7 resultados para Android,Peer to Peer,Wifi,Mesh Network

em CORA - Cork Open Research Archive - University College Cork - Ireland


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Body Sensor Network (BSN) technology is seeing a rapid emergence in application areas such as health, fitness and sports monitoring. Current BSN wireless sensors typically operate on a single frequency band (e.g. utilizing the IEEE 802.15.4 standard that operates at 2.45GHz) employing a single radio transceiver for wireless communications. This allows a simple wireless architecture to be realized with low cost and power consumption. However, network congestion/failure can create potential issues in terms of reliability of data transfer, quality-of-service (QOS) and data throughput for the sensor. These issues can be especially critical in healthcare monitoring applications where data availability and integrity is crucial. The addition of more than one radio has the potential to address some of the above issues. For example, multi-radio implementations can allow access to more than one network, providing increased coverage and data processing as well as improved interoperability between networks. A small number of multi-radio wireless sensor solutions exist at present but require the use of more than one radio transceiver devices to achieve multi-band operation. This paper presents the design of a novel prototype multi-radio hardware platform that uses a single radio transceiver. The proposed design allows multi-band operation in the 433/868MHz ISM bands and this, together with its low complexity and small form factor, make it suitable for a wide range of BSN applications.

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In this research we focus on the Tyndall 25mm and 10mm nodes energy-aware topology management to extend sensor network lifespan and optimise node power consumption. The two tiered Tyndall Heterogeneous Automated Wireless Sensors (THAWS) tool is used to quickly create and configure application-specific sensor networks. To this end, we propose to implement a distributed route discovery algorithm and a practical energy-aware reaction model on the 25mm nodes. Triggered by the energy-warning events, the miniaturised Tyndall 10mm data collector nodes adaptively and periodically change their association to 25mm base station nodes, while 25mm nodes also change the inter-connections between themselves, which results in reconfiguration of the 25mm nodes tier topology. The distributed routing protocol uses combined weight functions to balance the sensor network traffic. A system level simulation is used to quantify the benefit of the route management framework when compared to other state of the art approaches in terms of the system power-saving.

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The Internet and World Wide Web have had, and continue to have, an incredible impact on our civilization. These technologies have radically influenced the way that society is organised and the manner in which people around the world communicate and interact. The structure and function of individual, social, organisational, economic and political life begin to resemble the digital network architectures upon which they are increasingly reliant. It is increasingly difficult to imagine how our ‘offline’ world would look or function without the ‘online’ world; it is becoming less meaningful to distinguish between the ‘actual’ and the ‘virtual’. Thus, the major architectural project of the twenty-first century is to “imagine, build, and enhance an interactive and ever changing cyberspace” (Lévy, 1997, p. 10). Virtual worlds are at the forefront of this evolving digital landscape. Virtual worlds have “critical implications for business, education, social sciences, and our society at large” (Messinger et al., 2009, p. 204). This study focuses on the possibilities of virtual worlds in terms of communication, collaboration, innovation and creativity. The concept of knowledge creation is at the core of this research. The study shows that scholars increasingly recognise that knowledge creation, as a socially enacted process, goes to the very heart of innovation. However, efforts to build upon these insights have struggled to escape the influence of the information processing paradigm of old and have failed to move beyond the persistent but problematic conceptualisation of knowledge creation in terms of tacit and explicit knowledge. Based on these insights, the study leverages extant research to develop the conceptual apparatus necessary to carry out an investigation of innovation and knowledge creation in virtual worlds. The study derives and articulates a set of definitions (of virtual worlds, innovation, knowledge and knowledge creation) to guide research. The study also leverages a number of extant theories in order to develop a preliminary framework to model knowledge creation in virtual worlds. Using a combination of participant observation and six case studies of innovative educational projects in Second Life, the study yields a range of insights into the process of knowledge creation in virtual worlds and into the factors that affect it. The study’s contributions to theory are expressed as a series of propositions and findings and are represented as a revised and empirically grounded theoretical framework of knowledge creation in virtual worlds. These findings highlight the importance of prior related knowledge and intrinsic motivation in terms of shaping and stimulating knowledge creation in virtual worlds. At the same time, they highlight the importance of meta-knowledge (knowledge about knowledge) in terms of guiding the knowledge creation process whilst revealing the diversity of behavioural approaches actually used to create knowledge in virtual worlds and. This theoretical framework is itself one of the chief contributions of the study and the analysis explores how it can be used to guide further research in virtual worlds and on knowledge creation. The study’s contributions to practice are presented as actionable guide to simulate knowledge creation in virtual worlds. This guide utilises a theoretically based classification of four knowledge-creator archetypes (the sage, the lore master, the artisan, and the apprentice) and derives an actionable set of behavioural prescriptions for each archetype. The study concludes with a discussion of the study’s implications in terms of future research.

