Tuesday, 12 December 2017

Session 3: At the Edge of the Cloud

Cloud Storage Pricing: A Comparison of Current Practices

Authors:

Maurizio Naldi (Università di Roma Tor Vergata)
Loretta Mastroeni (Università di Roma Tre)

Abstract:

Cloud storage is fast securing its role as a major repository for both consumers and business customers. Many companies now offer storage solutions, sometimes for free for limited volumes. The most apparent means of competition is pricing, though the complexity of pricing plans may make a comparison difficult. We have surveyed the pricing plans of a selection of major cloud providers and compared them using the unit price as the means of comparison. We find that all the providers, excepting Amazon, adopt a bundling pricing scheme; Amazon follows instead a block-declining pricing policy. Our comparison of pricing plans is conducted through a double approach: a pointwise comparison for each value of storage volume, and an overall comparison using a two-part tariff approximation and a Pareto-dominance criterion. Under both approaches, most providers appear to offer pricing plans that are more expensive and can be excluded from a procurement selection in favour of a limited number of dominant providers.

DOI: 10.1145/2462307.2462315

Full text: PDF

[#][]

Decision Support for Partially Moving Applications to the Cloud - The Example of Business Intelligence

Authors:

Adrián Juan-Verdejo (CAS Software A.G. & University of Stuttgart)
Henning Baars (University of Stuttgart)

Abstract:

Cloud computing services have evolved to a sourcing option that promises a wide range of benefits, such as increased scalability and flexibility at reduced costs. However, many enterprise applications are subject to strict requirements – e.g. regarding privacy, security and availability – and are embedded into complex enterprise IT architectures with a multitude of interdependencies. For these reasons, many decision makers have developed a sceptical stance towards cloud computing. A solution might be a hybrid (local/cloud infrastructure) approach where only suited components are migrated to a cloud infrastructure. This, however, has significant architectural consequences that need to be taken into account. This contribution suggests a cloud migration framework that will be implemented as an IT-based decision support system based on modelling the interdependencies between components. The approach is illustrated with the example of Business Intelligence (BI), i.e. integrated approaches to management support. The underlying decision model would particularly consider data transfer volumes, performance, sensitivity of cloud-based data repositories, as well as exposure to public networks. The potential of such an approach is illustrated with a selected set of BI scenarios. Based on this, conclusions are derived and generalised for approaches taking into account deployments on both the local premises and cloud infrastructures.

DOI: 10.1145/2462307.2462316

Full text: PDF

[#][]

Position Paper: Elastic Processing and Storage at the Edge of the Cloud

Authors:

Steffen Viken Valvåg (University of Tromsø)
Dag Johansen (University of Tromsø)
Age Kvalnes (University of Tromsø)

Abstract:

Cloud services traditionally have a centralized architecture, where all clients communicate individually with the central service, and not directly with each other. Data is primarily stored in the cloud, and computations that touch data are performed in the cloud. We present Rusta, a platform that allows cloud services to deploy in a more flexible and decentralized manner, potentially involving the client machines at the edge of the cloud both for storage and processing of data. This can reduce operational costs both by leveraging freely available client resources, and by reducing data traffic to and from the cloud.

Rusta includes a group abstraction to delineate webs of trusted peers, a light-weight process abstraction based on asynchronous message passing, and a distributed data storage layer. For elasticity, processes may migrate freely among the clients of a group, and can be replicated in a transparent manner. A central hub service executes in the cloud and maintains critical system state, while delegating work to clients as appropriate. This paper describes the design and current implementation of Rusta, its high-level programming model, and some of its potential applications, in particular as a foundation for highly elastic computations at the edge of the cloud.

DOI: 10.1145/2462307.2462317

Full text: PDF

[#][]