Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Exploring the global and local networks of national information system integration initiatives : a case study of national cultural collection integration from an actor-network perspective

Australian Museums Online (AMOL) was the earliest attempt to make Australia’s distributed cultural collections accessible from a single online resource. Despite early successes, significant achievements and the considerable value it offered certain groups, the project ran into operational difficulties and was eventually discontinued. By using Actor-Network Theory and analysing the global and local actor-networks, it is revealed that although the project originated from large, state museums, buy-in was restricted to individuals, rather than institutions and the most significant value was for smaller, regional institutions. Furthermore, although the global networks that governed the project could translate their visions through the local production networks, because the network’s underlying weaknesses were never addressed, over time this destablised the global networks. This case study offers advice for projects attempting to consolidate data sources from disparate sources, and highlights the importance of individual actors in championing the project.

Nurses and personal attendants' diabetes knowledge : in regional public residential care

Aim: Identify staff knowledge about diabetes medicines and organisational factors that influence safe medicines use in two large Australian regional public RACs that comply with national accreditation standards.

Background: Diabetes management is complicated in residential aged care facilities (RAC). Managing medicines is complex, especially in older people. Little is known about diabetes-specific medicine knowledge of various care staff (registered nurses (RN), enrolled nurses (EN) and patient care attendants (PCA) working in RAC.

Methods: A triangulation of methods was used to collect the data: anonymous self-complete questionnaire (ADKnowl) staff interviews to clarify practice issues that could affect safe medicine use, and a case file audit to identify medicine-related data. Questionnaires were distributed to all RNs, ENs and PCAs in the two services via nursing management (N=540). The ADKnowl was supplemented with additional questions and vignettes derived from actual case notes in each RAC to assess translation of knowledge into practice. Only medicine related data are reported.

Results: Sixty-eight people returned completed questionnaires (12.5% response rate). Knowledge deficits were identified in administering oral hypoglycaemic agents and insulin, their action and potential adverse events. Most ENs and PCAs did not know why HbA1c was measured. Almost half the RNs and ENs and 80% of PCAs did not know how diabetes comorbidities affect medicine choices. RN achieved higher overall average knowledge scores,74.3%, compared to ENs and PCA, 49%. The interviews suggest lack of time, unclear communication processes, inadequate knowledge about medications and resident behaviour compromises optimal medicine administration. Twenty case files audits were undertaken in each RAC and revealed residents were taking on average nine medicines.

Conclusion: Staff involved in caring for residents with diabetes had suboptimal general and medicine-specific diabetes knowledge to deliver optimal care. System issues and unpredictable resident behaviours made medicine management difficult and compromised safety.

Integrating kinect and haptics for interactive STEM education in local and distributed environments

Skill shortage is a realistic social problem that Australia is currently facing, especially in the fields of Science, Technology, Engineering and Mathematics (STEM). Various approaches have been proposed to soften this issue. By now the most successful approach is to attract pre-university youth and university freshmen into those fields before they make a decision on future subjects by introducing them with interactive, modifiable and inspiring virtual environments, which incorporates most essential knowledge of STEM. We propose to design a comprehensive virtual reality platform with immersive interactions, pluggable components and flexible configurations. It also involves haptics, motion capture and gesture recognition, and could be deployed in both local and distributed environments. The platform utilizes off the shelf low cost haptics and motion capture products, however the fidelity can be maintained at a good level. The proposed platform has been implemented with different configurations and has been tested on a group of users. Preliminary test results show that the interactivity, flexibility and fidelity of the platform are highly appreciated by users. User surveys also indicate that the proposed platform could help pre-university students and university freshmen build an overview of various aspects of STEM education. Besides, users are also positive on the fact that the platform enabled them to identify the challenges for higher education in STEM by providing them opportunities to interactively modify system configurations and instantly experience the corresponding results both visually and haptically.

