Biotope: an integrated framework for simulating distributed multiagent computational systems

The study of distributed computational systems issues, such as heterogeneity, concurrency, control, and coordination, has yielded a number of models and architectures, which aspire to provide satisfying solutions to each of the above problems. One of the most intriguing and complex classes of distributed systems are computational ecosystems, which add an "ecological" perspective to these issues and introduce the characteristic of self-organization. Extending previous research work on self-organizing communities, we have developed Biotope, which is an agent simulation framework, where each one of its members is dynamic and self-maintaining. The system provides a highly configurable interface for modeling various environments as well as the "living" or computational entities that reside in them, while it introduces a series of tools for monitoring system evolution. Classifier systems and genetic algorithms have been employed for agent learning, while the dispersal distance theory has been adopted for agent replication. The framework has been used for the development of a characteristic demonstrator, where Biotope agents are engaged in well-known vital activities-nutrition, communication, growth, death-directed toward their own self-replication, just like in natural environments. This paper presents an analytical overview of the work conducted and concludes with a methodology for simulating distributed multiagent computational systems.     

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.     

On the combination of top-down and bottom-up methodologies for the design of coordination mechanisms in self-organising systems

In resource-flow systems, e.g. production lines, agents are processing resources by applying capabilities to them in a given order. Such systems benefit from self-organization as they become easier to manage and more robust against failures. In this paper, we demonstrate the conception of a decentralized coordination process for resource-flow systems and its integration into an agent-based software system. This process restores a system’s functionality after a failure by propagating information about the error through the system until a fitting agent is found that is able to perform the required function. The mechanism has been designed by combining a top-down design approach for self-organizing resource-flow system and a systemic development framework for the development of decentralized, distributed coordination processes. Using the latter framework, a process is designed and integrated in a system realization that follows the former conceptual model. Evaluations of convergence as well as performance of the mechanism and the required amount of redundancy of the system are performed by simulations.     

Design and implementation of a multiagent stock trading system

Stock trading is one of the key items in an economy and estimating its behavior and taking the best decision in it are among the most challenging issues. Solutions based on intelligent agent systems are proposed to cope with those challenges. Agents in a multiagent system (MAS) can share a common goal or they can pursue their own interests. That nature of MASs exactly fits the requirements of a free market economy. Although existing studies include noteworthy proposals on agent‐based market simulation and researchers discuss theoretical design issues of agent‐based stock exchange systems, unfortunately only a very few of the studies consider exact development and implementation of multiagent stock trading systems within the software engineering perspective and guides to the software engineers for constructing such software systems starting from scratch. To fill this gap, in this paper, we discuss the development of a multiagent‐based stock trading system by taking into consideration software design according to a well‐defined agent oriented software engineering methodology and implementation with a widely‐used MAS software development framework. Each participant in the system is first designed as belief–desire–intention agents with their facts, goals, and plans, and then belief–desire–intention reasoning and behavioral structure of the designed agents are implemented. Lessons learned during design and development within the software engineering perspective and evaluation of the implemented multiagent stock exchange system are also reported. Copyright © 2011 John Wiley & Sons, Ltd.     

智能自组织系统仿真与应用

信息技术的发展给现代企业带来了许多复杂决策问题,而利用传统的决策理论求解将具有极大的局限性。文章介绍了基于机器学习与进化算法的一个智能自组织系统仿真模型,这一模型不仅具有复杂系统机理研究的理论意义,也可以有效地应用于企业决策问题中,使决策模型具有从环境中自发学习与进化的能力。首先,文章介绍了三层智能自组织系统仿真的基本原理模型;接着介绍了模型在典型复杂企业决策问题中的实现原理、建模过程、算法实现等;最后,对模型的仿真应用结果进行了参数实验与讨论,仿真模型取得了令人满意的决策支持效果。     

对等网络中应用事件代理实现基于主题的情报分发*

针对集中式情报系统存在单点失效而导致整体失效、情报中心须事先确定,其角色和与系统拓扑过于紧耦合、以及信息融合能力不能满足多信息源的处理要求等问题,结合Petri网分析和描述情报分发过程,提出一种构建于对等网络之上的基于主题的自组织情报分发模型,并给出融合和分发核心算法。应用事件代理自组织成Gnutella P2P网络进行验证,结果显示系统能够较好解决以上问题,同时具有较高的时效。     

