Aggregate Flow Rate Research Articles

Machine Learning-Based Link Fault Identification and Localization in Complex Networks

With the proliferation of network devices and rapid development in information technology, networks such as Internet of Things are increasing in size and becoming more complex with heterogeneous wired and wireless links. In such networks, link faults may result in a link disconnection without immediate replacement or a link reconnection, e.g., a wireless node changes its access point. Identifying whether a link disconnection or a link reconnection has occurred and localizing the failed link become a challenging problem. An active probing approach requires a long time to probe the network by sending signaling messages on different paths, thus incurring significant communication delay and overhead. In this paper, we adopt a passive approach and develop a three-stage machine learning-based technique, namely ML-LFIL that identifies and localizes link faults by analyzing the measurements captured from the normal traffic flows, including aggregate flow rate, end-to-end delay and packet loss. ML-LFIL learns the traffic behavior in normal working conditions and different link fault scenarios. We train the learning model using support vector machine, multi-layer perceptron and random forest. We implement ML-LFIL and carry out extensive experiments using Mininet platform. Performance studies show that ML-LFIL achieves high accuracy while requiring much lower fault localization time compared to the active probing approach.

Effect of Target Composition and Sputtering Deposition Parameters on the Functional Properties of Nitrogenized Ag-Permalloy Flexible Thin Films Deposited on Polymer Substrates.

We report the first results of functional properties of nitrogenized silver-permalloy thin films deposited on polyethylene terephthalic ester {PETE (C10H8O4)n} flexible substrates by magnetron sputtering. These new soft magnetic thin films have magnetization that is comparable to pure Ni81Fe19 permalloy films. Two target compositions (Ni76Fe19Ag5 and Ni72Fe18Ag10) were used to study the effect of compositional variation and sputtering parameters, including nitrogen flow rate on the phase evolution and surface properties. Aggregate flow rate and total pressure of Ar+N2 mixture was 60 sccm and 0.55 Pa, respectively. The distance between target and the substrate was kept at 100 mm, while using sputtering power from 100–130 W. Average film deposition rate was confirmed at around 2.05 nm/min for argon atmosphere and was reduced to 1.8 nm/min in reactive nitrogen atmosphere. X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, vibrating sample magnetometer, and contact angle measurements were used to characterize the functional properties. Nano sized character of films was confirmed by XRD and SEM. It is found that the grain size was reduced by the formation of nitride phase, which in turns enhanced the magnetization and lowers the coercivity. Magnetic field coupling efficiency limit was determined from 1.6–2 GHz frequency limit. The results of comparable magnetic performance, lowest magnetic loss, and highest surface free energy, confirming that 15 sccm nitrogen flow rate at 115 W is optimal for producing Ag-doped permalloy flexible thin films having excellent magnetic field coupling efficiency.

On utility‐optimised router‐level bandwidth allocation

ABSTRACTKelly's network utility maximisation (NUM) problems and solutions are aimed to maximise the aggregate utility subject to link capacity constraints. They are formulated and solved by using the individual flow rate vector. Because of the architecture of the current networks such as the Internet, the individual flow rates are generally not measurable directly at the routers for the network service provider. However, the aggregate flow rates are more convenient to obtain and to adjust. In this paper, we still study the NUM problems for communication networks but from a router‐level bandwidth allocation standpoint. With the use of the generalised matrix inverse, we propose a general model of utility‐optimised router‐level bandwidth allocation and its solution, where the objective function and the constraints are formulated in terms of the aggregate flow rate vector rather than from the individual flow rate vector as in the usual NUM problem. We find that the new proposed models are equivalent to Kelly's NUM model in the sense that they lead to the same optimum and their solutions satisfy the given routing scheme. We also discuss the special cases where the routing matrix is of full row rank and where there is one single‐hop flow in every link in the network. We suggest a direct application to Internet Protocol‐based virtual private network of the latter case. We present the mathematical models and solution procedures that lead to the utility‐optimised aggregate flow rate vector and further illustrate them by numerical examples. We believe our approach is promising for deployment in communication networks. Copyright © 2012 John Wiley & Sons, Ltd.

