Towards a shared systems model of stakeholders in environmental conflict

Developing a shared mental model of stakeholders in conflict is a challenge in environmental conflict management. In this paper, we describe the development of a shared systems model of stakeholders in environmental conflict in the Transmission Gully project, a large‐scale transport infrastructure project in the Wellington region of New Zealand. Selected stakeholders of this project partook in generating this shared model, in the form of a causal loop diagram. This model was then analysed qualitatively to provide different insights into potential system behaviours.     

Systematic evaluation of peer‐to‐peer systems using PeerfactSim.KOM

Comparative evaluations of peer‐to‐peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large‐scale networks. In order to support this work, we present the peer‐to‐peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer‐to‐peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large‐scale peer‐to‐peer networks. We enhanced PeerfactSim.KOM with a fine‐grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer‐to‐peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post‐processing. Copyright © 2015 John Wiley & Sons, Ltd.     

A survey of self‐healing systems frameworks

Rising complexity within multi‐tier computing architectures remains an open problem. As complexity increases, so do the costs associated with operating and maintaining systems within these environments. One approach for addressing these problems is to build self‐healing systems (i.e. frameworks) that can autonomously detect and recover from faulty states. Self‐healing systems often combine machine learning techniques with closed control loops to reduce the number of situations requiring human intervention. This is particularly useful in situations where human involvement is both costly to develop, and a source of potential faults. Therefore, a survey of self‐healing frameworks and methodologies in multi‐tier architectures is provided to the reader. Uniquely, this study combines an overview of the state of the art with a comparative analysis of the computing environment, degree of behavioural autonomy, and organisational requirements of these approaches. Highlighting these aspects provides for an understanding of the different situational benefits of these self‐healing systems. We conclude with a discussion of potential and current research directions within this field. Copyright © 2014 John Wiley & Sons, Ltd.     

An optimization algorithm for production systems

As the scale of rule-based expert systems increases, the efficiency of production systems becomes a pressing concern. Recently developed production systems thus enable users to specify an appropriate ordering or clustering of join operations. Various efficiency heuristics have been introduced to optimize production rules manually. However, since the heuristics often conflict With each other, users have to proceed by trial and error. The problem addressed in this paper is how to automatically determine efficient join structures for production system programs. Our algorithm does not directly apply efficiency heuristics to programs, but rather enumerates possible join structures under various constraints and selects the best one. For this purpose, the cost model for production systems is introduced to estimate the run-time cost of join operations. Evaluation results demonstrate that the proposed algorithm can generate programs that are as efficient as those obtained by manual optimization, and thus can reduce the burden of manual optimization     

Using meta‐modeling in design and implementation of component‐based systems: the SOFA case study

To allow efficient and user‐friendly development of a component‐based application, component systems have to provide a rather complex development infrastructure, including a tool for component composition, component repository, and a run‐time infrastructure. In this paper, we present and evaluate benefits of using meta‐modeling during the process of defining a component system and also during creation of the development and run‐time infrastructures. Most of the presented arguments are based on a broad practical experience with designing the component systems SOFA and SOFA 2; the former designed in a classical ad hoc ‘manual’ way, whereas the latter with the help of meta‐modeling. Copyright © 2010 John Wiley & Sons, Ltd.     

Distributed robust stabilization of networked multiagent systems with strict negative imaginary uncertainties

This paper deals with the distributed robust stabilization problem for networked multiagent systems with strict negative imaginary (SNI) uncertainties. Communication among agents in the network is modelled by an undirected graph with at least one self‐loop. A protocol based on relative state measurements of neighbouring agents and absolute state measurements of a subset of agents is considered. This paper shows how to design the protocol parameters such that the uncertain closed‐loop networked multiagent system is robustly stable against any SNI uncertainty within a certain set for various different network topologies. Tools from negative imaginary (NI) theory are used as an aid to simplify the problem and synthesise the protocol parameters. We show that a state, input, and output transformation preserves the NI property of the network. Consequently, a necessary and sufficient condition for the transfer function matrix of the nominal closed‐loop networked system to be NI and satisfy a DC gain condition is that multiple reduced‐order equivalent systems be NI and satisfy a DC gain condition simultaneously. Based on the reduced‐order systems, we derive sufficient conditions in an LMI framework which ensure the existence of a protocol satisfying the desired objectives. A numerical example is given to confirm the effectivenesses of the proposed results.     

