SimEnvir++: An object-based simulation environment

In this paper an object-oriented discrete event simulation environment, SimEnvir++ is presented. The aim of the environment is to provide a research environment for design, analysis and management of electronic manufacturing systems. SimEnvir++ combines interactive simulation model design, object manipulation, simulation, output analysis and animation, to provide an intuitive modeling capability.     

Kassandra: A framework for distributed simulation of heterogeneous cooperating objects

To address the heterogeneity and scalability issues of simulating Cooperating Objects (COs) systems, we propose Kassandra, a conceptual framework for enabling distributed COs simulation by integrating existing simulation tools. Moreover, Kassandra exploits the communication middleware used by real-world COs as underlying communication mechanism for integrating Kassandra-enabled simulation tools. In this way, real-world COs can be included with simulated objects in a seamless way to perform more accurate system performance evaluation. Moreover, such a hardware-in-the-loop approach is not limited to pre-deployment performance analysis, and can offer possibilities to analyse performance at different phases of CO applications. The concept of Kassandra has been carried out in the EU PLANET project. In this paper, we introduce the Kassandra framework components and show their interactions at different phases for node deployments in PLANET use cases. The result demonstrates the applicability of Kassandra to facilitate the development of CO applications.     

An open source object-based framework to extract landform classes

This paper introduces a new open source, knowledge-based framework for automatic interpretation of remote sensing images, called InterIMAGE. This framework exhibits a flexible modular architecture, in which image processing operators can be associated to both root and leaf nodes of a semantic network, which accounts for a differential strategy in comparison to other object-based image analysis platforms currently available. The architecture, main features as well as an overview on the interpretation strategy implemented in InterIMAGE are presented. The paper also reports an experiment on the classification of landforms. Different geomorphometric and textural attributes obtained from ASTER/Terra images were combined with fuzzy logic to drive the interpretation semantic network. Object-based statistical agreement indices, estimated from a comparison between the classified scene and a reference map, were used to assess the classification accuracy. The InterIMAGE interpretation strategy yielded a classification result with strong agreement and proved to be effective for the extraction of landforms.     

An immunity-based distributed multiagent-control framework

The human immune system is a complex system of cells, molecules, tissues, and diverse organs that can provide us with primary defense against pathogenic organisms. These components are highly interactive and execute the immune response in a coordinated and specific manner. This paper presents a formal mathematical model of an artificial immune system (AIS)-based control framework. The framework aims to provide an integrated solution to control and coordinate complex distributed systems with a large number of autonomous agents such as automated warehouses, distribution centers, and automated material-handling systems. The control framework consists of a set of AIS agents working in response to the changing environment and the occurrence of tasks. The AIS agents manipulate their capabilities to derive appropriate responses to tackle different problems. A methodology describing the response-manipulation algorithm of the AIS agents and their ability to generate new capabilities is discussed in this paper. Through response manipulation and knowledge building, a self-organized and fully distributed system with agents that are able to adapt and accommodate in a dynamic environment via distributed decision making and interagent communication is achieved.     

基于网格的分布式虚拟环境仿真海量数据管理

分析了分布式虚拟环境仿真的特点,提出了基于网格的分布式虚拟环境仿真的海量数据管理框架.该框架结构采用分层结构,自底向上依次为网格节点、高性能通信系统、数据存储与处理系统和计算系统.给出了一个基于上述体系结构的原型系统.对该原型系统的仿真结果表明,该海量数据管理体系结构设计符合虚拟环境仿真实时性、稳定性和高可靠性的要求.     

An architectural application framework for evolving distributed systems

In this paper, we present an object-oriented application framework to support the development of evolving distributed systems. The framework combines concepts of the object-oriented paradigm with those of architectural design. The result is a framework which supports extensible and reusable configurations of distributed components. The framework addresses the problem of evolution by allowing the addition, replacement and extension of components of a configuration. Evolution is also possible at run time, where a configuration can change dynamically depending on a particular event. The paper outlines the fundamental aspects of our framework and presents a case study, which illustrates its application.     

An object-oriented framework for developing distributed manufacturing architectures

Management of complexity, changes and disturbances is one of the key issues of production today. Distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced.     

Training individuals for distributed teams: problem solving assessment for distributed mission research

In this paper we describe an effort investigating the feasibility and utility of cognitively diagnostic assessment of problem solving when training for distributed team tasks. We utilized computer-based knowledge elicitation methods to assess both relational problem solving, requiring the semantic integration of concepts, and dynamic problem solving, requiring the ability to integrate and apply these concepts. Additionally, we addressed how metacognitive processes interact with learning outcomes when training for complex synthetic task environments. We find first, that multiple methods of assessing problem solving performance are diagnostic of knowledge acquisition for a complex synthetic team task, and second, that general metacomprehension predisposition is related to metacomprehension accuracy in synthetic task environments.     

