ORCID Profile
0000-0002-2730-9150
Current Organisation
Deakin University
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Publisher: IEEE
Date: 12-2010
DOI: 10.1109/EUC.2010.106
Publisher: IEEE
Date: 09-2015
Publisher: Wiley
Date: 04-11-2010
DOI: 10.1002/CPE.1673
Publisher: Inderscience Publishers
Date: 2018
Publisher: Inderscience Publishers
Date: 2019
Publisher: IEEE
Date: 13-03-2023
Publisher: IEEE
Date: 2009
Publisher: Association for Computing Machinery (ACM)
Date: 02-2008
Abstract: Component-based software structuring principles are now commonplace at the application level but componentization is far less established when it comes to building low-level systems software. Although there have been pioneering efforts in applying componentization to systems-building, these efforts have tended to target specific application domains (e.g., embedded systems, operating systems, communications systems, programmable networking environments, or middleware platforms). They also tend to be targeted at specific deployment environments (e.g., standard personal computer (PC) environments, network processors, or microcontrollers). The disadvantage of this narrow targeting is that it fails to maximize the genericity and abstraction potential of the component approach. In this article, we argue for the benefits and feasibility of a generic yet tailorable approach to component-based systems-building that offers a uniform programming model that is applicable in a wide range of systems-oriented target domains and deployment environments. The component model, called OpenCom , is supported by a reflective runtime architecture that is itself built from components. After describing OpenCom and evaluating its performance and overhead characteristics, we present and evaluate two case studies of systems we have built using OpenCom technology, thus illustrating its benefits and its general applicability.
Publisher: IGI Global
Date: 2020
Abstract: The pervasiveness of social media and user-generated content has triggered an exponential increase in global data. However, due to collection and extraction challenges, data in embedded comments, reviews and testimonials are largely inaccessible to a knowledge management system. This article describes a KM framework for the end-to-end knowledge management and value extraction from such content. This framework embodies solutions to unlock the potential of UGC as a rich, real-time data source. Three contributions are described in this article. First, a method for automatically navigating webpages to expose UGC for collection is presented. This is evaluated using browser emulation integrated with automated collection. Second, a method for collecting data without any a priori knowledge of the sites is introduced. Finally, a new testbed is developed to reflect the current state of internet sites and shared publicly to encourage future research. The discussion benchmarks the new algorithm alongside existing techniques, providing evidence of the increased amount of UGC data extracted.
Publisher: IEEE
Date: 09-2012
Publisher: ACM
Date: 21-06-2017
Publisher: IEEE
Date: 18-12-2022
Publisher: ACM
Date: 27-06-2020
Publisher: MDPI AG
Date: 20-07-2020
DOI: 10.3390/ELECTRONICS9071176
Abstract: This paper presents a rapid response system architecture for the distributed management of warehouses in logistics by applying the concept of tiered edge computing. A tiered edge node architecture is proposed for the system to process computing tasks of different complexity, and a corresponding rapid response algorithm is introduced. The paper emphasizes the classification of abstracted outlier sensing data which could better match different sensing types and transplant to various application fields. A software-defined simulation is used to evaluate the system performance on response time and response accuracy, from which it can be concluded that common predefined emergency cases can be detected and responded to, rapidly.
Publisher: IEEE
Date: 06-2012
Publisher: Springer Science and Business Media LLC
Date: 19-07-2018
Publisher: IEEE
Date: 12-2012
Publisher: MDPI AG
Date: 06-06-2022
DOI: 10.3390/ELECTRONICS11111801
Abstract: Scientific problems can be formulated as workflows to allow them to take advantage of cluster computing resources. Generally, the assumption is that the greater the resources dedicated to completing these tasks the better. This assumption does not take into account the energy cost of performing the computation and the specific characteristics of each workflow. In this paper, we present a unique approach to evaluating the energy consumption of scientific workflows on compute clusters. Two workflows from different domains, Astronomy and Bioinformatics, are presented and their execution is analyzed on a cluster of low powered small board computers. The paper presents a theoretical analysis of an energy-aware execution of workflows that can reduce the energy consumption of workflows by up to 68% compared to normal execution. We demonstrate that there are limitations to the benefits of increasing cluster sizes and there are trade-offs when considering energy vs. performance of the workflows and that the performance and energy consumption of any scientific workflow is heavily dependent on its underlying structure. The study concludes that the energy consumption of workflows can be optimized to improve both aspects of the workflow and motivates the development of an energy-aware scheduler.