Integration of Information Resources Containing Data on the Properties of Substances and Materials: Practical Implementation and Existing Tools

New methods of integrating scientific data on the properties of substances and materials that apply modern information technologies are analysed. The capabilities of systems created using the Semantic Web and Big Data are explored. Despite some differences in the tasks that are solved, both approaches are oriented towards working with large arrays of web-distributed, structurally heterogeneous data. Several data-integration platforms that have been developed in recent years, including a system designed by the authors, are studied. It is concluded that currently none of the integration systems can fully satisfy specific the requirements of scientific data. Nevertheless, several software elements and technological solutions are of interest and can support the implementation of a project to integrate scientific data on properties of substances and materials.     

Weaving together requirements and architectures

Software development organizations often choose between alternative starting points-requirements or architectures. This invariably results in a waterfall development process that produces artificially frozen requirements documents for use in the next step in the development life cycle. Alternatively, this process creates systems with constrained architectures that restrict users and handicap developers by resisting inevitable and desirable changes in requirements. The spiral life-cycle model addresses many drawbacks of a waterfall model by providing an incremental development process, in which developers repeatedly evaluate changing project risks to manage unstable requirements and funding. An even finer-grain spiral life cycle reflects both the realities and necessities of modern software development. Such a life cycle acknowledges the need to develop software architectures that are stable, yet adaptable, in the presence of changing requirements. The cornerstone of this process is that developers craft a system's requirements and its architecture concurrently, and interleave their development     

Strategies for unsupervised multimedia processing: self-organizing trees and forests

In this article, we explore a new family of neural network architectures that have a basis in self-organization, yet are somewhat free from many of the constraints typical of other well-known self-organizing architectures. Within this family, the basic processing unit is known as the self-organizing tree map (SOTM). We will look at how this model has evolved since its inception in 1995, how it has inspired new models, and how it is being applied to complex multimedia research problems in digital asset management and microbiological image analysis.     

An overview of Dynamic Software Product Line architectures and techniques: Observations from research and industry

Over the last two decades, software product lines have been used successfully in industry for building families of systems of related products, maximizing reuse, and exploiting their variable and configurable options. In a changing world, modern software demands more and more adaptive features, many of them performed dynamically, and the requirements on the software architecture to support adaptation capabilities of systems are increasing in importance. Today, many embedded system families and application domains such as ecosystems, service-based applications, and self-adaptive systems demand runtime capabilities for flexible adaptation, reconfiguration, and post-deployment activities. However, as traditional software product line architectures fail to provide mechanisms for runtime adaptation and behavior of products, there is a shift toward designing more dynamic software architectures and building more adaptable software able to handle autonomous decision-making, according to varying conditions. Recent development approaches such as Dynamic Software Product Lines (DSPLs) attempt to face the challenges of the dynamic conditions of such systems but the state of these solution architectures is still immature. In order to provide a more comprehensive treatment of DSPL models and their solution architectures, in this research work we provide an overview of the state of the art and current techniques that, partially, attempt to face the many challenges of runtime variability mechanisms in the context of Dynamic Software Product Lines. We also provide an integrated view of the challenges and solutions that are necessary to support runtime variability mechanisms in DSPL models and software architectures.     

Multiagent systems and information retrieval our experience with X.MAS

Autonomous agents and multiagent systems have been successfully applied to a number of problems and have been largely used in different application fields. In particular, in this paper we are interested in information retrieval. In fact, in this field multiagent solutions are very useful and effective since they decouple the problem in a network of software agents that interact to solve problems that are beyond the individual capabilities or knowledge. In so doing, multiagent systems allow to overwhelm typical problems of single agent and centralized approaches. To discuss the lesson learnt in using the multiagent technology in the field of information retrieval, in this paper, we present our experience in using X.MAS, a generic multiagent architecture aimed at retrieving, filtering and reorganizing information according to user interests. To this end, after presenting X.MAS, we illustrate six applications built upon it. Our conclusion is that multiagent technology is quite effective to design and realize concrete information retrieval applications.     