SPL Conqueror: Toward optimization of non-functional properties in software product lines

A software product line (SPL) is a family of related programs of a domain. The programs of an SPL are distinguished in terms of features, which are end-user visible characteristics of programs. Based on a selection of features, stakeholders can derive tailor-made programs that satisfy functional requirements. Besides functional requirements, different application scenarios raise the need for optimizing non-functional properties of a variant. The diversity of application scenarios leads to heterogeneous optimization goals with respect to non-functional properties (e.g., performance vs. footprint vs. energy optimized variants). Hence, an SPL has to satisfy different and sometimes contradicting requirements regarding non-functional properties. Usually, the actually required non-functional properties are not known before product derivation and can vary for each application scenario and customer. Allowing stakeholders to derive optimized variants requires us to measure non-functional properties after the SPL is developed. Unfortunately, the high variability provided by SPLs complicates measurement and optimization of non-functional properties due to a large variant space. With SPL Conqueror, we provide a holistic approach to optimize non-functional properties in SPL engineering. We show how non-functional properties can be qualitatively specified and quantitatively measured in the context of SPLs. Furthermore, we discuss the variant-derivation process in SPL Conqueror that reduces the effort of computing an optimal variant. We demonstrate the applicability of our approach by means of nine case studies of a broad range of application domains (e.g., database management and operating systems). Moreover, we show that SPL Conqueror is implementation and language independent by using SPLs that are implemented with different mechanisms, such as conditional compilation and feature-oriented programming.     

A storyteller's guide to problem‐based learning for information systems management education

More than a decade ago, evidence‐based recommendations emerged regarding what students of information systems (IS) management education should learn and how should they learn it. Although these recommendations for how IS management should be taught remain valid, they need to be updated to account for recent advances in technologies that enable multimedia learning. Promoters of such technologies promise enhanced cognitive and behavioural outcomes, but this promise remains unreached, reflecting the underdeveloped multimedia‐enabled learning literature. To help attain this promise and rejuvenate the literature of multimedia learning, we offer a roadmap for new areas of research that would inform the design and use of a novel form of multimedia materials: narrative animated videos (NAVs). NAVs represent a form of self‐determined learning that features immersive, story‐based content. We argue that their use will intrinsically motivate users to process the materials to completion, thereby enhancing cognitive and behavioural outcomes, and thus catalysing the effectiveness of the team‐based learning and self‐regulated learning modes for problem‐based learning (PBL) delivery of IS management education. This compelling roadmap corresponds to meaningful IS research because it centres on a topic that the IS literature has long examined—the role of user motivation—and because its theoretical contributions invite specific paths of research for informing the design of the PBL delivery of IS management education within an information systems artefact.     

A framework for developing measurement systems and its industrial evaluation

As in every engineering discipline, metrics play an important role in software development, with the difference that almost all software projects need the customization of metrics used. In other engineering disciplines, the notion of a measurement system (i.e. a tool used to collect, calculate, and report quantitative data) is well known and defined, whereas it is not as widely used in software engineering. In this paper we present a framework for developing custom measurement systems and its industrial evaluation in a software development unit within Ericsson. The results include the framework for designing measurement systems and its evaluation in real life projects at the company. The results show that with the help of ISO/IEC standards, measurement systems can be effectively used in software industry and that the presented framework improves the way of working with metrics. This paper contributes with the presentation of how automation of metrics collection and processing can be successfully introduced into a large organization and shows the benefits of it: increased efficiency of metrics collection, increased adoption of metrics in the organization, independence from individuals and standardized nomenclature for metrics in the organization.     

Integration strategy for distributed intelligent systems

In this article, we describe a new framework for designing real-time intelligent control systems. An integrated intelligent system is a large knowledge integration environment that consists of both symbolic reasoning systems (expert systems) and numerical computation packages. These modular software programs are controlled by a meta-system which manages the selection, operation, and communication of these programs. This new architecture can serve as a universal configuration to develop high-performance intelligent systems for many complicated application domains in the real-time manufacturing process. As an example, an intelligent optimal control is utilized to illustrate the integrated intelligent control system.     