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2022
Publisher: MDPI AG
Date: 29-06-2023
DOI: 10.3390/S23136039
Abstract: Internet of Things (IoT) architectures generally focus on providing consistent performance and reliable communications. The convergence of IoT, edge, fog, and cloud aims to improve the quality of service of applications, which does not typically emphasize energy efficiency. Considering energy in IoT architectures would reduce the energy impact from billions of IoT devices. The research presented in this paper proposes an optimization framework that considers energy consumption of nodes when selecting a node for processing an IoT request in edge-fog-cloud layered architecture. The IoT use cases considered in this paper include smart grid, autonomous vehicles, and eHealth. The proposed framework is evaluated using CPLEX simulations. The results provide insights into mechanisms that can be used to select nodes energy-efficiently whilst meeting the application requirements and other network constraints in multi-layered IoT architectures.
Publisher: IEEE
Date: 05-2011
Publisher: IEEE
Date: 06-2012
Publisher: ACM
Date: 27-06-2020
Publisher: ACM
Date: 02-2021
Publisher: IEEE
Date: 05-2023
Publisher: ACM
Date: 14-02-2022
Publisher: IEEE
Date: 2009
Publisher: Wiley
Date: 02-07-2009
DOI: 10.1002/CPE.1446
Publisher: IEEE
Date: 2006
Publisher: IEEE
Date: 05-2007
DOI: 10.1109/ICIW.2007.16
Publisher: IEEE
Date: 11-2016
Publisher: Springer International Publishing
Date: 05-09-2017
Publisher: IEEE
Date: 26-10-2022
Publisher: IEEE
Date: 12-2022
DOI: 10.1109/ISPA-BDCLOUD-SOCIALCOM-SUSTAINCOM57177.2022.00075
Publisher: Springer Science and Business Media LLC
Date: 20-06-2017
Publisher: Impact Journals, LLC
Date: 25-07-2015
Publisher: IEEE
Date: 08-2019
Publisher: IEEE
Date: 12-2022
DOI: 10.1109/ISPA-BDCLOUD-SOCIALCOM-SUSTAINCOM57177.2022.00078
Publisher: Springer Science and Business Media LLC
Date: 19-01-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: MDPI
Date: 17-05-2022
Publisher: IEEE
Date: 05-2023
Publisher: Informa UK Limited
Date: 09-10-2023
Publisher: Inderscience Publishers
Date: 2019
Publisher: MDPI AG
Date: 13-02-2019
DOI: 10.3390/SYM11020213
Abstract: This special issue of Symmetry entitled “Emerging Approaches and Advances in Big Data” consists of 17 papers [...]
Publisher: Association for Computing Machinery (ACM)
Date: 10-2003
Abstract: While there has already been significant research in support of openness and programmability in networks, this paper argues that there remains a need for generic support for the integrated development, deployment and management of programmable networking software. We further argue that this support should explicitly address the management of run-time reconfiguration of systems, and should be independent of any particular programming paradigm (e.g. active networking or open signaling), programming language, or hardware/ operating system platform. In line with these aims, we outline an approach to the structuring of programmable networking software in terms of a ubiquitously applied software component model that can accommodate all levels of a programmable networking system from low-level system support, to in-band packet handling, to active networking execution environments to signaling and coordination.
Publisher: IEEE
Date: 07-2023
Publisher: IEEE
Date: 13-03-2023
Publisher: IEEE
Date: 2004
Publisher: IEEE
Date: 05-2008
Publisher: Inderscience Publishers
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Publisher: Springer International Publishing
Date: 07-09-2016
Publisher: Springer Science and Business Media LLC
Date: 25-04-2022
DOI: 10.1007/S10669-022-09855-1
Abstract: For mission critical (MC) applications such as bushfire emergency management systems (EMS), understanding the current situation as a disaster unfolds is critical to saving lives, infrastructure and the environment. Incident control-room operators manage complex information and systems, especially with the emergence of Big Data. They are increasingly making decisions supported by artificial intelligence (AI) and machine learning (ML) tools for data analysis, prediction and decision-making. As the volume, speed and complexity of information increases due to more frequent fire events, greater availability of myriad IoT sensors, smart devices, satellite data and burgeoning use of social media, the advances in AI and ML that help to manage Big Data and support decision-making are increasingly perceived as “Black Box”. This paper aims to scope the requirements for bushfire EMS to improve Big Data management and governance of AI/ML. An analysis of ModelOps technology, used increasingly in the commercial sector, is undertaken to determine what components might be fit-for-purpose. The result is a novel set of ModelOps features, EMS requirements and an EMS-ModelOps framework that resolves more than 75% of issues whilst being sufficiently generic to apply to other types of mission-critical applications.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: Wiley
Date: 08-12-2015
DOI: 10.1002/CPE.3709
Publisher: IEEE
Date: 06-2022
Publisher: ACM
Date: 25-06-2007
Publisher: MDPI AG
Date: 06-12-2021
DOI: 10.3390/ELECTRONICS10233047
Abstract: Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario.