Distributed nonlinear control algorithms for network consensus

In this paper, we develop a thermodynamic framework for addressing consensus problems for nonlinear multiagent dynamical systems with fixed and switching topologies. Specifically, we present distributed nonlinear static and dynamic controller architectures for multiagent coordination. The proposed controller architectures are predicated on system thermodynamic notions resulting in controller architectures involving the exchange of information between agents that guarantee that the closed-loop dynamical network is consistent with basic thermodynamic principles.     

Portability in MAC protocol and transceiver software implementations for LR‐WPAN platforms

In a variety of emerging networked computing system domains over the years, there have been bursts of activity on new medium access control (MAC) protocols, as new communication transceiver technologies with greater data‐movement performance or lower power dissipation have been introduced. To enable implementations flexible to evolving standards and improving application‐domain insight, such MAC protocols are typically initially implemented in software, and interface between applications or system software, typically executing on an embedded processor or microcontroller, and the evolving radio transceiver hardware. Many challenges exist in implementing MAC protocols across evolving or competing transceiver hardware implementations and processor architectures. Some of these challenges are peculiar to the requirements of MAC protocols, and others are a result of the plethora of system and processor architectures in the embedded systems domain. This article studies the challenges facing software implementations of MAC protocols running on embedded microcontrollers, and interfacing with radio transceiver hardware. Experience with an implementation of the IEEE 802.15.4 MAC across three hardware platforms with different processor, system, and systems software architectures is presented, focusing on implementation approach and interfaces. Pitfalls are pointed out, and guidelines are provided for ensuring that new MAC implementations are easily portable across processor architectures and transceiver hardware. Copyright © 2010 John Wiley & Sons, Ltd.     

Agent-based modeling of ancient societies and their organization structure

Some of the most interesting questions one can ask about early societies, are about people and their relations, and the nature and scale of their organization. In this work, we attempt to answer such questions with approaches introduced by multiagent systems. Specifically, we developed a generic agent-based model (ABM) for simulating ancient societies. Unlike most existing ABMs used in archaeology, our model includes agents that are autonomous and utility-based. Our model can (and does) also incorporate different social organization paradigms and technologies used in ancient societies. Equipped with such paradigms, our model allows us to explore the transition from a simple to a more complex society by focusing on the historical social dynamics—i.e., the flexibility and evolution of power relationships depending on social context and time. As a case study, we employ our model to evaluate the impact of the implemented social and technological paradigms on an artificial Early Bronze Age “Minoan” society located at a particular region of the island of Crete. Model parameter choices are based on archaeological evidence and studies, but are not biased towards any specific assumption. Results over a number of different simulation scenarios demonstrate an impressive sustainability for settlements consisting of and adopting a socio-economic organization model based on self-organization, and which was inspired by a recent framework for modern self-organizing agent organizations. This is the first time a self-organization approach is incorporated in an archaeology ABM system.     

Model-based engineering for change-tolerant systems

Developing and evolving today’s systems are often stymied by the sheer size and complexity of the capabilities being developed and integrated. At one end of the spectrum, we have sophisticated agent-based software with hundreds of thousands of collaborating nodes. These require modeling abstractions relevant to their complex workflow tasks as well as predictable transforms and mappings for the requisite elaborations and refinements that must be accomplished in composing these systems. At the other end of the spectrum, we have ever-increasing capabilities of reconfigurable hardware devices such as field-programmable gate arrays to support the emerging adaptability and flexibility needs of these systems. From a model-based engineering perspective, these challenges are very similar; both must move their abstraction and reuse levels up to meet growing productivity and quality objectives. Model-based engineering and software system variants such as the model-driven architecture (MDA) are increasingly being applied to systems development as the engineering community recognizes the benefits of managing complexity, separating key concerns, and automating transformations from high-level abstract requirements down through the implementation. However, there are challenges when it comes to establishing the correct boundaries for change-tolerant parts of the system. Capabilities engineering (CE) is a promising approach for defining long-lived components of a system to ensure some sense of change tolerance. For innovative initiatives such as the National Aeronautics and Space Administration (NASA)’s autonomous nanotechology swarms (ANTS), the development and subsequent evolution of such systems are of considerable importance as their missions involve complex, collaborative behaviors across distributed, reconfigurable satellites. In this paper, we investigate the intersection of these two technologies as they support the development of complex, change-tolerant systems. We present an effective approach for bounding computationally independent models so that, as they transition to the architecture, capabilities-based groupings of components are relevant to the change-tolerant properties that must convey in the design solution space. The model-based engineering approach is validated via a fully functional prototype and verified by generating nontrivial multiagent systems and reusing components in subsequent systems. We build off of this research completed on the collaborative agent architecture, discuss the CE approach for the transition to architecture, and then examine how this will be applied in the reconfigurable computing community with the new National Science Foundation Center for High-Performance Reconfigurable Computing. Based on this work and extrapolating from similar efforts, the model-based approach shows promise to reduce the complexities of software evolution and increase productivity—particularly as the model libraries are populated with canonical components.     

