Markovian Arrival Process Parameter Estimation With Group Data

Okamura, Hiroyuki; Dohi, Tadashi; Trivedi, Kishor S.

doi:10.1109/tnet.2008.2008750

Cited by 75 publications

(27 citation statements)

References 26 publications

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“…In particular, works on Markov model estimation can be found in [18,33]. Parameter fitting of a MAP -in terms of number of states, D 0 and D 1 -from a sample trace has been extensively studied, and methods to improve the parameter fitting in terms of accuracy and algorithm complexity order the are still being investigated [34,35,33,36].…”

Section: Discussionmentioning

confidence: 99%

“…where α ii = D 1; ii + 4 j=1,j =i D 0; ij MMPPs models are simpler than generic MAPs, but they can still model the variability on the inter-arrival time of events as well as some of the important correlations between inter-arrival times [37]. The problem of parameter fitting of a MMPP from a trace has been investigated in the literature [34,38,37,39,40]. In this work, we do not propose any new method to fit a workload trace into a MMPP but we use/rely-on methods already proposed in the literature.…”

Section: Markov-modulated Poisson Processmentioning

confidence: 99%

See 1 more Smart Citation

QoS and energy management with Petri nets: A self-adaptive framework

Pérez-Palacín

Mirandola

Merseguer

2012

Journal of Systems and Software

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Energy use is becoming a key design consideration in computing infrastructures and services. In this paper we focus on service-based applications and we propose an adaptation framework that can be used to reduce power consumption according to the observed workload. The adaptation guarantees a trade-off between energy consumption and system performance. The approach is based on the principle of proportional energy consumption obtained by scaling down energy for unused resources, considering both the number of servers switched on and their operating frequencies. Stochastic Petri Nets are proposed for the modeling of the framework concerns, their analyses give results about the trade-offs. The application of the approach to a simple case study shows its usefulness and practical applicability. Finally, different types of workloads are analyzed with validation purposes.

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Section: Discussionmentioning

confidence: 99%

Section: Markov-modulated Poisson Processmentioning

confidence: 99%

QoS and energy management with Petri nets: A self-adaptive framework

Pérez-Palacín

Mirandola

Merseguer

2012

Journal of Systems and Software

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“…Nogueira et al [11] offered a new perspective on empirical approach utilizing Markov concepts, a subgroup of Markov Arrival Processes (MAP) called Markov Modulated Poisson Process (MMPP) producing a hyper-exponentially distributed random variable. The problem of parameterizing MMPP models was addressed eg in [11][12][13][14].…”

Section: Related Workmentioning

confidence: 99%

VQ-based model for binary error process

Csoka

Polec

Csoka

et al. 2017

Journal of Electrical Engineering

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A variety of complex techniques, such as forward error correction (FEC), automatic repeat request (ARQ), hybrid ARQ or cross-layer optimization, require in their design and optimization phase a realistic model of binary error process present in a specific digital channel. Past and more recent modeling approaches focus on capturing one or more stochastic characteristics with precision sufficient for the desired model application, thereby applying concepts and methods severely limiting the model applicability (eg in the form of modeled process prerequisite expectations). The proposed novel concept utilizing a Vector Quantization (VQ)-based approach to binary process modeling offers a viable alternative capable of superior modeling of most commonly observed small-and large-scale stochastic characteristics of a binary error process on the digital channel. Precision of the proposed model was verified using multiple statistical distances against the data captured in a wireless sensor network logical channel trace. Furthermore, the Pearson's goodness of fit test of all model variants' output was performed to conclusively demonstrate usability of the model for realistic captured binary error process. Finally, the presented results prove the proposed model applicability and its ability to far surpass the capabilities of the reference Elliot's model. K e y w o r d s: binary error; VQ, wireless channel, logical channel, error model, wireless sensor network

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“…mapfit [47,62] is a package of R for PH/MAP fitting, which is distributed by CRAN. This package provides the fast EM algorithms for PH/MAP [61,66] and PH/MAP fitting with grouped data [65,67].…”

Section: Toolsmentioning

confidence: 99%

Ph Fitting Algorithm and Its Application to Reliability Engineering

Okamura

2016

JORSJ

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This article presents parameter estimation of phase-type (PH) distribution. PH distribution is widely used in model-based performance evaluation such as reliability and queueing system, and is defied by an absorbing continuous-time Markov chain (CTMC). Since non-Markovian model can be approximated by a CTMC by replacing general distributions with PH distributions, the parameter estimation is a challenging issue in stochastic modeling. We focus on the statistical inference algorithms to estimate not only the parameters of PH distribution with grouped, truncated and missing data but also the probability density function, and give two examples of PH fitting in reliability engineering.

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Markovian Arrival Process Parameter Estimation With Group Data

Cited by 75 publications

References 26 publications

QoS and energy management with Petri nets: A self-adaptive framework

QoS and energy management with Petri nets: A self-adaptive framework

VQ-based model for binary error process

Ph Fitting Algorithm and Its Application to Reliability Engineering

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