A non-equilibrium analysis and control framework for active queue management

We present a non-equilibrium analysis and control approach for the Active Queue Management (AQM) problem in communication networks. Using simplified fluid models, we carry out a bifurcation study of the complex dynamic queue behavior to show that non-equilibrium methods are essential for analysis and optimization in the AQM problem. We investigate an ergodic theoretic framework for stochastic modeling of the non-equilibrium behavior in deterministic models and use it to identify parameters of a fluid model from packet level simulations. For computational tractability, we use set-oriented numerical methods to construct finite-dimensional Markov models, including control Markov chains and hidden Markov models. Subsequently, we develop and analyze an example AQM algorithm using a Markov Decision Process (MDP) based control framework. The control scheme developed is optimal with respect to a reward function, defined over the queue size and aggregate flow rate. We implement and simulate our illustrative AQM algorithm in the ns-2 network simulator. The results obtained confirm the theoretical analysis and exhibit promising performance when compared with well-known alternative schemes under persistent non-equilibrium queue behavior.

Internet Congestion Control Subject to Node And Link Constraints

This paper studies the mathematical modelling of Internet congestion control. Differently to previous models, which consider either the link capacity or the node processing capability as the constraints, here we take both of them into account, i.e., the aggregate flow rate on a link cannot exceed the link capacity and the aggregate flow rate at a node is limited by the node processing capability. A decentralized primal-dual algorithm is proposed to solve the congestion control problem and its convergence is proven. Using this algorithm we show the bottleneck of the network performance when these two constraints are unbalanced.

A NON-EQUILIBRIUM ANALYSIS & CONTROL FRAMEWORK FOR COMMUNICATION NETWORKS

We present a non-equilibrium analysis and control approach for the Active Queue Management (AQM) problem in communication networks. Using simplified fluid models we carry out a bifurcation study of the complex dynamic queue behavior to show that non-equilibrium methods are essential for analysis and optimization in the AQM problem. We investigate an ergodic theoretic framework for stochastic modeling of the non-equilibrium behavior in deterministic models and use it to identify parameters of a fluid model from packet level simulations. For computational tractability, we use set-oriented numerical methods to construct finite-dimensional Markov models. Subsequently, we develop and analyze an example AQM algorithm using a Markov Decision Process (MDP) based control framework. The control scheme developed is optimal with respect to a reward function defined over the queue size and aggregate flow rate. We implement and simulate our illustrative AQM algorithm in the ns-2 network simulator. The initial results obtained confirm the theoretical analysis and exhibit promising performance when compared with well-known alternative schemes under persistent non-equilibrium queue behavior.

Local Stability of a New Adaptive Queue Management (AQM) Scheme

In this letter, we propose a new Adaptive Queue Management scheme based on the virtual queue size and the aggregate flow rate. Our proposal is tailored for the widely deployed TCP Reno and does not require modifications to TCP end users. We prove that our scheme can guarantee local stability for a network with an arbitrary topology and heterogeneous round-trip times for TCP users.

Relationship between erythrocyte aggregate size and flow rate in skeletal muscle venules.

In previous studies we showed that intravenous infusion of Dextran 500 in the rat causes blunting of the velocity profile of red blood cells in venules at low shear rates. To determine whether this blunting is associated with the formation of red blood cell aggregates, we measured the length and width of particles in the venular flow stream at systemic hematocrits up to 20% with a high-speed video camera and a new image analysis technique. Data were obtained at various shear rates under normal (nonaggregating) conditions as well as after infusion of Dextran 500. Under normal conditions, particle length (parallel to the vessel axis) was 6.5 +/- 2.7 microm and width (perpendicular to the axis) was 6.1 +/- 1.7 microm, in agreement with published dimensions of individual red blood cells for this species. After Dextran 500 infusion, particle length and width increased significantly to 8.7 +/- 5.1 and 10.4 +/- 4.4 microm, respectively. Particle dimensions were greater in the central region of the flow stream for both normal and dextran-treated blood and increased at low flow rates with dextran-treated blood. This study provides direct confirmation of aggregate formation at low shear in venules with high-molecular-weight dextran as well as an estimate of aggregate size and range.

Shear-dependent interaction of plasma proteins with erythrocytes in blood rheology.

Shear-dependent interaction of plasma proteins with erythrocytes in blood rheology.