Intelligent technologies of high-performance computing

This article analyzes mathematical and technological problems that arise in performing computational experiments on modern high-performance computers (supercomputers). As a means of overcoming the difficulties associated with the analysis and solution of computer model problems under conditions of approximate initial data on computers with parallel architectures, intelligent technologies are proposed that are based on intelligent software supported by architectural decisions of an intelligent computer and predictive system software.     

The Real-Time Process Algebra (RTPA)

The real-time process algebra (RTPA) is a set of new mathematical notations for formally describing system architectures, and static and dynamic behaviors. It is recognized that the specification of software behaviors is a three-dimensional problem known as: (i) mathematical operations, (ii) event/process timing, and (iii) memory manipulations. Conventional formal methods in software engineering were designed to describe the 1-D (type (i)) or 2-D (types (i) and (iii)) static behaviors of software systems via logic, set and type theories. However, they are inadequate to address the 3-D problems in real-time systems. A new notation system that is capable to describe and specify the 3-D real-time behaviors, the real-time process algebra (RTPA), is developed in this paper to meet the fundamental requirements in software engineering.RTPA is designed as a coherent software engineering notation system and a formal engineering method for addressing the 3-D problems in software system specification, refinement, and implementation, particularly for real-time and embedded systems. In this paper, the RTPA meta-processes, algebraic relations, system architectural notations, and a set of fundamental primary and abstract data types are described. On the basis of the RTPA notations, a system specification method and a refinement scheme of RTPA are developed. Then, a case study on a telephone switching system is provided, which demonstrates the expressive power of RTPA on formal specification of both software system architectures and behaviors. RTPA elicits and models 32 algebraic notations, which are the common core of existing formal methods and modern programming languages. The extremely small set of formal notations has been proven sufficient for modeling and specifying real-time systems, their architecture, and static/dynamic behaviors in real-world software engineering environment.     

嵌入式网络中代码移动性的研究

随着嵌入式应用领域的不断扩展,在越来越多的应用中要求实现嵌入式设备的网络化.网络化的需求对嵌入式系统软件的开发提出了新的要求.传统的嵌入式网络的编程方式效率低下、调试手段单一,已经难以满足快速开发、快速部署等现代嵌入式系统的开发要求.针对传统的嵌入式网络软件的开发方式,提出了将代码移动技术应用于嵌入式环境下的网络开发,实现了嵌入式的可编程网络;并针对嵌入式环境的特点提出了几种可能的实现手段,然后进行了比较.最后用实例说明了代码移动在车身控制系统开发中带来的益处.     

基于政策自组织系统的软件agent体系结构及其实现

当前自组织系统软件工程面临的一个重要挑战,就是如何设计适宜的个体交互行为来满足自组织系统的宏观涌现需求。针对此问题,提出了一种基于政策的自组织多agent系统的开发方法,此方法通过政策调节引导agent的行为,以期在系统层面得到用户所需求的宏观涌现结果。开发这类系统的核心问题是如何构造系统中的软件agent,使得agent能够感知、理解系统政策,并在遵循政策的前提下实现行为的自主决策。提出了一种基于政策自组织多agent系统的软件agent体系结构,并基于该体系结构设计了运行机制及行为决策算法。通过软件方式实现了一个基于政策的自组织多agent系统开发平台原型,并通过案例实现说明了体系结构、运行机制的有效性。