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1915 research outputs found
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Modeling Multi-mode D2D Communications in LTE
Get PDFA shorter version of this manuscript is accepted for publication in MAMA workshop collocated with Sigmetrics'14In this work we propose a roadmap towards the analytical understanding of Device-to-Device (D2D) communications in LTE-A networks. Various D2D solutions have been proposed, which include inband and outband D2D transmission modes, each of which exhibits different pros and cons in terms of complexity, interference, and spectral efficiency achieved. We go beyond traditional mode optimization and mode-selection schemes. Specifically, we formulate a general problem for the joint per-user mode selection, connection activation and resource scheduling of connections.pu
Best Practices for Advertisement of Multiple Paths in IBGP
Get PDFIDR Working Group
Internet-Draft AT&T
Intended status: Standards Track
Expires: Jun 3, 2015Add-Paths is a BGP enhancement that allows a BGP router to advertise multiple distinct paths for the same prefix/NLRI. This provides a number of potential benefits, including reduced routing churn, faster convergence and better loadsharing.
This document provides recommendations to implementers of Add-Paths so that network operators have the tools needed to address their specific applications and to manage the scalability impact of Add-Paths. A router implementing Add-Paths may learn many paths for a prefix and must decide which of these to advertise to peers. This document analyses different algorithms for making this selection and provides recommendations based on the target application.pu
Collection and Analysis of data for Inter-domain Traffic Engineering
Get PDFInter-domain IP traffic engineering requires the collection and analysis of data that is distributed among multiple network platforms. This process is usually considered complex for network operators and limits the efficiency that traffic management methods can achieve. The introduction of Software Define Networks may change this rigid context, as it is pushing operators to request flexible routing system architectures. In the future, the network operation team might have the resources to obtain, maintain, and analyze a rich variety of data from within and outside their networks. Without the need to change many of their routing devices, such data can be leveraged to implement more complex inter-domain TE applications. In this paper, we review the process of data col- lection and management required to benefit from such techniques. Additionally, we describe various enhanced TE applications, providing details of one of them in a case study.TRUEpu
Mobile Network Resource Optimization under Imperfect Prediction
Get PDFA highly interesting trend in mobile network optimization is to exploit knowledge of future network capacity to allow mobile terminals to prefetch data when signal quality is high and to refrain from communication when signal quality is low. While this approach offers remarkable benefits, it relies on the availability of a reliable forecast of system conditions. This paper focuses on the reliability of simple prediction techniques and their impact on resource allocation algorithms. In addition, we propose a resource allocation technique that is robust to prediction uncertainties. The algorithm combines autoregressive filtering and statistical models for short, medium, and long term forecasting. We validate our approach by means of an extensive simulation campaign for different network scenarios. We show that our solution performs close to an omniscient optimizer as well as the simple solution that always maintains a full buffer in terms of prefetching data before it is needed, while at the same time using 20% less network resources than the simple full buffer strategy.Telematics EngineeringUniversidad Carlos III de Madrid, Spainpu
Towards the Development of a Learning Analytics extension in Open edX
Get PDFThe emergence of platforms to support MOOCs (Massive Open Online Courses) strengthens the need of a powerful learning analytics support since teachers cannot be aware of so many students. However, the learning analytics support in MOOC platforms is in an early stage nowadays. The edX platform, one of the most important MOOC platforms, has few learning analytics functionalities at present. In this paper, we analyze the learning analytics support given by the edX platform, and the main initiatives to implement learning analytics in edX. We also present our initial steps to implement a learning analytics extension in edX. We review technical aspects, difficulties, solutions, the architecture and the different elements involved. Finally, we present some new visualizations in the edX platform for teachers and students to help them understand the learning process.TRUEpu
Fair Linking Mechanisms for Resource Allocation with Correlated Player Types
Get PDFNetworked Systems
Lecture Notes in Computer Science 2014, pp 70-83
DOI 10.1007/978-3-319-09581-3_6Resource allocation is one of the most relevant problems in the area of Mechanism Design for computing systems. Devising algorithms capable of providing efficient and fair allocation is the objective of many previous research efforts. Usually, the mechanisms they propose use payments in order to deal with selfishness. Since using payments is undesirable in some contexts, a family of mechanisms without payments is proposed in this paper. These mechanisms extend the Linking Mechanism of Jackson and Sonnenschein introducing a generic concept of fairness with correlated preferences. We prove that these mechanisms have good incentive, fairness, and efficiency properties. To conclude, we provide an algorithm, based on the mechanisms, that could be used in practical computing environments.TRUEpu