Publisher: IEEE
Date: 05-2012
Publisher: MDPI AG
Date: 03-12-2022
DOI: 10.3390/S22239463
Abstract: Personal protective equipment (PPE) is widely used around the world to protect against environmental hazards. With the emergence of the COVID-19 virus, the use of PPE domestically has increased dramatically. People use preventive and protective mechanisms now more than ever, leading to the important question of how protective is the PPE that is being used. Face masks are highly recommended or mandatory during the time of the COVID-19 pandemic due to their protective features against aerosol droplets. However, an issue faced by many users of face masks is that they are entirely manual, with users having to decide for themselves whether their mask is still protective or if they should replace their mask. Due to the difficulty in determining this, people tend to overuse masks beyond their optimal usage. The research presented in this paper is an investigation of the viability of integrating IoT sensors into masks that are capable of collecting data to determine its usage. This paper demonstrates the usage of humidity and temperature sensors for the purpose of determining a mask’s usage status based on changes in these variables when a mask is put on and taken off. An evaluation was made on the usage of the two sensors, with the conclusion that a humidity sensor provides more accurate results. From this, we present a framework that takes into consideration the factors that affect a mask’s performance, such as time, humidity and temperature, to calculate the life expectancy of a mask.
Publisher: ACM
Date: 03-08-2012
Publisher: IEEE
Date: 2006
Publisher: MDPI AG
Date: 03-02-2023
DOI: 10.3390/S23031711
Abstract: The COVID-19 pandemic has led to a dramatic increase in the use of PPE by the general public as well as health professionals. Scientists and health organizations have developed measures to protect people and minimize the catastrophic outcomes of COVID, including social distancing, frequent and periodic sanitizing, vaccinations, protective coverings, and face masks. During this time, the usage of protective face masks has increased dramatically. A mask only provides full safety to the user if it is a proper fit on their face. The aim of this paper is to automatically analyze and improve the fit of a face mask using IoT sensors. This paper describes the creation of a 3D-printed smart face mask that uses sensors to determine the current mask fit and then automatically tightens mask straps. This is evaluated using adjustment response time and the quality of fit achieved using the automatic adjustment approach with a range of sensor types.
Publisher: IEEE
Date: 09-2012
Publisher: IEEE
Date: 02-2010
Publisher: IEEE
Date: 06-2023
Publisher: MDPI AG
Date: 14-04-2022
DOI: 10.3390/ELECTRONICS11081239
Abstract: The Internet of Things (IoT) is maturing and becoming an established and vital technology [...]
Publisher: IEEE
Date: 07-2007
Publisher: IEEE
Date: 04-2013
Publisher: IEEE
Date: 2010
DOI: 10.1109/ICFN.2010.95
Publisher: Institution of Engineering and Technology (IET)
Date: 25-11-2011
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: University of Illinois Libraries
Date: 13-07-2011
Abstract: With the emergence of Web service mash-ups (Web applications that integrate different data sources), online data integration and aggregation is increasingly becoming the online norm for both commercial and non-commercial users. With such widespread adoption of data integration from discrete sources, the question emerges as to whether the resultant mash-up can be considered as trustworthy. This paper explores the concepts behind Web service mash-ups to determine the factors influencing their trustworthiness. The focus is on examining data quality and data assurance issues for both the data providers and the mash-up consumers.
Publisher: ERAU Hunt Library - DIGITAL COMMONS JOURNALS
Date: 2013
Publisher: IEEE
Date: 10-2010
DOI: 10.1109/CDEE.2010.57
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Kevin Lee.