Data race avoidance and replay scheme for developing and debugging parallel programs on distributed shared memory systems

Distributed shared memory (DSM) allows parallel programs to run on distributed computers by simulating a global virtual shared memory, but data racing bugs may easily occur when the threads of a multi-threaded process concurrently access the physically distributed memory. Earlier tools to help programmers locate data racing bugs in non-DSM parallel programs are not easily applied to DSM systems. This study presents the data race avoidance and replay scheme (DRARS) to assist debugging parallel programs on DSM or multi-core systems. DRARS is a novel tool which controls the consistency protocol of the target program, automatically preventing a large class of data racing bugs when the parallel program is subsequently run, obviating much of the need for manual debugging. For data racing bugs that cannot be avoided automatically, DRARS performs a deterministic replay-type function on DSM systems, faithfully reproducing the behavior of the parallel program during run time. Because one class of data racing bugs has already been eliminated, the remaining manual debugging task is greatly simplified. Unlike previous debugging methods, DRARS does not require that the parallel program be written in a specific style or programming language. Moreover, DRARS can be implemented in most consistency protocols. In this paper, DRARS is realized and verified in real experiments using the eager release consistency protocol on a DSM system with various applications.     

Autonomic self healing and recovery informed by environment knowledge

An important goal of autonomic computing is the development of computing systems that are capable of self healing with a minimum of human intervention. Typically, recovery from even a simple fault will require knowledge of the environment in which a computing system operates. To meet this need, we present an approach to self healing and recovery informed by environment knowledge that combines case based reasoning (CBR) and rule based reasoning. Specifically, CBR is used for fault diagnosis and rule based reasoning for fault remediation, recovery, and referral. We also show how automated information gathering from available sources in a computing system’s environment can increase problem solving efficiency and help to reduce the occurrence of service failures. Finally, we demonstrate the approach in an intelligent system for fault management in a local printer network.     

The Implementation Technology of the Mercury Debugger

Every programming language needs a debugger. Mercury now has three debuggers: a simple procedural debugger similar to the tracing systems of Prolog implementations, a prototype declarative debugger, and a debugger based on the idea of automatic trace analysis. In this paper, we present the shared infrastructure that underlies the three debuggers, and describe the implementation of the procedural debugger. We give our reasons for each of our main design decisions, and show how several of these decisions are rooted in our experience with the debugging of large programs working with large data structures.     

Output regulation by postprocessing internal models for a class of multivariable nonlinear systems

In this paper we propose a new design paradigm, which employs a postprocessing internal model unit, to approach the problem of output regulation for a class of multivariable minimum‐phase nonlinear systems possessing a partial normal form. Contrary to previous approaches, the proposed regulator handles control inputs of dimension larger than the number of regulated variables, provided that a controllability assumption holds, and can employ additional measurements that need not to vanish at the ideal error‐zeroing steady state, but that can be useful for stabilization purposes or to fulfill the minimum‐phase requirement. Conditions for practical and asymptotic output regulation are given, underlying how in postprocessing schemes the design of internal models is necessarily intertwined with that of the stabilizer.     

A novel ecological network‐based computation platform as a grid middleware system

Next‐generation grid systems where the emphasis shifts to distributed global collaboration, a service‐oriented approach, and information layer issues exhibit a strong sense of automation. Requirements for these systems resemble the self‐organizing and the self‐healing properties of natural ecosystems. Inspired by this resemblance, we introduce some key ecological concepts and mechanisms into the design for the third‐generation grid systems. In this article, a novel Ecological Network‐based Grid Middleware (ENGM), which is based on Ecological Network Computing Environment (ENCE), is proposed. First, we discuss how to design the ENCE by agent‐oriented approaches based on the key concepts and principles of ecosystems. ENCE provides a new computing and problem‐solving paradigm by combining natural ecosystem mechanisms with agent technologies. Then, we design the ENGM with built‐in mechanisms to support desirable requirements of new grid systems, namely scalability, adaptability, self‐organization, simplicity, and survivability. Based on Jeffery's conceptual model, we also present a corresponding grid‐computing prototype that embeds ENGM layers from the implementation point of view. The ENGM will be useful to address the challenges of the third‐generation grid systems. Finally, as a demonstration, we built an ENGM platform‐based commercial grid service environment and developed a prototype of enterprise supply chain management system. The experimental results demonstrate that the proposed ENGM satisfies the requirements of the next‐generation grid and is suitable for new generation grid applications. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 859–884, 2004.     