An ultra-large-scale simulation framework

Many modern systems involve complex interactions between a large number of diverse entities that constitute these systems. Unfortunately, these large, complex systems frequently defy analysis by conventional analytical methods and their study is generally performed using simulation models. Further aggravating the situation, detailed simulations of large systems will frequently require days, weeks, or even months of computer time and lead to scaled down studies. These scaled down studies may be achieved by the creation of smaller, representative, models and/or by analysis with short duration simulation exercises. Unfortunately, scaled down simulation studies will frequently fail to exhibit behaviors of the full-scale system under study. Consequently, better simulation infrastructure is needed to support the analysis of ultra-large (models containing over 1 million components)-scale models.Simulation support for ultra-large-scale simulation models must be achieved using low-cost commodity computer systems. The expense of custom or high-end parallel systems prevent their widespread use. Consequently, we have developed an Ultra-large-Scale Simulation Framework (USSF). This paper presents the issues involved in the design and development of USSF. Parallel simulation techniques are used to enable optimal time versus resource tradeoffs in USSF. The techniques employed in the framework to reduce and regulate the memory requirements of the simulations are described. The API needed for model development is illustrated. The results obtained from the experiments conducted using various system models with two parallel simulation kernels (comparing a conventional approach with USSF) are also presented.     

A pre-run-time scheduling algorithm for object-based distributed real-time systems

The most important goal in hard real-time systems is to guarantee that all timing constraints are satisfied. Even though object-based techniques (which contain reusable software components) are used to manage the complexity in the software development process of such systems, execution efficiency may have to be sacrificed, due to the large number of procedure calls and contention for accessing software components. These issues are addressed by the following parallelizing techniques: (a) converting potentially inefficient procedure calls to a source of concurrency via asynchronous remote procedure calls (ARPC) (b) replicating (or cloning) software components to reduce the contention. The existing object-based scheduling algorithms construct an initial schedule and apply incremental parallelization techniques to modify the initial schedule till a feasible schedule is generated. But these algorithms are applicable for scheduling only multiple independent tasks. This paper describes a pre-run-time scheduling algorithm for a set of periodic object-based tasks having precedence constraints among them. The algorithm allocates the components of object-based periodic real-time tasks to the sites of a distributed system based on a clustering heuristic which takes into account the ARPC parallelism and load balancing, and schedules them on respective sites. The algorithm also finds a schedule for communication channel(s). Further, it clones the components of object-based periodic tasks, if contention occurs in accessing them. In addition to the above (periodicity and precedence) constraints, the tasks handled by our algorithm can have resource constraints among them. The experimental evaluation of the algorithm shows that the combination of the proposed clustering heuristic and cloning enhances schedulability.     

基于HLA的分布式仿真框架自动生成技术

针对基于HLA仿真应用系统开发中存在的计算模型程序与RTI服务程序的耦合问题,研究了基于共享内存和中断回调技术的解耦方法,进一步采用HLA仿真适配器对RTI服务程序进行封装,从而实现了计算模型程序与RTI底层服务程序的有效隔离。为提高仿真应用程序开发效率,分析了联邦成员中RTI服务程序功能需求,研究实现了仿真适配器自动生成软件。该软件可快速生成基于HLA的联邦成员适配器代码和执行程序,从而构建仿真应用系统分布式仿真框架。     

Pseudosimulation: An algorithm for distributed simulation with limited memory

In this paper we present a new algorithm for the distributed simulation of systems that may be modeled as a network of processes which exchange event messages (e.g., computer networks, telephone systems). We focus upon the case of fully distributed processes with limited memory available to simulate each process. The synchronization algorithm employed is a blocking algorithm. The simulation of different processes is allowed to proceed in parallel until deadlock occurs, at which time a deadlock-breaking algorithm is invoked as in the Chandy/Misra scheme.⁽¹⁾ A central controller is emploled to detect and aid in the efficient resolution of deadlocks. We solve some problems which were not clearly addressed in the Chandy/Misra scheme. Our deadlock-breaking algorithm, christened Pseudosimulation, is a look-ahead algorithm, which undertakes to fill empty buffers with future event messages. Correctness and termination of the algorithm are proven. An analysis of the memory requirements and running time is performed. A lower bound on the memory requirements is also established which simplifies the deadlock-breaking algorithm.Research supported by grants from the National Sciences and Engineering Research Council of Canada and Centre de recherche informatique de Montréal.     

