Sithu D. Sudarsan

Efficient incident handling in industrial automation through collaborative engineering

We present our monitoring and decision framework for collaborative engineering for globally distributed operation, support, maintenance, and services for industrial automation. The framework provides relevant information to plant operators, engineers, staff and stakeholders to support the handling of incidents, based on semantically-appropriate factors such as personnel skills, physical location of affected equipment and dependencies between plant elements. We discuss the proposed application and present the architecture and implementation. Based on incoming events the framework selects, aggregates and displays information automatically for human processing possibly at distant control centres. For example an alarm in a manufacturing facility can trigger the display of relevant information on multiple devices such as workstations, tablets, or large control-room screens to supervisors and experts. Devices can be potentially in different locations and can comprise different visualization capabilities. The core of our framework uses semantic models and formal methods-based techniques to aggregate and process this information.

Collaborative engineering through integration of architectural, social and spatial models

We present work towards using ontological information to facilitate collaborative tasks during operation, maintenance and service of industrial automation facilities. We use semantic models as an additional layer for a collaboration framework to enable automatic reasoning, decision support and knowledge sharing among multiple parties. Documents such as texts, workflows, images, social media profiles or models of production plants can be semantically annotated to facilitate their ontological classification. Our semantic models comprise behavior and space information, as well as links between documents and from documents to external data collections, such as logs, tables and sensor data. Our semantic models can be used to check consistency, confidentiality and security properties and to support collaborative tasks.

Visualization facilities for distributed and remote industrial automation: VxLab

The Virtual eXperiences Lab at RMIT is a “21st century lab scope,” an enabling platform for research and prototyping in industrial automation, focusing on software engineering, next generation human-machine interaction experiences, user interfaces, and training. VxLab combines high resolution visualization, industrial automation facilities and cloud-based simulation servers in a dedicated private network. In this paper we describe the architecture, use cases, and research and innovation projects. We also present experiences applying VxLab. We present capabilities, include connected infrastructure provided by industry partners.

Spatio-temporal reasoning and decision support for smart energy systems

In this paper, we present an event handling framework for managing smart-grids and renewable energy installations: SmartSpace. Our framework aims at supporting decisions of human stakeholders, by providing adequate information to them. Different datasources feed into our framework and a variety of analysis and decision steps are supported. We are discussing potential data sources for decisions around smart energy systems and are focusing on spatio-temporal models of the involved data and operations to reason about them. Our models help to provide a semantic context for the data. Furthermore, we discuss the formalization of customized rules. Rules allow the specification of conditions under which information is provided to stakeholders. We exemplify our ideas and present our demonstrator which includes visualization capabilities.

Using normalized compression distance to measure the evolutionary stability of software systems

Software evolutionary stability has become an important issue in software maintenance and evolution. It is directly related to software reusability, maintainability and evolvability. In reported prior research, software evolutionary stability has been measured with architecture-level metrics, including reference points and program-level metrics, such as number of modules and number of lines of code. In this paper, information-level metrics based on Kolmogorov complexity are used to measure the differences between versions of software products. Using normalized compression distance, various evolutionary stability metrics of software artifacts are defined: version stability, branch stability, structure stability and aggregate stability. Case studies are performed on two open-source products, Apache HTTP server and Apache Ant build tool. The results from this study show that information-level evolutionary stability metrics can be used together with architecture-level metrics and program-level metrics to assist monitoring the software evolution process, as well as identifying stable or unstable software artifacts.

Societal-Consciousness in the Computing Curricula: A Time for Serious Introspection

This paper addresses the growing need for inculcating appropriate ethics within the computing curriculum by fostering the development of a societally-conscious ethical framework among our students to address the use of information technology vis-a-vis government, business and society. We propose a new integrated model based approach (IDEA) and suggest its adoption to encourage students on reflecting upon the social and ethical ramifications of technology, beyond the narrow, project-focused tunnel vision that currently (subliminally) exists in many computing curricula, and in particular, in todays profit-focused, consulting and contract-based software industry.

