the platforms on which they execute. Available probabilistic analysis methods require to capture the system specification using languages that are semantically very close to Markov Chains. However, designers...
Graph representations of data have emerged as powerful tools in the classification of partially labeled data. We give a new algorithm for graph based semi supervised learning which is based on a probabilistic model of the process which assigns labels to vertices. The main novelty is a non parametric mixture of graph diffusions, which we combine with a Markov random field potential. Markov chain Monte...
In order to reduce quality loss of the production process, this paper proposed the optimization design of EWMA charts with variable sampling intervals (VSI). Using Rayleigh distribution to approximate to probability distribution of the random process mean shifts, we determined the parameters of the VSI EWMA charts such that the overall mean of Taguchi's loss function (ML) is minimized. The results...
In this paper, Network Coding (NC) Theory is introduced to improve efficiency of the traditional ARQ scheme for Cognitive Radio (CR) broadcast, named as NC-ARQ, in which we consider making the CR basestation combine the lost packets during ARQ broadcast retransmission in CR networks (CRN), with the changeable availability of CR channel. The Broadcast Cost is defined to indicate and compare the theoretic...
The exact Markov modeling analysis of erasure networks with finite buffers is an extremely hard problem due to the large number of states in the system. In such networks, packets are lost due to either link erasures or blocking by the full buffers. In this paper, we propose a novel method that iteratively estimates the performance parameters of the network and more importantly reduces the computational...
The idea of the future Internet of Services is to combine several services of numerous service providers to new value-added services or applications. To sell these services on so-called service marketplaces the providers have to ensure both a high quality and a high quality reliability. But how could a provider of a composed service know the quality-reliability of his service without costly tests?...
One characteristic of service is in its lower barrier to entry. Fierce competition is almost a norm among many service businesses. The key to successful customer relationship management embeds in the ability to acquire the customer, to retain the customer and make frequent customers. This research suggests a probabilistic analytic framework to firstly create the transition matrices for acquiring customer,...
We develop a replacement-repair model to study a renewing free replacement warranty (RFRW) for a class of multi-state deteriorating repairable products. Each product may experience N different working states with different hazard functions, before the warranty contract expires. Once the item enters working state j(j = 1, 2,..., N), it can either fail or move t any of the subsequent states. In the...
This paper deals with a new class of Markov Chain type models that can be effectively used for real time modeling and on-line learning of nonlinear systems with uncertainties. We expand the concept of the generalized Markov Chain - a probabilistic model that synergistically combines the idea of transition probabilities with the information granulation paradigm. We consider generalized Markov chains...
This article proposes a methodology on how to justify homogeneous Markov source information entropy based on Chapman-Kolmogorov equation. According to the ergodic theorem, a new proof methodology is proposed in this article, which is different from the basis on properties of information entropy.
Markov models are essential for modeling systems in safety and reliability calculations. Unfortunately, these models become exponentially more complex with an increasing number of components. This makes manual modeling time-consuming, complicated, and prone to error. This paper introduces a method to systematically and automatically generate Markov models. The system model is made up of components...
In order to fully utilize the scarce spectrum resources and improve the efficiency of wireless spectrum resource utilization, dynamic spectrum access is proposed as a solution. There are two kinds of dynamic spectrum access system, one is overlay dynamic spectrum, and the other is dynamic spectrum access under interference temperature constraints. In this paper, we use a three-dimensional Markov chain...
A finite buffer queue scheduling with polling and reservation strategy for the network node is designed. Because the delay sensitive service and the non-delay sensitive service need the different quality of service, they will gain the different services through scheduling transmission rate. A three-dimension Markov queue model is proposed to investigate the queue scheduling model in this paper. The...
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