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Lidar is an optical remote sensing instrument that can measure atmospheric parameters. A Raman lidar instrument (UCLID) was established at University College Cork to contribute to the European lidar network, EARLINET. System performance tests were carried out to ensure strict data quality assurance for submission to the EARLINET database. Procedures include: overlap correction, telecover test, Rayleigh test and zero bin test. Raman backscatter coefficients, extinction coefficients and lidar ratio were measured from April 2010 to May 2011 and February 2012 to June 2012. Statistical analysis of the profiles over these periods provided new information about the typical atmospheric scenarios over Southern Ireland in terms of aerosol load in the lower troposphere, the planetary boundary layer (PBL) height, aerosol optical density (AOD) at 532 nm and lidar ratio values. The arithmetic average of the PBL height was found to be 608 ± 138 m with a median of 615 m, while average AOD at 532 nm for clean marine air masses was 0.119 ± 0.023 and for polluted air masses was 0.170 ± 0.036. The lidar ratio showed a seasonal dependence with lower values found in winter and autumn (20 ± 5 sr) and higher during spring and winter (30 ± 12 sr). Detection of volcanic particles from the eruption of the volcano Eyjafjallajökull in Iceland was measured between 21 April and 7 May 2010. The backscatter coefficient of the ash layer varied between 2.5 Mm-1sr-1 and 3.5 Mm-1sr-1, and estimation of the AOD at 532 nm was found to be between 0.090 and 0.215. Several aerosol loads due to Saharan dust particles were detected in Spring 2011 and 2012. Lidar ratio of the dust layers were determine to be between 45 and 77 sr and AOD at 532 nm during the dust events range between 0.84 to 0.494.

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Absorption heat transformers are thermodynamic systems which are capable of recycling industrial waste heat energy by increasing its temperature. Triple stage heat transformers (TAHTs) can increase the temperature of this waste heat by up to approximately 145˚C. The principle factors influencing the thermodynamic performance of a TAHT and general points of operating optima were identified using a multivariate statistical analysis, prior to using heat exchange network modelling techniques to dissect the design of the TAHT and systematically reassemble it in order to minimise internal exergy destruction within the unit. This enabled first and second law efficiency improvements of up to 18.8% and 31.5% respectively to be achieved compared to conventional TAHT designs. The economic feasibility of such a thermodynamically optimised cycle was investigated by applying it to an oil refinery in Ireland, demonstrating that in general the capital cost of a TAHT makes it difficult to achieve acceptable rates of return. Decreasing the TAHT's capital cost may be achieved by redesigning its individual pieces of equipment and reducing their size. The potential benefits of using a bubble column absorber were therefore investigated in this thesis. An experimental bubble column was constructed and used to track the collapse of steam bubbles being absorbed into a hotter lithium bromide salt solution. Extremely high mass transfer coefficients of approximately 0.0012m/s were observed, showing significant improvements over previously investigated absorbers. Two separate models were developed, namely a combined heat and mass transfer model describing the rate of collapse of the bubbles, and a stochastic model describing the hydrodynamic motion of the collapsing vapour bubbles taking into consideration random fluctuations observed in the experimental data. Both models showed good agreement with the collected data, and demonstrated that the difference between the solution's temperature and its boiling temperature is the primary factor influencing the absorber's performance.

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This paper discusses the difficulties involved in managing knowledge-intensive, multinational, multiorganisational, and multifunctional project networks. The study is based on a 2-year quasi-ethnography of one such network engaged in the design and development of a complex new process control system for an existing pharmaceutical plant in Ireland. The case describes how, drawing upon the organisational heritage of the corporations involved and the logic implicit within their global partnership arrangements, the project was initially structured in an aspatial manner that underestimated the complexity of the development process and the social relations required to support it. Following dissatisfaction with initial progress, a number of critical management interventions were made, which appeared to contribute to a recasting of the network ontology that facilitated the cultivation and protection of more appropriate communicative spaces. The case emphasises the need to move away from rationalistic assumptions about communication processes within projects of this nature, towards a richer conceptualisation of such enterprises as involving collective sensemaking activities within and between situated ‘communities’ of actors. Contrary to much contemporary writing, the paper argues that space and location are of crucial importance to our understanding of network forms of organising.

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Mobile and wireless networks have long exploited mobility predictions, focused on predicting the future location of given users, to perform more efficient network resource management. In this paper, we present a new approach in which we provide predictions as a probability distribution of the likelihood of moving to a set of future locations. This approach provides wireless services a greater amount of knowledge and enables them to perform more effectively. We present a framework for the evaluation of this new type of predictor, and develop 2 new predictors, HEM and G-Stat. We evaluate our predictors accuracy in predicting future cells for mobile users, using two large geolocation data sets, from MDC [11], [12] and Crawdad [13]. We show that our predictors can successfully predict with as low as an average 2.2% inaccuracy in certain scenarios.