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Proceedings ArticleDOI

Engineering the cloud from software modules

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TLDR
The basic idea is to turn the notion of software module into a first class entity used for management and distribution that can be autonomously managed by the underlying software fabric of the cloud.
Abstract
Cloud computing faces many of the challenges and difficulties of distributed and parallel software. While the service interface hides the actual application from the remote user, the application developer still needs to come to terms with distributed software that needs to run on dynamic clusters and operate under a wide range of configurations. In this paper, we outline our vision of a model and runtime platform for the development, deployment, and management of software applications on the cloud. Our basic idea is to turn the notion of software module into a first class entity used for management and distribution that can be autonomously managed by the underlying software fabric of the cloud. In the paper we present our model, outline an initial implementation, and describe a first application developed using the ideas presented in the paper.

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Secure virtualization for cloud computing

TL;DR: It is shown how virtualization can increase the security of cloud computing, by protecting both the integrity of guest virtual machines and the cloud infrastructure components and a novel architecture, Advanced Cloud Protection System, aimed at guaranteeing increased security to cloud resources.
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Mobile Cloud Computing: A Comparison of Application Models

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Where are we at with Cloud Computing?: A Descriptive Literature Review

Haibo Yang, +1 more
TL;DR: A descriptive literature review and classification scheme for cloud computing research is presented, showing that although current cloud computingResearch is still skewed towards technological issues, such as performance, network, and data management, new research theme regarding the social and organisational implications of cloud computing is emerging.
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A Survey of Software Testing in the Cloud

TL;DR: A systematic survey of published results attained by the synergy of software testing and cloud computing, regarding main contributions, trends, gaps, opportunities, challenges and possible research directions is reported on.
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A Decision Table for the Cloud Computing Decision in Small Business

TL;DR: This paper provides a framework for businesses to decide on harnessing the power of cloud computing and recommends the appropriate decision based on the way in which IT is currently used in the enterprise and future needs to meet competitive challenges.
References
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Journal ArticleDOI

MapReduce: simplified data processing on large clusters

TL;DR: This paper presents the implementation of MapReduce, a programming model and an associated implementation for processing and generating large data sets that runs on a large cluster of commodity machines and is highly scalable.
Journal ArticleDOI

MapReduce: simplified data processing on large clusters

TL;DR: This presentation explains how the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
Journal ArticleDOI

On the criteria to be used in decomposing systems into modules

TL;DR: In this paper, the authors discuss modularization as a mechanism for improving the flexibility and comprehensibility of a system while allowing the shortening of its development time, and the effectiveness of modularization is dependent upon the criteria used in dividing the system into modules.
Journal ArticleDOI

System architecture directions for networked sensors

TL;DR: Key requirements are identified, a small device is developed that is representative of the class, a tiny event-driven operating system is designed, and it is shown that it provides support for efficient modularity and concurrency-intensive operation.
Proceedings ArticleDOI

Dryad: distributed data-parallel programs from sequential building blocks

TL;DR: The Dryad execution engine handles all the difficult problems of creating a large distributed, concurrent application: scheduling the use of computers and their CPUs, recovering from communication or computer failures, and transporting data between vertices.
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