Delay-based distribution and optimization of a simulation model

The conception of Cyber-Physical Systems is a complex task: the multiple components making up those systems might not be fully known by the system architect, and putting those components together generates a new source of complexity. Study and validation of those systems is often done through simulation. Moreover, the CPS simulation is often studied through distributed simulation, as the CPS might itself be distributed or too complex. We present a methodology to distribute a simulation model in order to take full advantage of multiple processing units. We ensure that said distribution does not impact the simulation of our modeled system

Operating Task Redistribution in Hyperconverged Networks

In this article, a searching method for the rational task distribution through the nodes of a hyperconverged network is presented in which it provides the rational distribution of task sets towards a better performance. With using new subsettings related to distribution of nodes in the network based on distributed processing, we can minimize average packet delay. The distribution quality is provided with using a special objective function considering the penalties in the case of having delays. This process is considered in order to create the balanced delivery systems. The initial redistribution is determined based on the minimum penalty. After performing a cycle (iteration) of redistribution in order to have the appropriate task distribution, a potential system is formed for functional optimization. In each cycle of the redistribution, a rule for optimizing contour search is used. Thus, the obtained task distribution, including the appeared failure and success, will be rational and can decrease the average packet delay in the hyperconverged networks. The effectiveness of our proposed method is evaluated by using the model of hyperconverged support system of the university E-learning provided by V.N. Karazin Kharkiv National University. The simulation results based on the model clearly confirm the acceptable and better performance of our approach in comparison to the classical approach of task distribution

Dynamic Message Sign and Diversion Traffic Optimization

This dissertation proposes a Dynamic Message Signs (DMS) diversion control system based on principles of existing Advanced Traveler Information Systems and Advanced Traffic Management Systems (ATMS). The objective of the proposed system is to alleviate total corridor traffic delay by choosing optimized diversion rate and alternative road signal-timing plan. The DMS displays adaptive messages at predefined time interval for guiding certain number of drivers to alternative roads. Messages to be displayed on the DMS are chosen by an on-line optimization model that minimizes corridor traffic delay. The expected diversion rate is assumed following a distribution. An optimization model that considers three traffic delay components: mainline travel delay, alternative road signal control delay, and the travel time difference between the mainline and alternative roads is constructed. Signal timing parameters of alternative road intersections and DMS message level are the decision variables; speeds, flow rates, and other corridor traffic data from detectors serve as inputs of the model. Traffic simulation software, CORSIM, served as a developmental environment and test bed for evaluating the proposed system. MATLAB optimization toolboxes have been applied to solve the proposed model. A CORSIM Run-Time-Extension (RTE) has been developed to exchange data between CORSIM and the adopted MATLAB optimization algorithms (Genetic Algorithm, Pattern Search in direct search toolbox, and Sequential Quadratic Programming). Among the three candidate algorithms, the Sequential Quadratic Programming showed the fastest execution speed and yielded the smallest total delays for numerical examples. TRANSYT-7F, the most credible traffic signal optimization software has been used as a benchmark to verify the proposed model. The total corridor delays obtained from CORSIM with the SQP solutions show average reductions of 8.97%, 14.09%, and 13.09% for heavy, moderate and light traffic congestion levels respectively when compared with TRANSYT-7F optimization results. The maximum model execution time at each MATLAB call is fewer than two minutes, which implies that the system is capable of real world implementation with a DMS message and signal update interval of two minutes

A 3d multidisciplinary automated design optimization toolbox for wind turbine blades based on ns solver and experimental data

