Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets

Performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed component-based 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. In this paper, we present a novel case study of a realistic distributed component-based system, showing how Queueing Petri Net models can be exploited as a powerful performance prediction tool in the software engineering process. A detailed system model is built in a step-by-step fashion, validated, and then used to evaluate the system performance and scalability. Along with the case study, a practical performance modeling methodology is presented which helps to construct models that accurately reflect the system performance and scalability characteristics. Taking advantage of the modeling power and expressiveness of Queueing Petri Nets, our approach makes it possible to model the system at a higher degree of accuracy, providing a number of important benefits.     

MASCF: A generic process-centered methodological framework for analysis and design of multi-agent supply chain systems

Multi-agent systems (MAS) are becoming popular for modeling complex systems such as supply chains. However, development of multi-agent systems remain quite involved and extremely time consuming. Currently, there exist no generic methodologies for modeling supply chains using multi-agent systems. In this research, we propose a generic process-centered methodological framework, Multi-Agent Supply Chain Framework (MASCF), to simplify MAS development for supply chain (SC) applications. MASCF introduces the notion of process-centered organization metaphor, and creatively adopts Supply Chain Operations Reference (SCOR) model to a well-structured generic MAS analysis and design methodology, Gaia, for multi-agent supply chain system (MASCS) development. The popular Tamagotchi case was designed and analyzed using MASCF. The validity of the framework was established by implementing MASCF output of Tamagotchi SC using the Java Agent DEvelopment Framework (JADE).     

Systems dynamics modelling of a manufacturing supply chain system

Supply chains are multifaceted structures focusing on the integration of all the factors involved in the overall process of production and distribution of end products to the customers. Growing interest in supply chain systems has highlighted the need to adopt appropriate approaches that can ensure the efficient management of their complexity, enormity and broadness of scope. With the main aim of supply chain management being to optimise the performance of supply chains, attention is mainly drawn to the development of modelling frameworks that can be utilised to analyse and comprehend the dynamic behaviour of supply chains. While there have been only a few supply chain modelling attempts reported in the literature, this paper proposes a modelling framework that is used to simulate the operation of a supply chain network of moderate complexity. The proposed model comprises four echelons and is build around a central medium-sized manufacturing company operating as a typical Make-to-Order (MTO) system. The developed model was built using a systems dynamics (SD) approach. The operations performed within a supply chain are a function of a great number of key variables which often seem to have strong interrelationships. The ability of understanding the network as a whole, analysing the interactions between the various components of the integrated system and eventually supplying feedback without de-composing it make systems dynamics an ideal methodology for modelling supply chain networks. The objective of the paper is to model the operation of the supply chain network under study and obtain a true reflection of its behaviour. The modelling framework is also used to study the performance of the system under the initial conditions considered and compare it with that obtained by running the system under eight different scenarios concerning commonly addressed real-life operational conditions. The modelling effort has focused on measuring the supply chain system performance in terms of key metrics such as inventory, WIP levels, backlogged orders and customer satisfaction at all four echelons. The study concludes with the analysis of the obtained results and the conclusions drawn from contrasting the system’s performance under each investigated scenario to that of the benchmark model.     

Towards modeling and runtime verification of self-organizing systems

According to the fact that the intrinsic dynamism of self-organizing systems challenges the existing methods of engineering for modeling reliable complex systems, in this paper, we propose a new formal-based method to model self-organizing systems. The capabilities of the proposed method which are used to address several challenges in design, development and analysis of self-organizing systems are: modularity and robustness, decentralized control and scalability, required adaptation types, flexible and adaptive control mechanism, separation of adaptation and business logic, and safe adaptation. To evaluate the proposed method, we use self-organizing traffic management system as a case study and exploit the proposed method for modeling this dynamic system. Moreover, we propose and employ a novel policy-based runtime verification mechanism to ensure that the safety properties are satisfied by the implementation at runtime. We provide our case study prototype using Java and the Ponder2 toolkit and apply our runtime verification method to show its proper reaction capabilities to the property violations. This benefit is the result of using dynamic policies in our method to control the behavior of systems.     

Modeling event-based communication in component-based software architectures for performance predictions

Event-based communication is used in different domains including telecommunications, transportation, and business information systems to build scalable distributed systems. Such systems typically have stringent requirements for performance and scalability as they provide business and mission critical services. While the use of event-based communication enables loosely-coupled interactions between components and leads to improved system scalability, it makes it much harder for developers to estimate the system’s behavior and performance under load due to the decoupling of components and control flow. In this paper, we present our approach enabling the modeling and performance prediction of event-based systems at the architecture level. Applying a model-to-model transformation, our approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques. In summary, the contributions of this paper are: (1) the development of a meta-model for event-based communication at the architecture level, (2) a platform aware model-to-model transformation, and (3) a detailed evaluation of the applicability of our approach based on two representative real-world case studies. The results demonstrate the effectiveness, practicability and accuracy of the proposed modeling and prediction approach.     

