The design of robust protocols for distributed real-time systems

Modern distributed control systems comprise of a set of processors which are interconnected using a suitable communication network. For use in real-time control environments, such systems must be deterministic and generate specified responses within critical timing constraints. Also, they should be sufficiently robust to survive predictable events such as communication or processor faults. This thesis considers the problem of coordinating and synchronizing a distributed real-time control system under normal and abnormal conditions. Distributed control systems need to periodically coordinate the actions of several autonomous sites. Often the type of coordination required is the all or nothing property of an atomic action. Atomic commit protocols have been used to achieve this atomicity in distributed database systems which are not subject to deadlines. This thesis addresses the problem of applying time constraints to atomic commit protocols so that decisions can be made within a deadline. A modified protocol is proposed which is suitable for real-time applications. The thesis also addresses the problem of ensuring that atomicity is provided even if processor or communication failures occur. Previous work has considered the design of atomic commit protocols for use in non time critical distributed database systems. However, in a distributed real-time control system a fault must not allow stringent timing constraints to be violated. This thesis proposes commit protocols using synchronous communications which can be made resilient to a single processor or communication failure and still satisfy deadlines. Previous formal models used to design commit protocols have had adequate state coverability but have omitted timing properties. They also assumed that sites communicated asynchronously and omitted the communications from the model. Timed Petri nets are used in this thesis to specify and design the proposed protocols which are analysed for consistency and timeliness. Also the communication system is mcxielled within the Petri net specifications so that communication failures can be included in the analysis. Analysis of the Timed Petri net and the associated reachability tree is used to show the proposed protocols always terminate consistently and satisfy timing constraints. Finally the applications of this work are described. Two different types of applications are considered, real-time databases and real-time control systems. It is shown that it may be advantageous to use synchronous communications in distributed database systems, especially if predictable response times are required. Emphasis is given to the application of the developed commit protocols to real-time control systems. Using the same analysis techniques as those used for the design of the protocols it can be shown that the overall system performs as expected both functionally and temporally.

The effect of load on agent-based algorithms for distributed task allocation

Multi-agent algorithms inspired by the division of labour in social insects and by markets, are applied to a constrained problem of distributed task allocation. The efficiency (average number of tasks performed), the flexibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved efficiency and robustness. We employ nature inspired particle swarm optimisation to obtain optimised parameters for all algorithms in a range of representative environments. Although results are obtained for large population sizes to avoid finite size effects, the influence of population size on the performance is also analysed. From a theoretical point of view, we analyse the causes of efficiency loss, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

The green campus is also a virtual one

This paper analyses the role of education for sustainability as enabling future sustainability practitioners to become key change agents and leaders. It is important that generic skills and understandings are married to a capability to lead beyond one's disciplinary or professional authority. 'Academic' education for future (and current) sustainability professionals should focus on transdisciplinary learning and research, new media affordances and distributed learning. This raises important questions about the nature of experiential learning and the meaning of 'living sustainability'. With reference to various developments in e-learning, including the European Union's aim to establish a virtual campus for a sustainable Europe, this paper argues that the digital environment is an integral part of our lifeworld connecting people to place, with each other and to possibilities for creative transdisciplinary inquiry. The role of new media in education for sustainability is rarely discussed, is under theorised and its potential largely ignored. © 2010 Inderscience Enterprises Ltd.

Virtual Gires-Tournois etalons realized with phase-modulated wideband chirped fiber gratings

We propose and demonstrate novel virtual Gires-Tournois (GT) etalons based on fiber gratings. By introducing an additional phase modulation in wideband linearly chirped fiber Bragg gratings, we have successfully generated GT resonance with only one grating. This technique can simplify the fabrication procedure while retaining the normal advantages of distributed etalons, including their full compatibility with optical fiber, low insertion loss, and low cost. Such etalons can be used as dispersion compensation devices in optical transmission systems. © 2007 Optical Society of America.

Medical emergency alarm dissemination in urban environments

During medical emergencies, the ability to communicate the state and position of injured individuals is essential. In critical situations or crowd aggregations, this may result difficult or even impossible due to the inaccuracy of verbal communication, the lack of precise localization for the medical events, and/or the failure/congestion of infrastructure-based communication networks. In such a scenario, a temporary (ad hoc) wireless network for disseminating medical alarms to the closest hospital, or medical field personnel, can be usefully employed to overcome the mentioned limitations. This is particularly true if the ad hoc network relies on the mobile phones that people normally carry, since they are automatically distributed where the communication needs are. Nevertheless, the feasibility and possible implications of such a network for medical alarm dissemination need to be analysed. To this aim, this paper presents a study on the feasibility of medical alarm dissemination through mobile phones in an urban environment, based on realistic people mobility. The results showed the dependence between the medical alarm delivery rates and both people and hospitals density. With reference to the considered urban scenario, the time needed to delivery medical alarms to the neighbour hospital with high reliability is in the order of minutes, thus revealing the practicability of the reported network for medical alarm dissemination. © 2013 Elsevier Ltd. All rights reserved.

