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.

What does distributed cognition tell us about student learning of science?

This paper reports multi-layered analyses of student learning in a science classroom using the theoretical lens of Distributed Cognition (Hollan et al. 1999; Hutchins 1995). Building on the insights generated from previous research employing Distributed Cognition, the particular focus of this study has been placed on the “public space of interaction” (Alac and Hutchins 2004, p. 639) that includes both participants’ interaction with each other and their interaction with artefacts in their environment. In this paper, a lesson from an Australian science classroom was examined in detail, in which a class of grade-seven students were investigating the scientific theme of gravity by designing pendulums. The video-stimulated post-lesson interviews with both the teacher and the student groups offered complementary accounts (Clarke 2001a) that assisted the interpretation of the classroom data. The findings of this study provide supporting evidence to demonstrate the capacity of Distributed Cognition for advancing our understanding of the nature of learning in science classrooms.

Student difficulties in learning density: a distributed cognition perspective

Density has been reported as one of the most difficult concepts for secondary school students (e.g. Smith et al. 1997). Discussion about the difficulties of learning this concept has been largely focused on the complexity of the concept itself or student misconceptions. Few, if any, have investigated how the concept of density was constituted in classroom interactions, and what consequences these interactions have for individual students’ conceptual understanding. This paper reports a detailed analysis of two lessons on density in a 7th Grade Australian science classroom, employing the theory of Distributed Cognition (Hollan et al. 1999; Hutchins 1995). The analysis demonstrated that student understanding of density was shaped strongly by the public classroom discussion on the density of two metal blocks. It also revealed the ambiguities associated with the teacher demonstration and the student practical work. These ambiguities contributed to student difficulties with the concept of density identified in this classroom. The results of this study suggest that deliberate effort is needed to establish shared understanding not only about the purpose of the activities, but also about the meaning of scientific language and the utility of tools. It also suggests the importance of appropriate employment of instructional resources in order to facilitate student scientific understanding.

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.

Dynamic load variation and stability analysis in distribution networks with distributed generators

In this paper, the modeling of the distribution network is done in a different way where the distributed generator and dynamic loads are considered. Based on this modeling, this paper presents an analysis to investigate the dynamic and static load variation effect on the distribution network. Graphical interface industry software is used to conduct all the aspects of model implementation and carry out the extensive simulation studies. Here also focuses on the worst case scenario and the different fault effect on the generator. Finally, this paper presents the voltage profile for different penetration with different network configurations.

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.

Effects of load modeling in power distribution system with distributed wind generation

This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

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.