Recognising the capacities of dynamic reconfiguration for the QoS assurance of running systems in concurrent and parallel environments

Recognizing the impact of reconfiguration on the QoS of running systems is especially necessary for choosing an appropriate approach to dealing with dynamic evolution of mission-critical or non-stop business systems. The rationale is that the impaired QoS caused by inappropriate use of dynamic approaches is unacceptable for such running systems. To predict in advance the impact, the challenge is two-fold. First, a unified benchmark is necessary to expose QoS problems of existing dynamic approaches. Second, an abstract representation is necessary to provide a basis for modeling and comparing the QoS of existing and new dynamic reconfiguration approaches. Our previous work [8] has successfully evaluated the QoS assurance capabilities of existing dynamic approaches and provided guidance of appropriate use of particular approaches. This paper reinvestigates our evaluations, extending them into concurrent and parallel environments by abstracting hardware and software conditions to design an evaluation context. We report the new evaluation results and conclude with updated impact analysis and guidance.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

A Delphi study into the audit challenges of IT governance in the Australian public sector

Information technology (IT) has been playing a powerful role in creating a competitive advantage for organisations over the past decades. This role has become proportionally greater over time as expectations for IT investments to drive business opportunities keep on rising. However, this reliance on IT has also raised concerns about regulatory compliance, governance and security. IT governance (ITG) audit leverages the skills of IS/IT auditors to ensure that IT initiatives are in line with the business strategies. ITG audit emerged as part of performance audit to provide an assessment of the effective implementation of ITG. This research attempts to empirically examine the ITG audit challenges in the public sector. Based on literature and Delphi research, this paper provides insights regarding the impact of, and required effort to address these challenges. The authors also present the ten major ITG audit challenges facing Australian public sector organisations today.

On the reliability of classifying programming tasks using a Neo-Piagetian theory of cognitive development

Recent research has proposed Neo-Piagetian theory as a useful way of describing the cognitive development of novice programmers. Neo-Piagetian theory may also be a useful way to classify materials used in learning and assessment. If Neo-Piagetian coding of learning resources is to be useful then it is important that practitioners can learn it and apply it reliably. We describe the design of an interactive web-based tutorial for Neo-Piagetian categorization of assessment tasks. We also report an evaluation of the tutorial's effectiveness, in which twenty computer science educators participated. The average classification accuracy of the participants on each of the three Neo-Piagetian stages were 85%, 71% and 78%. Participants also rated their agreement with the expert classifications, and indicated high agreement (91%, 83% and 91% across the three Neo-Piagetian stages). Self-rated confidence in applying Neo-Piagetian theory to classifying programming questions before and after the tutorial were 29% and 75% respectively. Our key contribution is the demonstration of the feasibility of the Neo-Piagetian approach to classifying assessment materials, by demonstrating that it is learnable and can be applied reliably by a group of educators. Our tutorial is freely available as a community resource.

A taxonomy of model-based testing approaches

Model-based testing (MBT) relies on models of a system under test and/or its environment to derive test cases for the system. This paper discusses the process of MBT and defines a taxonomy that covers the key aspects of MBT approaches. It is intended to help with understanding the characteristics, similarities and differences of those approaches, and with classifying the approach used in a particular MBT tool. To illustrate the taxonomy, a description of how three different examples of MBT tools fit into the taxonomy is provided.

Real-time risk monitoring in business processes : a sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

Simulation architecture for the design of cooperative collision warning systems

Simulation has been widely used to estimate the benefits of Cooperative Systems (CS) based on Inter-Vehicular Communications (IVC). This paper presents a new architecture built with the SiVIC simulator and the RTMaps™ multisensors prototyping platform. We introduce several improvements from a previous similar architecture, regarding IVC modelisation and vehicles’ control. It has been tuned with on-road measurements to improve fidelity. We discuss the results of a freeway emergency braking scenario (EEBL) implemented to validate our architecture’s capabilities.

Simulation architecture for cooperative ITS applications and augmented perception

Cooperative Systems provide, through the multiplication of information sources over the road, a lot of potential to improve the safety of road users, especially drivers. However, developing cooperative ITS applications requires additional resources compared to non-cooperative applications which are both time consuming and expensive. In this paper, we present a simulation architecture aimed at prototyping cooperative ITS applications in an accurate and detailed, close-to-reality environment; the architecture is designed to be modular and generalist. It can be used to simulate any type of CS applications as well as augmented perception. Then, we discuss the results of two applications deployed with our architecture, using a common freeway emergency braking scenario. The first application is Emergency Electronic Brake Light (EEBL); we discuss improvements in safety in terms of the number of crashes and the severity of crashes. The second application compares the performance of a cooperative risk assessment using an augmented map against a non-cooperative approach based on local-perception only. Our results show a systematic improvement of forward warning time for most vehicles in the string when using the augmented-map-based risk assessment.

An intuitive dashboard for Bayesian network inference

Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

MODAM: A MODular Agent-based Modelling framework

Designing the smart grid requires combining varied models. As their number increases, so does the complexity of the software. Having a well thought architecture for the software then becomes crucial. This paper presents MODAM, a framework designed to combine agent-based models in a flexible and extensible manner, using well known software engineering design solutions (OSGi specification [1] and Eclipse plugins [2]). Details on how to build a modular agent-based model for the smart grid are given in this paper, illustrated by an example for a small network.

Parallel ABM for electricity distribution grids : a case study

This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

Algorithm clustering for multi-algorithm processor design

An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Simulating cooperative systems applications : a new complete architecture

For a decade, embedded driving assistance systems were mainly dedicated to the management of short time events (lane departure, collision avoidance, collision mitigation). Recently a great number of projects have been focused on cooperative embedded devices in order to extend environment perception. Handling an extended perception range is important in order to provide enough information for both path planning and co-pilot algorithms which need to anticipate events. To carry out such applications, simulation has been widely used. Simulation is efficient to estimate the benefits of Cooperative Systems (CS) based on Inter-Vehicular Communications (IVC). This paper presents a new and modular architecture built with the SiVIC simulator and the RTMaps™ multi-sensors prototyping platform. A set of improvements, implemented in SiVIC, are introduced in order to take into account IVC modelling and vehicles’ control. These 2 aspects have been tuned with on-road measurements to improve the realism of the scenarios. The results obtained from a freeway emergency braking scenario are discussed.