Knowledge processes in virtual teams:consolidating the evidence

This article takes stock of the current state of research on knowledge processes in virtual teams (VTs) and consolidates the extent research findings. Virtual teams, on the one hand, constitute important organisational entities that facilitate the integration of diverse and distributed knowledge resources. On the other hand, collaborating in a virtual environment creates particular challenges for the knowledge processes. The article seeks to consolidate the diverse evidence on knowledge processes in VTs with a specific focus on identifying the factors that influence the effectiveness of these knowledge processes. The article draws on the four basic knowledge processes outlined by Alavi and Leidner (2001) (i.e. creation, transferring, storage/retrieval and application) to frame the investigation and discuss the extent research. The consolidation of the existing research findings allows us to recognise the gaps in the understanding of knowledge processes in VTs and identify the important avenues for future research.

Benchmarking of distributed computing engines spark and GraphLab for big data analytics

In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

A virtuális térben élő fogyasztó – A Second Life hatása a fogyasztói magatartásra (Consumer in the virtual world – Affect of the Second Life to the consumer behavior)

A virtuális szociális világok, úgy mint a Second Life, egyre nagyobb népszerűségre téve szert, hamar az üzleti érdeklődés középpontjában találták magukat. A szerző célja, hogy feltérképezze a virtuális identitás és a fogyasztói magatartás közötti kapcsolat mibenlétét a Second Life világában. Ezért először bemutatja, hogy miként működik a Second Life és milyen jellemzőkkel rendelkezik. Másodszor ismerteti, hogy az on-line identitásalkotás miként befolyásolja üzleti szempontból az individuális viselkedést. A Second Life vizsgálata során a virtuális identitás fogalmát használja föl, mely összevethető az egyén valódi életbeli identitásával. Harmadszor: rátér a kutatási részre, amely során a Second Life világában kialakított identitás jellemzőit vizsgálta. Négy virtuális identitástípust azonosított, melyeknek más és más kapcsolata van a virtuális fogyasztás jelenségével. Végezetül: kiemeli azokat az eredményeket és megállapításokat, melyeket a vállalatoknak különösképpen figyelembe kell venniük a pszichológiai nézőpont szempontjából ahhoz, hogy eredményesen szerepeljenek a virtuális világokban. ________ Given their increasing popularity, virtual worlds, such as Second Life, attracted the attention of the business media. The aim of the present article is to explore the relationship between virtual identity and consumer behaviour in Second Life. First, the author reviews Second Life functions and particular characteristics. Second, he illustrates how online identity construction affects one’s behaviour in such environments from a business perspective. Third, the author demonstrates his findings associated with identity construction in Second Life. More specifically, four different types of virtual identities can be identified, each with slightly different implications toward virtual consumption. Finally, he highlights the major points to which companies should pay particular attention in their virtual social world activities, focusing on the psychological mechanisms that influence people’s online behaviour and thinking.

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

Group presence in virtual worlds: Supporting collaborative e-learning

Even though e-learning endeavors have significantly proliferated in recent years, current e-learning technologies provide poor support for group-oriented learning. The now popular virtual world's technologies offer a possible solution. Virtual worlds provide the users with a 3D - computer generated shared space in which they can meet and interact through their virtual representations. Virtual worlds are very successful in developing high levels of engagement, presence and group presence in the users. These elements are also desired in educational settings since they are expected to enhance performance. The goal of this research is to test the hypothesis that a virtual world learning environment provides better support for group-oriented collaborative e-learning than other learning environments, because it facilitates the emergence of group presence. To achieve this, a quasi-experimental study was conducted and data was gathered through the use of various survey instruments and a set of collaborative tasks assigned to the participants. Data was gathered on the dependent variables: Engagement, Group Presence, Individual Presence, Perceived Individual Presence, Perceived Group Presence and Performance. The data was analyzed using the statistical procedures of Factor Analysis, Path Analysis, Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). The study provides support for the hypothesis. The results also show that virtual world learning environments are better than other learning environments in supporting the development of all the dependent variables. It also shows that while only Individual Presence has a significant direct effect on Performance; it is highly correlated with both Engagement and Group Presence. This suggests that these are also important in regards to performance. Developers of e-learning endeavors and educators should incorporate virtual world technologies in their efforts in order to take advantage of the benefit they provide for e-learning group collaboration.