This thesis attempts to develop a framework to optimize wind turbine blades automatically by a multidisciplinary 3D modeling and simulation methods. The original NREL Phase VI wind turbine blade and its experimental measurements are used to validate the Computational Fluid Dynamics (CFD) model developed in ANSYS Fluent and based on the 3D Navier-Stokes (NS) solver with a realizable k-epsilon turbulence model, which is later used in the automation process. The automated design optimization process involves multiple modeling and simulation methods using Solidworks and ANSYS Mesher and ANSYS Fluent NS solver, which are integrated and controlled through Matlab by implementing the scripting capabilities of each software package. Then all scripts are integrated into one optimization cycle, with its optimization objective being the highest mean value of 3D Lift/Drag ratio (3DLDR) across the blade. A 3DLDR distribution across the blade can be calculated by the Inverse Blade Element Momentum (IBEM) Method based on experimental measurements. The optimization process is performed to find optimized twist angles across the blade using the Angle of Attack (AOA) with the highest 3DLDR as a reference, in order to 3 achieve the optimization objective. Therefore, the automatic optimization framework is based on 3D solid modeling and 3D aerodynamic simulation and guided by IBEM and experimental data. Thus the design tool is capable of exploiting the 3D stall delay of blades designed by the traditional 2D BEM method to enhance their performances. It is found that this automated framework can result in optimized blade geometries with the improvement of performance parameters compared to the original ones

Airline schedule punctuality management

Airline schedule punctuality is a complex problem and one of the major concerns of the airline top management. Flight schedule disturbances may occur as delays and/or cancellations. There are many internal and external reasons for delays. These delays may propagate in the aircraft cycles and cause a large schedule disturbance. This may influences passenger satisfaction and airline resources. The objective of this research is to formulate a systematic approach for schedule punctuality which supports management decision making. The punctuality management system is structured to combine all schedule punctuality components, input and output variables. Five models are incorporated in this system. The first model is the disturbance model which generates random delays based on an estimated Lognormal delay distribution function. The delay analysis is carried out from a one year sample of delay statistics in which general, original , reactionary and other delay types are classified. The second model is the recovery model which incorporates the disturbance model with management strategies to determine delay propagation. A PC based simulation model (SKDMOD) is developed as a prototype which integrates disturbance and recovery models using SIMSCRIPT 11.5. 18 management strategies are simulated covering ground times (30, 40 and 50 minutes), maximum delay times to assign spare aircraft (1, 2, 3, 4, 5, and 6 hours) and spare aircraft using part of the domestic network of Saudi Arabia. The third model is the passengers' attitude model which determines the delay impact functions and the maximum passenger revenue loss based on 262 responses from a passenger interview survey. The fourth model is the revenue model which estimates the passengers' revenue loss. The fifth model is the cost model which estimates the extra cost resulting from implementation of the management strategies. All strategies are evaluated to determine the optimum based on profit and profit margin. OPTIM is the optimization program developed to find the optimum strategy(ies). This approach provides a guidelines for the management of punctuality. It integrates all the tools developed in a decision support system framework

Improved Data Transmission Scheme of Network Coding Based on Access Point Optimization in VANET

VANET is a hot spot of intelligent transportation researches. For vehicle users, the file sharing and content distribution through roadside access points (AP) as well as the vehicular ad hoc networks (VANET) have been an important complement to that cellular network. So the AP deployment is one of the key issues to improve the communication performance of VANET. In this paper, an access point optimization method is proposed based on particle swarm optimization algorithm. The transmission performances of the routing protocol with random linear network coding before and after the access point optimization are analyzed. The simulation results show the optimization model greatly affects the VANET transmission performances based on network coding, and it can enhance the delivery rate by 25% and 14% and reduce the average delay of transmission by 38% and 33%

Analysis of Multiple Flows using Different High Speed TCP protocols on a General Network

We develop analytical tools for performance analysis of multiple TCP flows (which could be using TCP CUBIC, TCP Compound, TCP New Reno) passing through a multi-hop network. We first compute average window size for a single TCP connection (using CUBIC or Compound TCP) under random losses. We then consider two techniques to compute steady state throughput for different TCP flows in a multi-hop network. In the first technique, we approximate the queues as M/G/1 queues. In the second technique, we use an optimization program whose solution approximates the steady state throughput of the different flows. Our results match well with ns2 simulations.Comment: Submitted to Performance Evaluatio