基于UML-RT的复杂嵌入式系统建模方法及其应用

分析了UML在实时系统设计中的优点和需要解决的主要问题,论述了基于UML RT的实时嵌入式系统设计方法,并且对其进行扩展以支持数据流计算模型的建模,最后以汽车巡航系统为例加以说明。     

短生命周期产品的供应链仿真框架

文章提出了短生命周期产品的供应链管理的概念,介绍了这种供应链的特点和在管理中存在的问题。在分析其重点过程、性能指标、仿真参数的基础上,给出了短生命周期产品供应链管理的仿真框架,并针对其仿真特点和要求,研究了具有Petri网和面向对象技术特点的复合建模仿真技术。最后以服装业为例,给出了仿真实例。     

An advanced supply chain management tool based on modeling and simulation

The paper presents an advanced modeling approach and a simulation model for supporting supply chain management. The first objective is to develop a flexible, time-efficient and parametric supply chain simulator starting from a discrete event simulation package. To this end we propose and advanced modeling approach. The second objective is to provide a decision making tool for supply chain management. The simulator is a decision making tool capable of analyzing different supply chain scenarios by using an approach based on multiple performance measures and user-defined set of input parameters. Our simulator capabilities as decision making tool are strongly amplified if Design of Experiment (DOE) and Analysis of Variance (ANOVA) are respectively used for experiments planning and simulation results analysis. With regard to supply chain decision making process, we propose an application example for a better understanding of tool potentials. The application example considers a specific supply chain scenario and analyzes the effects of inventory control policies, lead times, customers’ demand intensity and variability, on three different supply chain performance measures.     

Return on investment calculator for RFID ecosystem of high tech company

The use of RFID technology affords an opportunity for greater visibility in the supply chain and further supply chain automation, making the processes more streamlined, providing accurate and timely automatic data capture, thereby improving shipment reliability. This paper provides a case study of an RFID-enabled supply chain ecosystem focusing on a large high tech multi-national corporation based in Singapore. Specifically, the paper provides an implementation framework for the Return on Investment (ROI) calculator which trades off labor cost and productivity gains. The Supply Chain Operations Reference (SCOR) methodology is used to assess the operational level benefits of RFID implementation. We show how scalability is critical for RFID adoption.     

Entropia: architecture and performance of an enterprise desktop grid system

The exploitation of idle cycles on pervasive desktop PC systems offers the opportunity to increase the available computing power by orders of magnitude (10×–1000×). However, for desktop PC distributed computing to be widely accepted within the enterprise, the systems must achieve high levels of efficiency, robustness, security, scalability, manageability, unobtrusiveness, and openness/ease of application integration.We describe the Entropia distributed computing system as a case study, detailing its internal architecture and philosophy in attacking these key problems. Key aspects of the Entropia system include the use of: (1) binary sandboxing technology for security and unobtrusiveness, (2) a layered architecture for efficiency, robustness, scalability and manageability, and (3) an open integration model to allow applications from many sources to be incorporated.Typical applications for the Entropia System includes molecular docking, sequence analysis, chemical structure modeling, and risk management. The applications come from a diverse set of domains including virtual screening for drug discovery, genomics for drug targeting, material property prediction, and portfolio management. In all cases, these applications scale to many thousands of nodes and have no dependences between tasks. We present representative performance results from several applications that illustrate the high performance, linear scaling, and overall capability presented by the Entropia system.     

An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry

Closed-loop supply chain management has been identified as an efficient, effective and economical strategy towards environmental sustainable practices in manufacturing companies. Without a formidable closed-loop supply chain to complement green supply chain management, most of the goals will not be achieved. A performance evaluation system is crucial for achieving a successful closed-loop supply chain in the automotive industry. Hence, a suitable expert fuzzy rule-based system for evaluation was developed in this study using Visual Basic.Net. The fuzzy rules and arithmetic used were described. The resulting performance measurement system was evaluated using a case study company from the automotive industry. The study culminated with recommendations and proposal of directions for future studies.     

