Cascaded asymmetrical triple-ring multibus system: Modelling and performance analysis

Performance analysis and prediction of asymmetric two-level priority polling system based on BP neural network

In the preface to The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling , Raj Jain discusses the intended audience and the goals of the book, which are to:• Provide computer professionals simple and straightforward performance analysis techniques in a comprehensive textbook.• Give basic modeling, simulation, measurement, experimental design, and statistical analysis background.• Emphasize and integrate the modeling and measurement aspects of performance analysis.• Discuss common mistakes and games in performance analysis studies.• Illustrate the presented techniques using examples and case studies from the field of computer systems.• Summarize key techniques and results in "boxes".• Organize chapters in 45-minute lectures and include appropriate exercises.

Predictive performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed systems. However, as systems grow in size and complexity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. The challenge stems from the limited model expressiveness on the one hand and the limited scalability of model analysis techniques on the other. This chapter presents a novel methodology for modeling and performance analysis of distributed systems [Kounev, 2006]. The methodology is based on queueing Petri nets (QPNs) which provide greater modeling power and expressiveness than conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using QPNs, one can integrate both hardware and software aspects of system behavior into the same model. In addition to hardware contention and scheduling strategies, QPNs make it easy to model software contention, simultaneous resource possession, synchronization, blocking and asynchronous processing. These aspects have significant impact on the performance of modern distributed systems. To avoid the problem of state space explosion, our methodology uses discrete event simulation for model analysis. We propose an efficient and reliable method for simulation of QPNs [Kounev & Buchmann, 2006]. As a validation of our approach, we present a case study of a real-world distributed system, showing how our methodology is applied in a step-by-step fashion to evaluate the system performance and scalability. The system studied is a deployment of the industry-standard SPECjAppServer2004 benchmark. A detailed model of the system and its workload is built and used to predict the system performance for several deployment configurations and workload scenarios of interest. Taking advantage of the expressive power of QPNs, our approach makes it possible to model systems at a higher degree of accuracy providing a number of important benefits. The rest of this chapter is organized as follows. In Section 2, we give a brief introduction to QPNs. Following this, in Section 3, we present a method for quantitative analysis of QPNs based on discrete event simulation. The latter enables us to analyze QPN models of realistic size and complexity. In Section 4, we present our performance modeling methodology for distributed systems. The methodology is introduced in a step-by-step

Performance analysis of a complex computing system requires a lot of time and effort. Many studies related to performance analysis have been conducted. Firstly, there are studies about workload modeling that model and analyze the observed workloads using statistical summaries. Also, there are studies to analyze system behavior and procedures through simulation modeling. However, there are some disadvantages to using only one approach for analyzing the complex system more accurately. Therefore, this paper presents cooperation between data modeling and simulation modeling for performance analysis of the system. The target system, Hadoop, is one of the representative big data platforms that can demonstrate the complexity of the analysis. Firstly, we identify the characteristics of Hadoop and divide them into two parts according to their characteristics. Then, we model and integrate them using each modeling approach. This paper presents the experiment to show the advantages of the cooperative modeling in the accuracy, execution time, and modeling extensibility.

To provide food supply chains, reduce losses from various crops after the harvesting process, and also to preserve vegetable and fruit crops purchased for consumption from rotting and not being wasted. The drying process is one of the most appropriate ways to solve such problems. In this research, several simple thermal modeling methods were proposed to perform the drying process through open sun drying (OSD) under forced pressure (FGD) and natural convection (NGD). This study was conducted at the King Faisal University Training and Research Station (25.4° latitude). North, longitude 49.6° east, height 142 meters above sea level). The thermal performance analysis of the models was evaluated by calculating the amount of solar radiation, air temperature, product temperature, moisture evaporation rate, and wind speed. The results obtained showed that drying inside the greenhouse is the best alternative to drying under direct sunlight, so that the maximum temperatures were obtained, ranging between 55 to 52 in FGD and 40−45 inside NGD. Also, the heat transfer coefficient was highest in the amount of moisture removed from the product, reaching its maximum. The weight of the product was reduced to 83%, 80 and 73%, in GFD, NGD and OSD, respectively Accordingly, it was found that drying gave the highest expected results, and the temperature of the product ranged between 9.25 to 14.36 and 4.93 to 10.32, and the correlation coefficient ranged between 0.95−0.52 and 0.95. −0.89 at OSD and NGD respectively. Moisture evaporation from the product is 28.92−2.77 at NGD and moisture evaporation exerted for FGD is 31.35 and the correlation coefficient for the product at FGD ranges from 0.93−0.84. The product and greenhouse temperature range are between 0.99−0.96. The moisture evaporation rate indicating that the values obtained were well matched. Finally, the economic analysis of the different methods of drying was done through a mathematical model.

