317,787 research outputs found

    Systems support for distributed learning environments

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    This thesis contends that the growing phenomena of multi-user networked "learning environments" should be treated as distributed interactive systems and that their developers should be aware of the systems and networks issues involved in their construction and maintenance. Such environments are henceforth referred to as distributed learning environments, or DLEs. Three major themes are identified as part of systems support: i) shared resource coherence in DLEs; ii) Quality of Service for the end- users of DLEs; and iii) the need for an integrating framework to develop, deploy and manage DLEs. The thesis reports on several distinct implementations and investigations that are each linked by one or more of those themes. Initially, responsiveness and coherence emerged as potentially conflicting requirements, and although a system was built that successfully resolved this conflict it proved difficult to move from the "clean room" conditions of a research project into a real world learning context. Accordingly, subsequent systems adopted a web-based approach to aid deployment in realistic settings. Indeed, production versions of these systems have been used extensively in credit-bearing modules in several Scottish Universities. Interactive responsiveness then emerged as a major Quality of Service issue in its own right, and motivated a series of investigations into the sources of delay, as experienced by end users of web-oriented distributed learning environments. Investigations into this issue provided insight into the nature of web-oriented interactive distributed learning and highlighted the need to be QoS-aware. As the volume and the range of usage of distributed learning applications increased the need for an integrating framework emerged. This required identifying and supporting a wide variety of educational resource types and also the key roles occupied by users of the system, such as tutors, students, supervisors, service providers, administrators, examiners. The thesis reports on the approaches taken and lessons learned from researching, designing and implementing systems which support distributed learning. As such, it constitutes a documented body of work that can inform the future design and deployment of distributed learning environments

    {\mu}-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog computing Environments

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    Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet of Things (IoT) use cases, particularly latency-critical applications. Smart devices, such as traffic and surveillance cameras, often do not have sufficient resources to process computation-intensive and latency-critical services. Hence, the constituent parts of services can be offloaded to nearby Edge/Fog resources for processing and storage. However, making offloading decisions for complex services in highly stochastic and dynamic environments is an important, yet difficult task. Recently, Deep Reinforcement Learning (DRL) has been used in many complex service offloading problems; however, existing techniques are most suitable for centralized environments, and their convergence to the best-suitable solutions is slow. In addition, constituent parts of services often have predefined data dependencies and quality of service constraints, which further intensify the complexity of service offloading. To solve these issues, we propose a distributed DRL technique following the actor-critic architecture based on Asynchronous Proximal Policy Optimization (APPO) to achieve efficient and diverse distributed experience trajectory generation. Also, we employ PPO clipping and V-trace techniques for off-policy correction for faster convergence to the most suitable service offloading solutions. The results obtained demonstrate that our technique converges quickly, offers high scalability and adaptability, and outperforms its counterparts by improving the execution time of heterogeneous services

    Learning algorithms for the control of routing in integrated service communication networks

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    There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

    INSPIRAL: investigating portals for information resources and learning. Final project report

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    INSPIRAL's aims were to identify and analyse, from the perspective of the UK HE learner, the nontechnical, institutional and end-user issues with regard to linking VLEs and digital libraries, and to make recommendations for JISC strategic planning and investment. INSPIRAL's objectives -To identify key stakeholders with regard to the linkage of VLEs, MLEs and digital libraries -To identify key stakeholder forum points and dissemination routes -To identify the relevant issues, according to the stakeholders and to previous research, pertaining to the interaction (both possible and potential) between VLEs/MLEs and digital libraries -To critically analyse identified issues, based on stakeholder experience and practice; output of previous and current projects; and prior and current research -To report back to JISC and to the stakeholder communities, with results situated firmly within the context of JISC's strategic aims and objectives

    Perceived quality of multimedia educational content: A cognitive style approach

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    This is the post-print version of the Article. The oficial published version can be accessed from the link below - Copyright, 2006 SpringerCognitive styles influence the way how humans process information, with previous research demonstrating that they have significant effects on student learning in multimedia environments. On the other hand, the perceptual quality of the human multimedia experience is notoriously difficult to measure. In this paper, we report the results of an empirical study, which investigated the relationship between user cognitive styles and perceptual multimedia quality, in which users had the possibility to specify their desired Quality of Service settings — in terms of frame rates and color depth. Results show that whilst color choice is impacted by a participant's cognitive style, such Quality of Service parameters do not significantly affect perceived multimedia quality, and that users do not necessarily choose optimum presentation settings to enhance their perceived enjoyment and assimilation of multimedia informational content

    Next Generation Cloud Computing: New Trends and Research Directions

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    The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

    The impact of cognitive styles on perceptual distributed multimedia quality

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    This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2003 John Wiley & Sons, Inc.Multimedia technology has been widely used in web-based instruction, but previous studies have indicated that individual differences, especially cognitive styles, have significant effects on users’ preferences with respect to presentation of multimedia content. However, such research has thus far neglected to examine the effect of cognitive styles on users’ subjective perceptions of multimedia quality. This study aims to examine the relationships among users’ cognitive styles, the multimedia Quality of Service (QoS) delivered by the underlying network, and Quality of Perception (QoP), which encompasses user levels of enjoyment and understanding of the informational content provided by multimedia material. Accordingly, 132 users took part in an experiment in which they were shown multimedia video clips presented with different values of two QoS parameters (frame rate and colour depth). Results show that, whilst the two QoS parameters do not impact user QoP, multimedia content and dynamism levels significantly influence the user understanding and enjoyment component of QoP

    Applications of computer communications in education.

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    Applications of computer communications can be used in many ways in education. An overview is given of a number of categories of computer communications applications in learning-related activities. Particular attention is given to a new type of system called a course-support environment. In this type of system a database is integrated with Web-based tools and applications, and used to generate a course-support environment accessed via a standard Web browser. Some examples are given. The article moves on to an overview of various issues confronting the acceptance of computer communication systems in educational settings, and indicates some of the ways in which computer communications engineers will have to deal with those issue

    A cognitive approach to user perception of multimedia quality: An empirical investigation

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    Whilst multimedia technology has been one of the main contributing factors behind the Web's success, delivery of personalized multimedia content has been a desire seldom achieved in practice. Moreover, the perspective adopted is rarely viewed from a cognitive styles standpoint, notwithstanding the fact that they have significant effects on users’ preferences with respect to the presentation of multimedia content. Indeed, research has thus far neglected to examine the effect of cognitive styles on users’ subjective perceptions of multimedia quality. This paper aims to examine the relationships between users’ cognitive styles, the multimedia quality of service delivered by the underlying network, and users’ quality of perception (understood as both enjoyment and informational assimilation) associated with the viewed multimedia content. Results from the empirical study reported here show that all users, regardless of cognitive style, have higher levels of understanding of informational content in multimedia video clips (represented in our study by excerpts from television programmes) with weak dynamism, but that they enjoy moderately dynamic clips most. Additionally, multimedia content was found to significantly influence users’ levels of understanding and enjoyment. Surprisingly, our study highlighted the fact that Bimodal users prefer to draw on visual sources for informational purposes, and that the presence of text in multimedia clips has a detrimental effect on the knowledge acquisition of all three cognitive style groups
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