Discovering likely mappings between APIs using text mining

Developers often release different versions of their applications to support various platform/programming-language application programming interfaces (APIs). To migrate an application written using one API (source) to another API (target), a developer must know how the methods in the source API map to the methods in the target API. Given a typical platform or language exposes a large number of API methods, manually writing API mappings is prohibitively resource-intensive and may be error prone. Recently, researchers proposed to automate the mapping process by mining API mappings from existing code-bases. However, these approaches require as input a manually ported (or at least functionally similar) code across source and target APIs. To address the shortcoming, this paper proposes TMAP: Text Mining based approach to discover likely API mappings using the similarity in the textual description of the source and target API documents. To evaluate our approach, we used TMAP to discover API mappings for 15 classes across: 1) Java and C# API, and 2) Java ME and Android API. We compared the discovered mappings with state-of-the-art source code analysis based approaches: Rosetta and StaMiner. Our results indicate that TMAP on average found relevant mappings for 57% more methods compared to previous approaches. Furthermore, our results also indicate that TMAP on average found exact mappings for 6.5 more methods per class with a maximum of 21 additional exact mappings for a single class as compared to previous approaches.

Medical Software – Issues and Best Practices

The design and functional complexity of medical software has increased during the past 50 years, evolving from the use of a metronome circuit for the initial cardiac pacemaker to functions that include electrocardiogram (EKG) analysis, laser surgery, and networked systems for monitoring patients across various healthcare environments. Software has become ubiquitous in healthcare applications, as is evident from its prevalent use for controlling medical devices, maintaining electronic patient health data, and enabling healthcare information technology (HIT) systems. As the software functionality becomes more intricate, concerns arise regarding efficacy, safety and reliability. It thus becomes imperative to adopt an approach or methodology based on best engineering practices to ensure that the possibility of any defect or malfunction in these devices is minimized.

Impact of Duty Cycle Variation on WSNs

Wireless Sensor Networks (WSNs) operate with varying duty cycles to meet their application-specific criteria such as the availability, reliability, and the life expectancy of the system. This variation in duty cycle consequently affects the system characteristics including the interference and collision of signals. However, the sensitivity to physical jamming attacks with respect to duty cycle of the network is not widely explored area of research. This paper presents a detailed analysis of the effect of the duty cycle to the interference and collision of signals in the WSNs. In particular, our simulation model depicts a log normal shadowing model to represent a realistic wireless channel and observe the effects of duty cycle variation when a physical jamming attack is launched on the network using a compromised node. Our results show that setting the duty cycle at predetermined value would help minimize the packet drop ratio of the network.

Modelling and simulation: The basis for education enrichment and software design

As the internet continually eliminates geographic boundaries, the concept of doing business within a single country is giving way to companies focusing on competing in an international marketplace. As modelling and simulation professionals, we have the most unique opportunities to become true global visionaries and be highly effective in providing fundamental opportunities that all our employers expect from our students. The future of the various professions in the information technology (IT) business relies greatly on innovative modelling and simulation practices that not merely enhance our ability to graduate good application programmers  – these skills have now become commodities that can be either outsourced or automated. We are now more able to graduate students who are comfortable with the theory, build their higher-order thinking (HOT) skills and blend these with the necessary practice through the understanding of business and cultural issues involved; while being able to effectively share, communicate, articulate and advance their ideas for innovative products and solutions. Since good educational preparation is one of the primary means for us to prepare our future workforce; modelling and simulation as an oft-repeated, practice-driven learnt skill can help our students gain the necessary HOT skills to compete globally for highly skilled technology based jobs. We focus in this paper on the models and provide a model for educational innovation using modelling and simulation as a vehicle for software development. We illustrate this with a simple example of designing well co-ordinated software systems. Using a simple Petri net based-approach we develop a model-based, co-ordination-focused, requirements-driven guidelines for co-ordinated software design and testing.