2017
DOI: 10.48550/arxiv.1710.01476
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A Comparative Taxonomy and Survey of Public Cloud Infrastructure Vendors

Dimitrios Sikeridis,
Ioannis Papapanagiotou,
Bhaskar Prasad Rimal
et al.

Abstract: An increasing number of technology enterprises are adopting cloud-native architectures to offer their web-based products, by moving away from privately-owned data-centers and relying exclusively on cloud service providers. As a result, cloud vendors have lately increased, along with the estimated annual revenue they share. However, in the process of selecting a provider's cloud service over the competition, we observe a lack of universal common ground in terms of terminology, functionality of services and bill… Show more

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Cited by 4 publications
(5 citation statements)
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“…On the SC defense side, the ICT administration which is responsible for securing the information-related SC layers utilizes its pre-allocated defense budget 𝑐 2 by allocating it across the different social media entities under attack. The ICT financial resources can be used either a) for deploying ICT administration human resources responsible for identifying/exposing unreliable sources and providing trustworthy news to the public, or b) for dynamically securing and acquiring cloud computing resources (usually offered by public cloud service providers [31], similar to the case of IBM in Rio [7]). Such resources (computing power for real-time data analytics and machine learning frameworks [31]) can be utilized for deploying truth discovery algorithms that identify misinformation in the presence of noisy data from unvetted SM sources (e.g., as in [15] where the proposed solution was evaluated against real-world Twitter datasets extracted from recent terrorist attacks).…”
Section: A Attack and Defense Scenariosmentioning
confidence: 99%
“…On the SC defense side, the ICT administration which is responsible for securing the information-related SC layers utilizes its pre-allocated defense budget 𝑐 2 by allocating it across the different social media entities under attack. The ICT financial resources can be used either a) for deploying ICT administration human resources responsible for identifying/exposing unreliable sources and providing trustworthy news to the public, or b) for dynamically securing and acquiring cloud computing resources (usually offered by public cloud service providers [31], similar to the case of IBM in Rio [7]). Such resources (computing power for real-time data analytics and machine learning frameworks [31]) can be utilized for deploying truth discovery algorithms that identify misinformation in the presence of noisy data from unvetted SM sources (e.g., as in [15] where the proposed solution was evaluated against real-world Twitter datasets extracted from recent terrorist attacks).…”
Section: A Attack and Defense Scenariosmentioning
confidence: 99%
“…IBM. The strength of these cloud APIs is their ability to develop custom models rapidly and download trained custom models to deploy them on the edge for real-time applications and lowlatency requirements [75,76].…”
Section: Iot Gateway: the Edge Node And Connection To The Cloudmentioning
confidence: 99%
“…They all provide fairly similar capabilities, although some emphasize object recognition, Amazon, or building custom models, like Microsoft Azure and IBM. The strength of these cloud APIs is their ability to develop custom models rapidly and download trained custom models to deploy them on the edge for real-time applications and low-latency requirements [75,76].…”
Section: Auv Controlmentioning
confidence: 99%
See 1 more Smart Citation
“…Edge computing has recently been envisioned to push cloud computing services closer to IoT devices and data sources. Edge computing is designed to drive low-latency data processing by migrating computing capacity from the cloud data centre to the edge [166][167]. Influential cloud computing vendors, such as Google [168] and Microsoft Azure [169], have released service platforms to drive intelligence to the edge, allowing end devices to execute machine learning inference locally with pre-formed models.…”
Section: Cloud Ai At the Edgementioning
confidence: 99%