RoboNetSim: An integrated framework for multi-robot and network simulation

In networked multi-robot systems, communication plays a major role defining system’s dynamics and performance. Unfortunately, existing multi-robot simulators do not provide advanced communication models. Therefore, given the intrinsic unreliability of wireless communications, significant differences might be observed between simulation and real-world results.Addressing these issues, we present RoboNetSim, an integrated simulation framework for communication-realistic simulation of networked multi-robot systems. RoboNetSim integrates multi-robot simulators with network simulators. We present two model implementations based on ARGoS at the robotic side, and NS-2 and NS-3 as network simulators. We evaluate the framework in terms of accuracy and computational performance, showing that it can efficiently simulate systems consisting of hundreds of robots.Using the Stage simulator as an example, we also show the integration of a robotic simulator with RoboNetSim by only adapting robot controllers, without the need to adapt the general code of the simulator.Finally, we demonstrate the effects of communication on mobile multi-robot systems. We consider two different case studies: a distributed coordination and task assignment scenario, and a coordinated mobility scenario. We compare realistic network simulation with simplified communication models and algorithms, and we study the resulting behavior and performance of the multi-robot system and the impact of different parameters.     

COOL: An object-based language for parallel programming

Effectively using shared-memory multiprocessors requires substantial programming effort. We present the programming language COOL (Concurrent Object-Oriented Language), which was designed to exploit coarse-grained parallelism at the task level in shared-memory multiprocessors. COOL's primary design goals are efficiency and expressiveness. By efficiency we mean that the language constructs should be efficient to implement and a program should not have to pay for features it does not use. By expressiveness, we imply that the program should flexibly support different concurrency patterns, thereby allowing various decompositions of a problem. COOL emphasizes the integration of concurrency and synchronization with data abstraction to ease the task of creating modular and efficient parallel programs. It is an extension of C++, which was chosen because it supports abstract data type definitions and is widely used     

EIS/XAIT project: an object-based interoperability framework for heterogeneous systems

This paper briefly describes various technical issues involved in the design and development of an object-based interoperability framework in support of Engineering Information Systems (EIS). It also discusses the interaction of such frameworks with various emerging standards and the possibility of developing standards in the area of object-oriented interoperable frameworks. Finally, it summarizes the background and the status of the project.     

一种分布式自治物流信息系统构架

针对物流企业及零售商分散的特点和客户的多样化个性化需求,为了整合分散的物流信息,建立具有弹性的物流对象协同运作模式,解决RFID与该构架的信息集成,提出了一种基于Internet的分布式协调自治物流信息系统构架。详细描述了系统的各关键环节。     

A model for scheduling of object-based,distributed real-time systems

This paper describes a general model for pre-run-time scheduling of distributed real-time systems that are composed of abstract data types (definable in languages such as Ada, Clu and Modula-2) and abstract data objects (which can be defined in C++, Eiffel and RT Euclid). An architecture model, a programming paradigm, and execution and communication paradigms form the basis for this general model. The model includesabsolute timing constraints to represent periodicity and deadlines,relative timing constraints to model several kinds of timed precedence relations and synchronization requirements,independency constraints to capture non-determinism of conditionals and repetitions, andconsistency constraints to enforce consistent use of resources. In this paper, the model is formalized to obtain a mathematical foundation on which assignment (Verhoosel et al. 1993a, Welch 1992, Welch et al. 1993) and pre-run-time scheduling problems (Verhoosel et al. 1991, Verhoosel 1992, 1993a, 1993c) are defined. Additionally, the model is extended to allow exploitation of parallelism from programs, a technique that can be used during assignment and scheduling for meeting timing constraints.     

Supply chain distributed simulation: An efficient architecture for multi-model synchronization

The growing interest in evaluating the overall performance of supply chains leads further and further towards the development of complex simulation models able to answer unsolved questions. In particular, distributed simulation represents one of the tools most frequently used to observe the behaviour of supply chains in order to highlight its lack of efficiency and evaluate new management solutions in a relatively short time.Distributed simulation, however, requires resort to complex platforms, necessary for coordinated time advancing and information exchange management. The technological complexity of these platforms represents a strong limit to the diffusion of this tool in supply chain studies, which, on the contrary, evidence the necessity to develop more simplified methodologies.The paper proposes an efficient architecture (SYNCHRO) which is able to synchronize, simply and securely, simulation models which are located in different geographical areas. The architecture, developed by the authors, has been tested to establish its efficiency when using a variable number of connected units and has demonstrated it can be successfully applied in supply chain contexts.