Wireless sensor networks (WSNs) have unlimited and extensive potential application in different areas. Right now, how to integrate WSNs into the web service is an issue in related research related areas. In this paper, firstly, we do a survey on related research work, then we put forward a delay tolerant wireless sensor web service framework (DTN-WSNWS),after that we build corresponding queuing model for this framework, and give its performance analysis and numeral simulation results. Finally, based on the results of performance analysis and simulation, we give some basic optimization parameter selection norms in this framework.

This paper focuses on the methodology analysis for the stability and the corresponding tracking performance of a closed-loop digital jump linear control system with a stochastic switching signal. The method is applied to a flight control system. A distributed recoverable platform is implemented on the flight control system and subject to independent digital upsets. The upset processes are used to stimulate electromagnetic environments. Specifically, the paper presents the scenarios that the upset process is directly injected into the distributed flight control system, which is modeled by independent Markov upset processes and independent and identically distributed (IID) processes. A theoretical performance analysis and simulation modelling are both presented in detail for a more complete independent digital upset injection. The specific examples are proposed to verify the methodology of tracking performance analysis. The general analyses for different configurations are also proposed. Comparisons among different configurations are conducted to demonstrate the availability and the characteristics of the design.

This paper investigates the wireless communication with a novel architecture of antenna arrays, termed modular extremely large-scale array (XL-array), where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules. Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength, while different modules are separated by the relatively large inter-module distance for convenience of practical deployment. By accurately modelling the signal amplitudes and phases, as well as projected apertures across all modular elements, we analyse the near-field signal-to-noise ratio (SNR) performance for modular XL-array communications. Based on the non-uniform spherical wave (NUSW) modelling, the closed-form SNR expression is derived in terms of key system parameters, such as the overall modular array size, distances of adjacent modules along all dimensions, and the user's three-dimensional (3D) location. In addition, with the number of modules in different dimensions increasing infinitely, the asymptotic SNR scaling laws are revealed. Furthermore, we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases, e.g., the collocated XL-array architecture, the uniform plane wave (UPW) based far-field modelling, and the modular extremely large-scale uniform linear array (XL-ULA) of one-dimension. Extensive simulation results are presented to validate our findings.

Modeling and Experimental Analysis of Suction Pressure Generated by Active Suction Chamber Based Wall Climbing Robot with a Novel Bottom Restrictor

Robotic arms are widely used in industrial automation due to their simple structure, high flexibility, and moderate cost, especially in standardized scenarios such as conveyor belt operations. This study focuses on a three-axis robotic arm, addressing the demands of conveyor belt operations through modeling and performance analysis. First, precise structural modeling of the robotic arm was completed using SolidWorks, and its kinematic model was established using the D-H parameter method. Second, trajectory planning of the end-effector was studied based on task-specific requirements, and the variations in joint angles, velocities, and accelerations were analyzed through simulations. Finally, the smoothness of paths and workspace coverage were evaluated via simulations. Results indicate that the three-axis robotic arm can meet the demands of conveyor belt operations with good applicability. However, further improvements in control precision and dynamic stability are needed for more complex, non-standardized scenarios. This study provides theoretical support for the design optimization and broader application of three-axis robotic arms.