Environmental stability affects phenotypic evolution in a globally distributed marine picoplankton

Marine phytoplankton can evolve rapidly when confronted with aspects of climate change because of their large population sizes and fast generation times. Despite this, the importance of environment fluctuations, a key feature of climate change, has received little attention-selection experiments with marine phytoplankton are usually carried out in stable environments and use single or few representatives of a species, genus or functional group. Here we investigate whether and by how much environmental fluctuations contribute to changes in ecologically important phytoplankton traits such as C:N ratios and cell size, and test the variability of changes in these traits within the globally distributed species Ostreococcus. We have evolved 16 physiologically distinct lineages of Ostreococcus at stable high CO2 (1031±87?µatm CO2, SH) and fluctuating high CO2 (1012±244?µatm CO2, FH) for 400 generations. We find that although both fluctuation and high CO2 drive evolution, FH-evolved lineages are smaller, have reduced C:N ratios and respond more strongly to further increases in CO2 than do SH-evolved lineages. This indicates that environmental fluctuations are an important factor to consider when predicting how the characteristics of future phytoplankton populations will have an impact on biogeochemical cycles and higher trophic levels in marine food webs.

Modelo de interoperabilidade para utilização dos recursos dos ambientes virtuais de aprendizagem através de dispositivos móveis

The technological evolution has been making the Distance Education accessible for a greater number of citizens anytime and anywhere. The potential increase of the supply for mobile devices integrated to mobile learning environments allows that the information comes out of the physical environment, creating opportunities for students and teachers to create geographically distributed learning scenarios. However, many applications developed for these environments remain isolated from each other and do not become integrated sufficiently into the virtual learning environments (AVA). This dissertation presents an interoperability model between mobile devices and distinct AVA based on webservices. For the conception of this model, requirements engineering and software architecture techniques were used. With the goal of showing the model viability, a mobile application focused on surveys has been developed, and additionally, the main functionalities related to the interoperability were tested

Design and Implementation of a Cloud Infrastructure for Distributed Scientific Calculation

Cloud computing enables independent end users and applications to share data and pooled resources, possibly located in geographically distributed Data Centers, in a fully transparent way. This need is particularly felt by scientific applications to exploit distributed resources in efficient and scalable way for the processing of big amount of data. This paper proposes an open so- lution to deploy a Platform as a service (PaaS) over a set of multi- site data centers by applying open source virtualization tools to facilitate operation among virtual machines while optimizing the usage of distributed resources. An experimental testbed is set up in Openstack environment to obtain evaluations with different types of TCP sample connections to demonstrate the functionality of the proposed solution and to obtain throughput measurements in relation to relevant design parameters.

Studying Recommender Systems to Enhance Distributed Computing Schedulers

Distributed Computing frameworks belong to a class of programming models that allow developers to

launch workloads on large clusters of machines. Due to the dramatic increase in the volume of

data gathered by ubiquitous computing devices, data analytic workloads have become a common

case among distributed computing applications, making Data Science an entire field of

Computer Science. We argue that Data Scientist's concern lays in three main components: a dataset,

a sequence of operations they wish to apply on this dataset, and some constraint they may have

related to their work (performances, QoS, budget, etc). However, it is actually extremely

difficult, without domain expertise, to perform data science. One need to select the right amount

and type of resources, pick up a framework, and configure it. Also, users are often running their

application in shared environments, ruled by schedulers expecting them to specify precisely their resource

needs. Inherent to the distributed and concurrent nature of the cited frameworks, monitoring and

profiling are hard, high dimensional problems that block users from making the right

configuration choices and determining the right amount of resources they need. Paradoxically, the

system is gathering a large amount of monitoring data at runtime, which remains unused.

In the ideal abstraction we envision for data scientists, the system is adaptive, able to exploit

monitoring data to learn about workloads, and process user requests into a tailored execution

context. In this work, we study different techniques that have been used to make steps toward

such system awareness, and explore a new way to do so by implementing machine learning

techniques to recommend a specific subset of system configurations for Apache Spark applications.

Furthermore, we present an in depth study of Apache Spark executors configuration, which highlight

the complexity in choosing the best one for a given workload.