Sökning: (WFRF:(Arvidsson Åke 1957 )) >
Web metrics for the...
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Arvidsson, Åke,1957-Högskolan Kristianstad,Forskningsmiljön för datavetenskap (RECS),Avdelningen för datavetenskap
(författare)
Web metrics for the next generation performance enhancing proxies
- Artikel/kapitelEngelska2019
Förlag, utgivningsår, omfång ...
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IEEE,2019
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printrdacarrier
Nummerbeteckningar
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LIBRIS-ID:oai:DiVA.org:hkr-20591
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urn:nbn:se:hkr:diva-20591urn
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Språk:engelska
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Sammanfattning på:engelska
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Klassifikation
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Ämneskategori:ref swepub-contenttype
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Ämneskategori:kon swepub-publicationtype
Anmärkningar
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The fast growth of Internet traffic, the growing importance of cellular accesses and the escalating competition between content providers and network operators result in a growing interest in improving network performance and user experience. In terms of network transport, different solutions ranging from tuning TCP to installing middleboxes are applied. It turns out, however, that the practical results sometimes are disappointing and we believe that poor testing is one of the reasons for this. Indeed, many cases in the literature limit testing to the simple and rare use case of a single file download, while common and complex use cases like web browsing often are ignored or modelled only by considering smaller files. To facilitate better testing, we present a broader view which includes domain counts, flow counts and different forms of concurrency to better characterise the complexity around web pages, and from which the potential for different optimisation techniques can be estimated. We also derive numerical values of these metrics for a small set of popular web pages and study similarities and differences between pages with the same kind of content (newspapers, e-commerce and video) and between pages designed for the same platform (computer and smartphone).
Ämnesord och genrebeteckningar
Biuppslag (personer, institutioner, konferenser, titlar ...)
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Grinnemo, Karl-JohanKarlstads universitet
(författare)
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Chen, Eric ZhiHögskolan Kristianstad,Avdelningen för datavetenskap,Forskningsmiljön för datavetenskap (RECS)(Swepub:hkr)chen
(författare)
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Wang, QinghuaHögskolan Kristianstad,Forskningsmiljön för datavetenskap (RECS),Avdelningen för datavetenskap(Swepub:hkr)waq
(författare)
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Brunström, AnnaKarlstads universitet
(författare)
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Högskolan KristianstadForskningsmiljön för datavetenskap (RECS)
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:2019 27TH INTERNATIONAL CONFERENCE ON SOFTWARE, TELECOMMUNICATIONS AND COMPUTER NETWORKS (SOFTCOM): IEEE, s. 171-1769789532900880
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