2010
DOI: 10.1145/1842733.1842738
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Akamai state of the internet report, Q4 2009

Abstract: In this paper, we review data gathered across Akamai's global server network about attack traffic, Internet and broadband penetration, and mobile connectivity, as well as trends seen in this data over time.

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Cited by 34 publications
(29 citation statements)
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“…Such growth has been fuelled by the emergence of advanced web-based services (Web 2.0, SaaS cloud services, etc. ), enhanced client device capabilities (JavaScript browser runtimes, display), and increased downlink speeds [4]. This growing complexity, however, can dramatically slow down page retrieval.…”
Section: Introductionmentioning
confidence: 99%
“…Such growth has been fuelled by the emergence of advanced web-based services (Web 2.0, SaaS cloud services, etc. ), enhanced client device capabilities (JavaScript browser runtimes, display), and increased downlink speeds [4]. This growing complexity, however, can dramatically slow down page retrieval.…”
Section: Introductionmentioning
confidence: 99%
“…The right-hand graph in Figure 4 compares HC and CBH performance when we applied a 1Mbps filter to the sender-to-receiver link. This recreates common broadband home Internet connections, with increasingly high downlink bandwidth and limited uplink bandwidth [2].…”
Section: Discussionmentioning
confidence: 99%
“…While broadband, both wired and mobile, is rapidly becoming ubiquitous in developed countries [2], it is not a panacea. Firstly, upload bandwidth remains a scarce resource for the average broadband consumer, for commercial and technical reasons that are unlikely to change in the near future [2]. Yet, in many examples mentioned above, clients tend to upload more than they download; e.g., in backup and file hosting/sharing systems.…”
Section: Introductionmentioning
confidence: 99%
“…The retrieval process is typically supported by an inverted index. Though we are not aware of any BoVW based P2P CBIR systems, many existing P2P text retrieval systems build a distributed inverted index in a highly efficient manner over DHT, using term ID as key and document ID as value [16], [17], [18], [19]. Generally, there are two strategies to distribute index tuples: document partition (or local indexing), and term partition (or global indexing), both are well exploited in the literature [31], [32], [33].…”
Section: Visual Feature Extractionmentioning
confidence: 99%
“…This is not a very big issue in shared-memory or distributed servers, but does pose a challenge in P2P networks, as the nodes in P2P networks are loosely coupled and have much lower bandwidth. As a result, term partition is a more popular choice in P2P networks [16], [17], [18], [19]. To further reduce the network cost and tackle the issue of workload balance with term partition, different techniques have been proposed.…”
Section: Visual Feature Extractionmentioning
confidence: 99%