Development of distributed energy systems for Middle East Countries

Although Renewable energy applications in Middle East countries were started in the middle of the seventies, they have only gained momentum in the last ten years. Considering the past gained experience, a proposed national Renewable Energy (RE) plan aims toward bringing RE into the main stream of the national energy supply system with a target contribution of 10% of the electricity demand by the year 2020. The proposed plan calls for a wide spectrum of renewable energy applications. This paper will highlight renewable energy applications in Middle East countries, the gained experience, the RE resources, and the future prospects for the utilization of RE recourses.

Time correlated anomaly detection based on inferences

Anomaly detection techniques are used to find the presence of anomalous activities in a network by comparing traffic data activities against a "normal" baseline. Although it has several advantages which include detection of "zero-day" attacks, the question surrounding absolute definition of systems deviations from its "normal" behaviour is important to reduce the number of false positives in the system. This study proposes a novel multi-agent network-based framework known as Statistical model for Correlation and Detection (SCoDe), an anomaly detection framework that looks for timecorrelated anomalies by leveraging statistical properties of a large network, monitoring the rate of events occurrence based on their intensity. SCoDe is an instantaneous learning-based anomaly detector, practically shifting away from the conventional technique of having a training phase prior to detection. It does acquire its training using the improved extension of Exponential Weighted Moving Average (EWMA) which is proposed in this study. SCoDe does not require any previous knowledge of the network traffic, or network administrators chosen reference window as normal but effectively builds upon the statistical properties from different attributes of the network traffic, to correlate undesirable deviations in order to identify abnormal patterns. The approach is generic as it can be easily modified to fit particular types of problems, with a predefined attribute, and it is highly robust because of the proposed statistical approach. The proposed framework was targeted to detect attacks that increase the number of activities on the network server, examples which include Distributed Denial of Service (DDoS) and, flood and flash-crowd events. This paper provides a mathematical foundation for SCoDe, describing the specific implementation and testing of the approach based on a network log file generated from the cyber range simulation experiment of the industrial partner of this project.

Guest editors' introduction : Special issue on trust, security, and privacy in parallel and distributed systems

In modern computing paradigms, most computing systems, e.g., cluster computing, grid computing, cloud computing, the Internet, telecommunication networks, Cyber- Physical Systems (CPS), and Machine-to-Machine communication networks (M2M), are parallel and distributed systems. While providing improved expandability, manageability, efficiency, and reliability, parallel and distributed systems increase their security weaknesses to an unprecedented scale. As the system devices are widely connected, their vulnerabilities are shared by the entire system. Because tasks are allocated to, and information is exchanged among the system devices that may belong to different users, trust, security, and privacy issues have yet to be resolved. This special issue of the IEEE Transactions on Parallel and Distributed Systems (TPDS) highlights recent advances in trust, security, and privacy for emerging parallel and distributed systems. This special issue was initiated by Dr. Xu Li, Dr. Patrick McDaniel, Dr. Radha Poovendran, and Dr. Guojun Wang. Due to a large number of submissions, Dr. Zhenfu Cao, Dr. Keqiu Li, and Dr. Yang Xiang were later invited to the editorial team. Dr. Xu Li was responsible for coordinating the paper review process. In response to the call for papers, we received 150 effective submissions, out of which 24 are included in this special issue after rigorous review and careful revision, presenting an acceptance ratio of 16 percent. The accepted papers are divided into three groups, covering issues related to trust, security, and privacy, respectively.

An effective VAR planning to improve dynamic voltage profile of distribution networks with distributed wind generation

This paper proposes an effective VAR planning based on reactive power margin for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a distribution test system representative of the Kumamoto area in Japan. The detailed mathematical modeling of the system is also presented. Firstly, this paper provides simulation results showing the effects of composite load on voltage dynamics in the distribution network through an accurate time-domain analysis. Then, a cost-effective combination of shunt capacitor bank and distribution static synchronous compensator (D-STATCOM) is selected to ensure fast voltage recovery after a sudden disturbance. The analysis shows that the proposed approach can reduce the size of compensating devices, which in turn, reduces the cost. It also reduces power loss of the system.