Dynamic mobile RFID-based supply chain control and management system in construction

Construction project control attempts to effectively obtain real-time information and enhance dynamic control and management via information sharing and analysis from involved participants of the projects to reduce construction conflicts and project delay. However, extending the construction project control system to job sites is considered inefficient since construction sites are unconventional practice. Integrating promising information technologies such as radio frequency identification (RFID) technology, mobile devices-PDA and web portals can help improve the effectiveness and convenience of information flow in construction supply chain control systems. Radio frequency identification is appropriate for various construction applications, and provides cost savings through increased speed and accuracy of data entry. This study demonstrates the effectiveness of a RFID-based supply chain management application called the mobile construction RFID-based dynamic supply chain management (M-ConRDSCM) system in construction projects, demonstrating that it responds efficiently and enhances the information flow among offices and sites in a construction supply chain environment. The M-ConRDSCM system is then applied to a selected case study involving a High-Tech factory building in Taiwan to verify the proposed methodology and demonstrate the effectiveness of information sharing of project control in the construction phase. The advantage of the M-ConRDSCM system lies not only in improving work efficiency for on-site engineers, but also in providing dynamic operation control and management to enable project participants to control the whole project. Moreover, this study presents a generic system architecture and its implementation.     

Review of supply chain performance measurement systems: 1998–2015

In today’s competitive business environment, supply chain performance is one of the most critical issues in various industries. It is argued that supply chain performance measurement is fundamental to efficient supply chain management. Over the past two decades, several frameworks and systems have been developed to meet this need. This study reviews the literature in the field of supply chain performance measurement and assembles an overview of those systems, approaches, techniques and criteria. For this purpose, 83 of 374 related articles from 1998 to 2015 were selected for final review using the Scopus and ISI databases. Findings disclose that performance measurement in supply chain contexts is still a fruitful area of research. The study also provides an overview of the performance measures employed in supply chain systems. These findings present a solid basis for future academic and practitioner work in the field of supply chain performance measurement.     

Risk assessment and management for supply chain networks: A case study

The aim of this study is to show how a timed Petri nets framework can be used to model and analyze a supply chain (SC) network which is subject to various risks. The method is illustrated by an industrial case study. We first investigate the disruption factors of the SC network by a failure mode, effects and criticality analysis (FMECA) technique. We then integrate the risk management procedures into design, planning, and performance evaluation process of supply chain networks through Petri net (PN) based simulation. The developed PN model provides an efficient environment for defining uncertainties in the system and evaluating the added value of the risk mitigation actions. The findings of the case study shows that the system performance can be improved using risk management actions and the overall system costs can be reduced by mitigation scenarios.     

A comprehensive clustering algorithm for strategic analysis of supply chain networks

Inventory management in supply chain networks involves keeping track of hundreds of items spread across multiple locations with complex interrelationships between them. However, it is not computationally feasible to consider each item individually during the decision making process. The use of clusters of items is preferred for the evaluation of these decisions. In addition, the use of groups of items provides management with more effective methods for characterizing and controlling system performance and results in cost savings such as group discounts. In this research, we introduce a comprehensive clustering methodology for supporting inventory management in supply chain networks. All product characteristics which have a significant impact on the performance of the supply chain are taken into account. The nodes in the network are split into subnodes prior to clustering to reduce the complexity. The average linkage clustering algorithm and the Calinski and Harabasz index are used to identify clusters of similar items. In addition, a set of heuristics is used to capture the relationships between items as specified in the bill of materials for the products. Examples are presented to demonstrate the effectiveness of the clustering methodology as well as the performance of the heuristics, by comparing the results obtained with the optimal solution.     

ELDAMeth: An agent-oriented methodology for simulation-based prototyping of distributed agent systems

In application domains, such as distributed information retrieval, content management and distribution, e-Commerce, the agent-based computing paradigm has been demonstrated to be effective for the analysis, design and implementation of distributed software systems. In particular, several agent-oriented methodologies, incorporating suitable agent models, frameworks and tools, have been to date defined to support the development lifecycle of distributed agent systems (DAS). However, few of them provide effective validation methods to analyze design objects at different degrees of refinement before their actual implementation and deployment. In this paper, ELDAMeth, a simulation-based methodology for DAS, which enables rapid prototyping based on visual programming, validation, and automatic code generation for JADE-based DAS, is presented. ELDAMeth can be used both stand-alone for the modeling and evaluation of DAS and coupled with other agent-oriented methodologies for enhancing them with simulation-based validation. In particular, the proposed methodology, which is based on the ELDA (Event-driven Lightweight Distilled StateCharts-based Agents) agent model, provides key programming abstractions (event-driven computation, multi-coordination, and coarse-grained strong mobility) very suitable for highly dynamic distributed computing and is supported by a CASE tool-driven iterative process seamlessly covering the detailed design, simulation, and implementation phases of DAS. A simple yet effective case study in the distributed information retrieval domain is used to illustrate the proposed methodology.     

