5,494 research outputs found

    Addressing the Challenges in Federating Edge Resources

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    This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

    Exploring the usage of a video application tool: Experiences in film studies

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    This paper explores our experiences in deploying a video application tool in film studies, and its evaluation in terms of realistic contextual end-users who have real tasks to perform in a real environment. We demonstrate our experiences and core lesson learnt in deploying our novel movie browser application with undergraduate and graduate students completing a Film Studies course in Dublin City University over a semester. We developed a system called MOVIEBROWSER2 that has two types of browsing modes: Advanced and Basic. In general, students found that the features we provided were beneficial for their studies. Some issues or mismatches arose during the trial. A ‘wish-list’ was drawn up that might be useful for the future system developer. The contribution and achievements reported in this article are on the demonstration and exploration of how advances in technology can be deployed, and media can be accessed in the context of a real user community. Exploring the usage indicates a positive acceptance among students, besides lessons learned that are important for further investigation

    Spatio-temporal Edge Service Placement: A Bandit Learning Approach

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    Shared edge computing platforms deployed at the radio access network are expected to significantly improve quality of service delivered by Application Service Providers (ASPs) in a flexible and economic way. However, placing edge service in every possible edge site by an ASP is practically infeasible due to the ASP's prohibitive budget requirement. In this paper, we investigate the edge service placement problem of an ASP under a limited budget, where the ASP dynamically rents computing/storage resources in edge sites to host its applications in close proximity to end users. Since the benefit of placing edge service in a specific site is usually unknown to the ASP a priori, optimal placement decisions must be made while learning this benefit. We pose this problem as a novel combinatorial contextual bandit learning problem. It is "combinatorial" because only a limited number of edge sites can be rented to provide the edge service given the ASP's budget. It is "contextual" because we utilize user context information to enable finer-grained learning and decision making. To solve this problem and optimize the edge computing performance, we propose SEEN, a Spatial-temporal Edge sErvice placemeNt algorithm. Furthermore, SEEN is extended to scenarios with overlapping service coverage by incorporating a disjunctively constrained knapsack problem. In both cases, we prove that our algorithm achieves a sublinear regret bound when it is compared to an oracle algorithm that knows the exact benefit information. Simulations are carried out on a real-world dataset, whose results show that SEEN significantly outperforms benchmark solutions

    CALIPS: DESIGN OF UBIQUITOUS DECISION SUPPORT MECHANISM FOR THE CAMPUS LIFE PLANNING FROM THE VIEW OF INTEGRATING GENERAL BAYESIAN NETWORKS AND CONTEXT PREDICTION

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    Recently, ubiquitous decision support systems become more popular in many applications. However, the campus life planning area has remained untouched in the decision support literature. Moreover, the potentials of context prediction in lieu of context awareness systems were rarely explored in previous studies of the ubiquitous decision support systems. In this sense, this study proposes the systematic usage of General Bayesian Networks (GBNs) to organize high quality of causal knowledge base to be used for the sake of campus life planning. The prototype named CALIPS was designed on the smartphone. Two research questions that were never investigated in literature were raised- (1) suggestion of the ubiquitous decision support mechanism for the campus life planning, named CALIPS, and (2) integrating GBN and context prediction into the CALIPS. Experiment results proved to support the validity of the CALIP

    Towards Self-evolving Context-aware Services

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    The introduction of new communication infrastructures such as Beyond 3rd Generation (B3G) and the widespread usage of small computing devices are rapidly changing the way we use and interact with technology to perform everyday tasks. Ubiquitous networking empowered by B3G networking makes it possible for mobile users to access networked software services across continuously changing heterogeneous infrastructures by resource-constrained devices. Heterogeneity and devices' limitedness, create serious problems for the development and dynamic deployment of mobile applications that are able to run properly on the execution context and consume services matching with the users' expectations. Furthermore, the everchanging B3G environment calls for applications that self-evolve according to context changes. Out of these problems, self-evolving adaptable applications are increasingly emerging in the software community. In this paper we describe how CHAMELEON, a declarative framework for tailoring adaptable applications, is being used for tackling adaptation and self-evolution within the IST PLASTIC project

    Quality assessment technique for ubiquitous software and middleware

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    The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future
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