Interactive Use of Cloud Services: Amazon SQS and S3

Yoon, Hobin; Gavrilovska, Ada; Schwan, Karsten; Donahue, Jim

doi:10.1109/ccgrid.2012.85

Cited by 13 publications

(4 citation statements)

References 2 publications

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“…Some availability techniques are based on static methods that predefine number of replicas and data placement. For instance, 3 replicas is the default value in Amazon S3 [8], Swift, HDFS [9] and GFS [18], and a round robin policy is defined in Open Stack Swift [10]. Erasure Coding (EC) is a static redundancy strategy that offers similar levels of fault tolerance as replication, but with less storage space.…”

Section: Related Workmentioning

confidence: 99%

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Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

Sosa-Sosa¹,

Barron

Gonzalez-Compeán

et al. 2022

IEEE Trans. Cloud Comput.

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Content delivery and sharing (CDS) is a popular and cost effective cloud-based service for organizations to deliver/share contents to/with end-users, partners and insider users. This type of service improves the data availability and I/O performance by producing and distributing replicas of shared contents. However, such a technique increases overhead on the storage/network resources. This paper introduces a threefold methodology to improve the trade-off between I/O performance and capacity utilization of cloud storage for CDS services. This methodology includes: i) Definition of a classification model for identifying types of users and contents by analyzing their consumption/ demand and sharing patterns, ii) Usage of the classification model for defining content availability and load balancing schemes, and iii) Integration of a dynamic availability scheme into a cloud-based CDS system. Our method was implemented on both a simulator and a real-world CDS service, supporting information sharing operations performed in a cloud storage. An experimental evaluation, conducted in a private cloud through simulation and emulation of workloads, showed the feasibility of this methodology in terms of storage capacity utilization, whereas the real-world implementation revealed the efficiency of applying a classification model to information sharing patterns in terms of I/O performance.

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Section: Related Workmentioning

confidence: 99%

“…The replication factor (RF) defines the number of copies that will be distributed in the storage system. Popular systems, such as Amazon S3 [8] or HDFS [9], suggest as good practice to use RF = 3. Other systems have a predefined data placement technique, for example, a round robin policy, as it is implemented in Open Stack Swift [10].…”

Section: Introductionmentioning

confidence: 99%

Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

Sosa-Sosa¹,

Barron

Gonzalez-Compeán

et al. 2022

IEEE Trans. Cloud Comput.

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“…Message queuing API's are important cloud federation building blocks. Such services are used to couple cloud application components and move messages among highly distributed and diverse environments with high reliability [71].…”

Section: B Queuing Servicesmentioning

confidence: 99%

A Comparative Taxonomy and Survey of Public Cloud Infrastructure Vendors

Sikeridis,

Papapanagiotou,

Rimal

et al. 2017

Preprint

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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 billing models. This is an important gap especially under the new reality of the industry where each cloud provider has moved towards his own service taxonomy, while the number of specialized services has grown exponentially. This work discusses cloud services offered by four dominant, in terms of their current market share, cloud vendors. We provide a taxonomy of their services and sub-services that designates major service families namely computing, storage, databases, analytics, data pipelines, machine learning, and networking. The aim of such clustering is to indicate similarities, common design approaches and functional differences of the offered services. The outcomes are essential both for individual researchers, and bigger enterprises in their attempt to identify the set of cloud services that will utterly meet their needs without compromises. While we acknowledge the fact that this is a dynamic industry, where new services arise constantly, and old ones experience important updates, this study paints a solid image of the current offerings and gives prominence to the directions that cloud service providers are following.

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“…There are also other Message Oriented Middlewares and selection for an application depends on specific requirements. Simple Queue Service (SQS), is a message-queue-as-a-service offering from Amazon Web Services (Yoon, Gavrilovska, Schwan, & Donahue, 2012). It supports only useful and simple messaging operations, quite lighter from the complexity of e.g.…”

Section: Real-time Processingmentioning

confidence: 99%

Evaluations of Big Data Processing

Terzi¹,

Demirezen²,

Sağıroğlu³

2016

STBD

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Big data phenomenon is a concept for large, heterogeneous and complex data sets and having many challenges in storing, preparing, analyzing and visualizing as well as techniques and technologies for making better decision and services. Uncovered hidden patterns, unknown or unpredicted relations and secret correlations are achieved via big data analytics. This might help companies and organizations to have new ideas, get richer and deeper insights, broaden their horizons, get advantages over their competitors, etc. To make big data analytics easy and efficient, a lot of big data techniques and technologies have been developed. In this article, the chronological development of batch, real-time and hybrid technologies, their advantages and disadvantages have been reviewed. A number of criticism have been focused on available processing techniques and technologies. This paper will be a roadmap for researchers who work on big data analytics.

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Interactive Use of Cloud Services: Amazon SQS and S3

Cited by 13 publications

References 2 publications

Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

A Comparative Taxonomy and Survey of Public Cloud Infrastructure Vendors

Evaluations of Big Data Processing

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