Supply chains are becoming more global, complex and increasingly vulnerable. Specifically, the latest evolution of the modern supply chains creates crucial cyber-risks and cyber-security challenges. Nowadays, supply chain risk managers need methods and tools for control, analysis, risk mitigation and managing of their cyber vulnerabilities. In this context, cyber-risk modeling and analysis in supply chain has become one of the major research subjects. The first part of this chapter provides a survey of the field and investigates the use of Petri Nets as a tool for modeling and performance analysis of supply chains, as well as their great potential for supply chain risk analysis. The second part of this work is dedicated to our contributions for modeling and performance evaluation of supply chain networks by using discrete event dynamic approaches. Based on the modeling and performance analysis power of Batch Deterministic and Stochastic Petri nets (BDSPN) for supply chain and logistic systems, two original risk-modeling approaches are introduced for this emerging research topic.

This paper presents an systematic dynamic modeling and performance analysis method of an over-constrained 2PUR-PSR parallel manipulator with parasitic motions, where P, U, S, and R represent the prismatic joint, universal joint, spherical joint, and revolute joint, respectively. The process of the deduction of the over-constrained forces/moment is given. The Newton–Euler approach and natural orthogonal complement method are adopted to establish two types of dynamic models with and without constrained forces/moments with the consideration of the over-constrained forces/moments. The dynamic manipulability ellipsoid, which measures the uniformity of changing the position and orientation of the manipulator’s moving platform, is adopted to evaluate the dynamic performance of the parallel manipulator. To show the feasibility of the proposed method, numerical simulations are conducted to investigate the dynamic models and performance of the 2PUR-PSR manipulator. The actuation forces, constrained forces/moments, and the compatible deformation are calculated. Distribution of the DME index is also obtained. The proposed modeling approach provides a fundamental basis for the structural optimization and control scheme design of the over-constrained parallel manipulator.

This paper focuses on the modeling and symmetry breaking analysis of the large class of chaotic electronic circuits utilizing an antiparallel diodes pair as nonlinear device necessary for chaotic oscillations. A new and relatively simple autonomous jerk circuit is used as a paradigm. Unlike current approaches assuming identical diodes (and thus a perfect symmetric circuit), we consider the more realistic situation where both antiparallel diodes present different electrical properties in spite of unavoidable scattering of parameters. Hence, the nonlinear component synthesized by the diodes pair exhibits an asymmetric current–voltage characteristic which engenders the explicit symmetry break of the whole electronic circuit. The mathematical model of the new circuit consists of a continuous time 3D autonomous system with exponential nonlinear terms. We investigate the chaos mechanism with respect to model parameters and initial conditions as well, both in the symmetric and asymmetric modes of operation by using bifurcation diagrams and phase space trajectories plots as main indicators. We report period doubling route to chaos, spontaneous symmetry breaking, merging crisis and the coexistence of two, four, or six mutually symmetric attractors in the symmetric regime of operation. More intriguing and complex nonlinear behaviors are revealed in the asymmetric system such as coexisting asymmetric bubbles of bifurcation (a new kind of phenomenon discovered in this work), hysteretic dynamics, critical phenomena, and coexisting multiple (i.e. two, three, four, or five) asymmetric attractors for some appropriately selected values of parameters. Laboratory experimental tests are conducted to support the theoretical analysis. The results obtained in this work clearly indicate that chaotic circuits with back to back diodes can demonstrate much more complex dynamics than what is reported in the relevant literature and thus should be reconsidered accordingly following the method described in this paper.

Mie Gacoan Restaurant faces long queues especially during rush hour, which leads to long waiting times and decreased customer satisfaction. The purpose of this study is to evaluate the existing queue system and create an overall service process model. The system receives input in the form of data on the number of customers and service duration, while the output is in the form of a queue model and performance analysis. This topic is significant because the speed of service is a key factor in customer satisfaction in fast food restaurants. Currently, there is no model that describes in detail the queuing system at Mie Gacoan, so there is no analytical basis for operational improvements. The solution is carried out through discrete simulation modeling based on the results of field observations. The system was analyzed using a single queue–multiple server model that depicts the real conditions of the restaurant. Simulation of multiple scenarios was used to examine the effect of changes in the number of servers on queue performance. The addition of one waiter during peak hours has been proven to reduce waiting times by up to 35% and queue lengths by up to 40%. This research contributes as a quantitative basis for operational decision-making.

A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.