282 research outputs found
Ten fallacies and pitfalls on end-to-end available bandwidth estimation
The area of available bandwidth (avail-bw) estimation has attracted significant interest recently, with several estimation techniques and tools developed during the last 2-3 years. Unfortunately, some key issues regarding the avail-bw definition, estimation, and validation remain vague or misinterpreted. In this note, we first review the previous work in the area and classify the existing techniques in two classes: direct probing and iterative probing. We then identify ten misconceptions, in the form of fallacies or pitfalls, that we consider as most important. Some misconceptions relate to basic statistics, such as the impact of the population variance on the sample mean, the variability of the avail-bw in different time scales, and the effect of the probing duration. Other misconceptions relate to the queueing model underlying these estimation techniques. For instance, ignoring that traffic burstiness or the presence of multiple bottlenecks can cause significant underestimation errors. Our objective is not to debunk previous work or to claim that some estimation techniques are better than others, but to clarify a number of important issues that cover the entire area of avail-bw estimation so that this important metric can be better understood and put in practical use
Generating Function For Network Delay
In this paper correspondence between experimental data for packet delay and
two theoretical types of distribution is investigated. Statistical tests have
shown that only exponential distribution can be used for the description of
packet delays in global network. Precision experimental data to within
microseconds are gathered by means of the RIPE Test Box. Statistical
verification of hypothesis has shown that distribution parameters remain
constants during 500 second intervals at least. In paper cumulative
distribution function and generating function for packet delay in network are
in an explicit form written down, the algorithm of search of parameters of
distribution is resulted.Comment: 5 pages, 4 Tables, 5 Figure
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MetaMorphosis+ - A social network of educational Web resources based on semantic integration of services and data
Past research aiming at interoperability within the Technology Enhanced Learning (TEL) field has led to a fragmented landscape of competing metadata schemas and interface mechanisms. So far, Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de facto standard for sharing data on the Web. We propose MetaMorphosis+, a social educational application which adopts a general approach to exploit existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain
Linked education: interlinking educational resources and the web of data
Research on interoperability of technology-enhanced learning (TEL) repositories throughout the last decade has led to a fragmented landscape of competing approaches, such as metadata schemas and interface mechanisms. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de-facto standard for sharing data on the Web and offers a large potential to solve interoperability issues in the field of TEL. In this paper, we describe a general approach to exploit the wealth of already existing TEL data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide rich and well-interlinked data for the educational domain. This approach has been implemented in the context of the mEducator project where data from a number of open TEL data repositories has been integrated, exposed and enriched by following Linked Data principles
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