Modeling and performance evaluation of supply chains using batch deterministic and stochastic Petri nets

Batch deterministic and stochastic Petri nets are introduced as a tool for modeling and performance evaluation of supply chains. The new model is developed by enhancing deterministic and stochastic Petri nets (DSPNs) with batch places and batch tokens. By incorporating stochastic Petri nets (SPNs) with the batch features, inhibitor arcs, and marking-dependent weights, operational policies of supply chains such as inventory policies can be easily described in the model. Methods for structural and performance analysis of the model are developed by extending existing ones for DSPNs. As applications, an inventory system and an industrial supply chain are modeled and their performances are evaluated analytically and by simulation, respectively, using this BSPN model. The applications demonstrate that our model and associated methods can solve some important supply chain modeling and analysis issues. Note to Practitioners-This paper was motivated by the problem of performance analysis and optimization of supply chains but it also applies to other discrete event systems where materials are processed in finite discrete quantities (batches) and operations are performed in a batch way because of batch inputs and/or in order to take advantages of the economies of scale. Existing Petri net modeling and analysis tools for such systems ignore their batch features, making their modeling complicated. This paper suggests a new model called batch deterministic and stochastic Petri nets (BDSPNs) by enhancing deterministic and stochastic Petri nets with batch places and batch tokens. Methods for structural and performance analysis of the model are developed. We then show how an inventory system and a real-life supply chain can be modeled and their performances can be evaluated analytically and by simulation respectively based on the model. The model and associated analysis methods therefore provide a promising tool for modeling and performance evaluation of supply chains.     

Data modeling in the NoSQL world

NoSQL systems have gained their popularity for many reasons, including the flexibility they provide in organizing data, as they relax the rigidity provided by the relational model and by the other structured models. This flexibility and the heterogeneity that has emerged in the area have led to a little use of traditional modeling techniques, as opposed to what has happened with databases for decades.In this paper, we argue how traditional notions related to data modeling can be useful in this context as well. Specifically, we propose NoAM (NoSQL Abstract Model), a novel abstract data model for NoSQL databases, which exploits the commonalities of various NoSQL systems. We also propose a database design methodology for NoSQL systems based on NoAM, with initial activities that are independent of the specific target system. NoAM is used to specify a system-independent representation of the application data and, then, this intermediate representation can be implemented in target NoSQL databases, taking into account their specific features. Overall, the methodology aims at supporting scalability, performance, and consistency, as needed by next-generation web applications.     

Modeling the planning process in advanced planning systems

Whereas much of the modeling literature in supply chain planning addresses the analysis of decision models and presents solution techniques and much of the empirical literature on planning systems such as ERP and APS software addresses implementation challenges from an organizational perspective, research on the modeling process of capturing the planning process in planning software is very scarce. In this paper, we examine this modeling process. Our approach is based on a normative method for hierarchical planning and presents a case study where this modeling process was used. We analyze the process, relate it to the literature on modeling, and demonstrate the value of the theory in explaining major observations. We conclude that the hierarchical premise on which most planning processes are based is very difficult to capture in an advanced planning system, and find that users and organizations essentially circumvent this problem by creating their own workflows, independent of the system’s prescribed one.     

ArchSim: A System-Level Parallel Simulation Platform for the Architecture Design of High Performance Computer

High performance computer (HPC) is a complex huge system, of which the architecture design meets increasing difficulties and risks. Traditional methods, such as theoretical analysis, component-level simulation and sequential simulation, are not applicable to system-level simulations of HPC systems. Even the parallel simulation using large-scale parallel machines also have many difficulties in scalability, reliability, generality, as well as efficiency. According to the current needs of HPC architecture design, this paper proposes a system-level parallel simulation platform: ArchSim. We first introduce the architecture of ArchSim simulation platform which is composed of a global server (GS), local server agents (LSA) and entities. Secondly, we emphasize some key techniques of ArchSim, including the synchronization protocol, the communication mechanism and the distributed checkpointing/restart mechanism. We then make a synthesized test of some main performance indices of ArchSim with the phold benchmark and analyze the extra overhead generated by ArchSim. Finally, based on ArchSim, we construct a parallel event-driven interconnection network simulator and a system-level simulator for a small scale HPC system with 256 processors. The results of the performance test and HPC system simulations demonstrate that ArchSim can achieve high speedup ratio and high scalability on parallel host machine and support system-level simulations for the architecture design of HPC systems.