A genetic approach to Markovian characterisation of H.264 scalable video

We propose an algorithm for multivariate Markovian characterisation of H.264/SVC scalable video traces at the sub-GoP (Group of Pictures) level. A genetic algorithm yields Markov models with limited state space that accurately capture temporal and inter-layer correlation. Key to our approach is the covariance-based fitness function. In comparison with the classical Expectation Maximisation algorithm, ours is capable of matching the second order statistics more accurately at the cost of less accuracy in matching the histograms of the trace. Moreover, a simulation study shows that our approach outperforms Expectation Maximisation in predicting performance of video streaming in various networking scenarios

Quantifying the impact of daily and seasonal variation in sap pH on xylem dissolved inorganic carbon estimates in plum trees

In studies on internal CO2 transport, average xylem sap pH (pH(x)) is one of the factors used for calculation of the concentration of dissolved inorganic carbon in the xylem sap ([CO2*]). Lack of detailed pH(x) measurements at high temporal resolution could be a potential source of error when evaluating [CO2*] dynamics. In this experiment, we performed continuous measurements of CO2 concentration ([CO2]) and stem temperature (T-stem), complemented with pH(x) measurements at 30-min intervals during the day at various stages of the growing season (Day of the Year (DOY): 86 (late winter), 128 (mid-spring) and 155 (early summer)) on a plum tree (Prunus domestica L. cv. Reine Claude d'Oullins). We used the recorded pH(x) to calculate [CO2*] based on T-stem and the corresponding measured [CO2]. No statistically significant difference was found between mean [CO2*] calculated with instantaneous pH(x) and daily average pH(x). However, using an average pH(x) value from a different part of the growing season than the measurements of [CO2] and T-stem to estimate [CO2*] led to a statistically significant error. The error varied between 3.25 +/- 0.01% under-estimation and 3.97 * 0.01% over-estimation, relative to the true [CO2*] data. Measured pH(x) did not show a significant daily variation, unlike [CO2], which increased during the day and declined at night. As the growing season progressed, daily average [CO2] (3.4%, 5.3%, 7.4%) increased and average pH(x) (5.43, 5.29, 5.20) decreased. Increase in [CO2] will increase its solubility in xylem sap according to Henry's law, and the dissociation of [CO2*] will negatively affect pH(x). Our results are the first quantifying the error in [CO2*] due to the interaction between [CO2] and pH(x) on a seasonal time scale. We found significant changes in pH(x) across the growing season, but overall the effect on the calculation of [CO2*] remained within an error range of 4%. However, it is possible that the error could be more substantial for other tree species, particularly if pH(x) is in the more sensitive range (pHx > 6.5)

A batch-service queueing model with a discrete batch Markovian arrival process

Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of customers in system (system content) reaches or exceeds a threshold. Correlation is taken into account by assuming a discrete batch Markovian arrival process (D-BMAP), i.e. the distribution of the number of customer arrivals per slot depends on a background state which is determined by a first-order Markov chain. We deduce the probability generating function of the system content at random slot marks and we examine the influence of correlation in the arrival process on the behavior of the system. We show that correlation merely has a small impact on the threshold that minimizes the mean system content. In addition, we demonstrate that correlation might have a significant influence on the system content and therefore has to be included in the model

Study of Queueing Behaviour in IP Buffers

It is unquestioned that the importance of IP network will further increase and that it will serve as a platform for more and more services, requiring different types and degrees of service quality. Modern architectures and protocols are being standardized, which aims at guaranteeing the quality of service delivered to users. In this paper, we investigate the queueing behaviour found in IP output buffers. This queueing increases because multiple streams of packets with different length are being multiplexed together. We develop balance equations for the state of the system, from which we derive packet loss and delay results. To analyze these types of behaviour, we study the discrete-time version of the “classical” queue model M/M/1/k called Geo/Gx/1/k, where Gx denotes a different packet length distribution defined on a range between a minimum and maximum value

The NxD-BMAP/G/1 queueing model : queue contents and delay analysis

We consider a single-server discrete-time queueing system with N sources, where each source is modelled as a correlated Markovian customer arrival process, and the customer service times are generally distributed. We focus on the analysis of the number of customers in the queue, the amount of work in the queue, and the customer delay. For each of these quantities, we will derive an expression for their steady-state probability generating function, and from these results, we derive closed-form expressions for key performance measures such as their mean value, variance, and tail distribution. A lot of emphasis is put on finding closed-form expressions for these quantities that reduce all numerical calculations to an absolute minimum

Determining milk isolated and conjugated trans-unsaturated fatty acids using Fourier transform Raman spectroscopy

The feasibility of Raman spectroscopy in combination with partial least-squares (PLS) regression for the determination of individual or grouped trans-monounsaturated fatty acids (trans-MUFA) and conjugated linoleic acids (CLA) in milk fat is demonstrated using spectra obtained at two temperature conditions: room, temperature and after freezing at -80 degrees C. The PLS results displayed capability for direct semiroutine quantification of several individual CLA (cis-9,trans-11 and trans-10,cis-12 C18:2) and trans-MUFA (trans-4-15 C18:1) in minor concentrations (below 1.0 g/100 g of milk fat). Calibration models were based on reference data cross-correlation or determined by specific scattering signals in the Raman spectra. Distinct bands for trans-MUFA (1674 cm(-1)) and CLA (1653 cm(-1)) from the trans isolated and cis,trans conjugated C=C bonds were identified, as well as original evidence for the temperature effect (new bands, peak shifts, and higher intensities) on the Raman spectra of fatty acid methyl ester and triacylglyceride standards, are supplied

Matrix-geometric solutions of M/G/1-type Markov chains: A unifying generalized state-space approach

In this paper, we present an algorithmic approach to find the stationary probability distribution of M/G/1-type Markov chains which arise frequently in performance analysis of computer and communication networ ks. The approach unifies finite- and infinite-level Markov chains of this type through a generalized state-space representation for the probability generating function of the stationary solution. When the underlying probability generating matrices are rational, the solution vector for level k, x k, is shown to be in the matrix-geometric form x k+1 = gF k H, k ≥ 0, for the infinite-level case, whereas it takes the modified form x k+1 = g 1F 1 kH 1 + g 2F 2 K-k-1 H 2, 0 ≤ k < K, for the finite-level case. The matrix parameters in the above two expressions can be obtained by decomposing the generalized system into forward and backward subsystems, or, equivalently, by finding bases for certain generalized invariant subspaces of a regular pencil λE - A. We note that the computation of such bases can efficiently be carried out using advanced numerical linear algebra techniques including matrix-sign function iterations with quadratic convergence rates or ordered generalized Schur decomposition. The simplicity of the matrix-geometric form of the solution allows one to obtain various performance measures of interest easily, e.g., overflow probabilities and the moments of the level distribution, which is a significant advantage over conventional recursive methods