Energy-oriented design tools for collaboration in the cloud

Emerging from the challenge to reduce energy consumption in buildings is the need for energy simulation to be used more effectively to support integrated decision making in early design. As a critical response to a Green Star case study, we present DEEPA, a parametric modeling framework that enables architects and engineers to work at the same semantic level to generate shared models for energy simulation. A cloud-based toolkit provides web and data services for parametric design software that automate the process of simulating and tracking design alternatives, by linking building geometry more directly to analysis inputs. Data, semantics, models and simulation results can be shared on the fly. This allows the complex relationships between architecture, building services and energy consumption to be explored in an integrated manner, and decisions to be made collaboratively.

Extensible software for research data capture

Projects funded by the Australian National Data Service(ANDS). The specific projects that were funded included: a) Greenhouse Gas Emissions Project (N2O) with Prof. Peter Grace from QUT’s Institute of Sustainable Resources. b) Q150 Project for the management of multimedia data collected at Festival events with Prof. Phil Graham from QUT’s Institute of Creative Industries. c) Bio-diversity environmental sensing with Prof. Paul Roe from the QUT Microsoft eResearch Centre. For the purposes of these projects the Eclipse Rich Client Platform (Eclipse RCP) was chosen as an appropriate software development framework within which to develop the respective software. This poster will present a brief overview of the requirements of the projects, an overview of the experiences of the project team in using Eclipse RCP, report on the advantages and disadvantages of using Eclipse and it’s perspective on Eclipse as an integrated tool for supporting future data management requirements.

Exploring subscription renewal intention of operational cloud enterprise systems - a stakeholder perspective

Retaining customers is a relevant topic throughout all service industries. However, only limited attention has been directed towards studying the antecedents of subscription renewal in the context of operational cloud enterprise systems. Cloud services have historically been offered as subscription-based services with the (theoretical) possibility of seamless service cancellation, in contrast to classical IT-Outsourcing contracts or license-based software installations of on-premise enterprise systems. In this work, we investigate the central concept of subscription renewal by focusing on different facets of IS success and their relevance for distinct employee cohorts. Analyzing inter-cohort differences has strong practical implications, as it helps IT vendors to focus on specific IT-related factors when trying to retain customers. Therefore an empirical study was undertaken. The hypotheses were developed on an individual level and tested using survey responses of IT decision makers within companies which adopted cloud enterprise systems. Gathered data was then analyzed using PLS. The results show that subscription renewal intention of the strategic cohort is mainly based on perceived system quality, whereas information quality explains most of the variance of subscription renewal in the management cohort. Beneath the cloud enterprise systems specific contributions, the work adds to the theoretical body of research related to IS success and IS continuation, as well as stakeholder perspectives.

A new approach to the cloud-based heterogeneous MapReduce placement problem

Guaranteeing Quality of Service (QoS) with minimum computation cost is the most important objective of cloud-based MapReduce computations. Minimizing the total computation cost of cloud-based MapReduce computations is done through MapReduce placement optimization. MapReduce placement optimization approaches can be classified into two categories: homogeneous MapReduce placement optimization and heterogeneous MapReduce placement optimization. It is generally believed that heterogeneous MapReduce placement optimization is more effective than homogeneous MapReduce placement optimization in reducing the total running cost of cloud-based MapReduce computations. This paper proposes a new approach to the heterogeneous MapReduce placement optimization problem. In this new approach, the heterogeneous MapReduce placement optimization problem is transformed into a constrained combinatorial optimization problem and is solved by an innovative constructive algorithm. Experimental results show that the running cost of the cloud-based MapReduce computation platform using this new approach is 24:3%-44:0% lower than that using the most popular homogeneous MapReduce placement approach, and 2:0%-36:2% lower than that using the heterogeneous MapReduce placement approach not considering the spare resources from the existing MapReduce computations. The experimental results have also demonstrated the good scalability of this new approach.

Introduction to the Proceedings of the Workshop on User-Focused Service Engineering, Consumption and Aggregation (USECA) 2011

The first User-Focused Service Engineering, Consumption and Aggregation workshop (USECA) in 2011 was held in conjunction with the WISE 2011 conference in Sydney, Australia. Web services and related technology are a widely accepted standard architectural paradigm for application development. The idea of reusing existing software components to build new applications has been well documented and supported for the world of enterprise computing and professional developers. However, this powerful idea has not been transferred to end-users who have limited or no computing knowledge. The current methodologies, models, languages and tools developed for Web service composition are suited to IT professionals and people with years of training in computing technologies. It is still hard to imagine any of these technologies being used by business professionals, as opposed to computing professionals. © 2013 Springer-Verlag.

A framework for generating realistic traffic for distributed denial-of-service attacks and flash events

An intrinsic challenge associated with evaluating proposed techniques for detecting Distributed Denial-of-Service (DDoS) attacks and distinguishing them from Flash Events (FEs) is the extreme scarcity of publicly available real-word traffic traces. Those available are either heavily anonymised or too old to accurately reflect the current trends in DDoS attacks and FEs. This paper proposes a traffic generation and testbed framework for synthetically generating different types of realistic DDoS attacks, FEs and other benign traffic traces, and monitoring their effects on the target. Using only modest hardware resources, the proposed framework, consisting of a customised software traffic generator, ‘Botloader’, is capable of generating a configurable mix of two-way traffic, for emulating either large-scale DDoS attacks, FEs or benign traffic traces that are experimentally reproducible. Botloader uses IP-aliasing, a well-known technique available on most computing platforms, to create thousands of interactive UDP/TCP endpoints on a single computer, each bound to a unique IP-address, to emulate large numbers of simultaneous attackers or benign clients.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

Modelling Denial of Service Attacks on JFK with Meadow's Cost-Based Framework

We present the first detailed application of Meadows’s cost-based modelling framework to the analysis of JFK, an Internet key agreement protocol. The analysis identifies two denial of service attacks against the protocol that are possible when an attacker is willing to reveal the source IP address. The first attack was identified through direct application of a cost-based modelling framework, while the second was only identified after considering coordinated attackers. Finally, we demonstrate how the inclusion of client puzzles in the protocol can improve denial of service resistance against both identified attacks.

Let's Dance: A Language for Service Behavior Modeling

In Service-Oriented Architectures (SOAs), software systems are decomposed into independent units, namely services, that interact with one another through message exchanges. To promote reuse and evolvability, these interactions are explicitly described right from the early phases of the development lifecycle. Up to now, emphasis has been placed on capturing structural aspects of service interactions. Gradually though, the description of behavioral dependencies between service interactions is gaining increasing attention as a means to push forward the SOA vision. This paper deals with the description of these behavioral dependencies during the analysis and design phases. The paper outlines a set of requirements that a language for modeling service interactions at this level should fulfill, and proposes a language whose design is driven by these requirements.

IT service desk process improvement : a narrative style case study

This paper is a detailed case narrative on how a Faculty of a leading Australian University conducted a rigorous process improvement project, applying fundamental Business Process Management (BPM) concepts. The key goal was to increase the efficiency of the faculty’s service desk. The decrease of available funds due to reducing student numbers and the ever increasing costs associated with service desk prompted this project. The outcomes of the project presented a set of recommendations which leads to organizational innovation having information technology as an enabler for change. The target audience includes general BPM practitioners or academics who are interested in BPM related case studies, and specific organisations who might be interested in conducting BPM within their service desk processes.