Design of a norm-bounded LQG controller for power distribution networks with distributed generation

This paper presents a novel excitation control design to improve the voltage profile of power distribution networks with distributed generation and induction motor loads. The system is linearised by perturbation technique. Controller is designed using the linear-quadratic-Gaussian (LQG) controller synthesis method. The LQG controller is addressed with norm-bounded uncertainty. The approach considered in this paper is to find the smallest upper bound on the H∞ norm of the uncertain system and to design an optimal controller based on this bound. The design method requires the solution of a linear matrix inequality. The performance of the controller is tested on a benchmark power distribution system. Simulation results show that the proposed controller provides impressive oscillation damping compared to the conventional excitation controller.

Voltage profile improvement for distributed wind generation using D-STATCOM

This paper presents the application of FACTS devices for the enhancement of dynamic voltage stability in distribution networks with distributed wind generation. The analysis is carried over a test distribution system representative of the Kumamoto area in Japan. The detailed mathematical modelling of the system is also presented. Firstly, this paper provides simulation results showing the effects of higher and lower penetration of distributed wind generation on the voltage dynamics in a faulted system. Then, a distribution static synchronous compensator (D-STATCOM) is used to improve the voltage profile of the system. This analysis shows that D-STATCOM has significant performance to improve the voltage dynamics of distribution system compared to shunt capacitor.

A secure cloud storage system from threshold encryption

The confidentiality of data is one of the most important issues in cloud storage system. We address the privacy issue of decentralized cloud storage system using threshold cryptography. The major challenge of designing this cloud storage system is to provide a better privacy guarantee. To achieve this goal, we propose a threshold encryption scheme and integrate it with a secure decentralized erasure code to form a secure cloud storage system, where the user generates a secret parameter participated in system encryption and decryption of plaintext blocks in the combine process. Our cloud storage system meets the requirements of data robustness and confidentiality.

Engineering a distributed infrastructure for large-scale cost-effective content dissemination over urban vehicular networks

This paper proposes a practical and cost-effective approach to construct a fully distributed roadside communication infrastructure to facilitate the localized content dissemination to vehicles in the urban area. The proposed infrastructure is composed of distributed lightweight low-cost devices called roadside buffers (RSBs), where each RSB has the limited buffer storage and is able to transmit wirelessly the cached contents to fast-moving vehicles. To enable the distributed RSBs working toward the global optimal performance (e.g., minimal average file download delays), we propose a fully distributed algorithm to determine optimally the content replication strategy at RSBs. Specifically, we first develop a generic analytical model to evaluate the download delay of files, given the probability density of file distribution at RSBs. Then, we formulate the RSB content replication process as an optimization problem and devise a fully distributed content replication scheme accordingly to enable vehicles to recommend intelligently the desirable content files to RSBs. The proposed infrastructure is designed to optimize the global network utility, which accounts for the integrated download experience of users and the download demands of files. Using extensive simulations, we validate the effectiveness of the proposed infrastructure and show that the proposed distributed protocol can approach to the optimal performance and can significantly outperform the traditional heuristics.

Workers’ compensation and mental health : examining the mental health impacts of involvement in the Victorian Work Cover system from the perspective of long-­term injured workers

The project aimed to explore long--term injured workers’ experiences and perceptions of their mental health as they progressed through the Victorian WorkCover process. The purpose of the project was to assist in understanding these factors in order to identify how workers might be better supported, and to identify changes that compensation authorities, employers and unions can make to reduce mental distress amongst injured workers. As a project based on workers’ accounts of their experiences, it aimed to provide a narrative basis for the development of supportive policy and practice to reduce mental distress amongst people who are clients of the WorkCover system. The project was a qualitative study based on fifteen in--depth interviews with people who had been injured at work and who had been off work for at least six months. The workers who took part in the study were recruited with the assistance of their trade unions, using an advertisement that was distributed via the unions’ regular communication channels. Workers were asked to tell their story of injury and recovery with a particular focus on how they felt and the factors that affected them, both positively and negatively. They were also asked what could or should be changed to support workers’ recovery and improve their experience of the WorkCover system. The workers who took part in the study came from a variety of industry sectors (education, textile and clothing manufacturing and meat industries) and different occupational categories (professional, trade/technical and manual). They included people whose primary injury was physical and those whose primary injury was psychosocial.