Observer‐based fault diagnosis and self‐restore control for systems with measurement delays

The problems of fault diagnosis and fault‐tolerant control are considered for systems with measurement delays. In contrast to the present fault diagnosis and fault‐tolerant control approaches, which consider only the input delay and/or state delay, the main contribution of this paper consists of proposing a new observer‐based reduced‐order fault diagnoser construction approach and a design approach to dynamic self‐restore fault‐tolerant control law for systems with measurement delays. First, the time‐delay system is transformed into a delay‐free system in form by a special functional‐based delay‐free transformation approach for measurement delays. Then, the fault diagnosis is realized online via the proposed reduced‐order fault diagnoser. Using the results of fault diagnosis, two dynamic self‐restore control laws are designed to make the system isolated from faults. A numerical example demonstrates the feasibility and validity of the proposed scheme. © 2012 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An algorithm for the robust exponential stabilization of a class of switched systems

In this paper, we consider continuous‐time switched systems whose subsystems are linear, or, more generally, homogeneous of degree one. For that class of systems, we present a control algorithm that under certain conditions generates switching signals that globally exponentially stabilizes the switched system, even in the case in which there are model uncertainties and/or measurement errors, provided that the bounds of that uncertainties and errors depend linearly on the norm of the state of the system and are small enough in a suitable sense. We also show that in the case in which the measurement errors and the model uncertainties are bounded, the algorithm globally exponentially stabilizes the system in a practical sense, with a final error which depends linearly on the bounds of both the model uncertainties and the measurement errors. In other words, the closed‐loop system is exponentially input‐to‐state‐stable if one considers the perturbations and output measurements bounds as inputs. For switched linear systems, under mild observability conditions, we design an observer whose state‐estimation drives the control algorithm to exponentially stabilize the system in absence of perturbations and to stabilize it in an ultimately bounded way when the perturbations and the output measurement errors are bounded. Finally, we illustrate the behavior of the algorithm by means of simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

A proposal to apply inductive logic programming to self‐healing problem in grid computing: How will it work?

As computation systems get extremely large and complex, failure diagnosis becomes even more complex. To cope with this ever increasing complexity of managing heterogeneous systems—such as grids and nowadays clouds—systems should manage their own behavior themselves. This vision of self‐managing systems also referred to as autonomic computing (AC) aims to allow systems to recover themselves from various failures or malfunctions. This is known as self‐healing (SH) and is one of the requirements of AC. However, dealing with these complex failure scenarios is always an open challenge. Dealing with this challenge requires prediction and control through a number of automated learning and proactive actions. In this work, we present the usage of a relational learning method known as inductive logic programming, for prediction and root casual analysis, and the development of an SH component. Copyright © 2011 John Wiley & Sons, Ltd.     

A real-time responsiveness measurement method of linux-based mobile systems for P2P cloud systems

Linux-based mobile computing systems such as robots, electronic control devices, and smart-phone are the most important types of P2P cloud systems in recent days. To improve the overall performance of networked systems, each mobile computing system requires real-time characteristics. For this reason, mobile computing system developers want to know how well real-time responsiveness is supported; several real-time measurement tools have been proposed. However, those previous tools have their own measurement schemes and we think that the results from those models do not show how responsive those systems are. In this paper, we propose ELRM, a new real-time measurement method that has clear measurement interval definitions and an accurate measurement method for real-time responsiveness. We evaluate ELRM on various mobile computing systems and compare it with other existing models. As a result, our method can obtain more accurate and intuitive real-time responsiveness measurement results.