A Modeling Approach for Cloud Infrastructure Planning Considering Dependability and Cost Requirements

Sousa, Erica; Lins, Fernando; Tavares, Eduardo; Cunha, Paulo Roberto Freire; Maciel, Paulo

doi:10.1109/tsmc.2014.2358642

Cited by 36 publications

(10 citation statements)

References 23 publications

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“…This technique uses IBM data traces and is effective in reducing time of VM provisioning and reducing overhead to improve energy efficiency. Sousa et al [112] aimed to develop an approach for Capacity Planning for Cloud Infrastructure (CPCI) by considering two important parameters such as cost and dependability. A stochastic model generator is used to identify the dependability of servers while developing the cost-effective capacity plan.…”

Section: Related Studiesmentioning

confidence: 99%

A Taxonomy and Future Directions for Sustainable Cloud Computing

2018

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The cloud computing paradigm offers on-demand services over the Internet and supports a wide variety of applications. With the recent growth of Internet of Things (IoT) based applications the usage of cloud services is increasing exponentially. The next generation of cloud computing must be energy-efficient and sustainable to fulfil the end-user requirements which are changing dynamically. Presently, cloud providers are facing challenges to ensure the energy efficiency and sustainability of their services. The usage of large number of cloud datacenters increases cost as well as carbon footprints, which further effects the sustainability of cloud services. In this paper, we propose a comprehensive taxonomy of sustainable cloud computing. The taxonomy is used to investigate the existing techniques for sustainability that need careful attention and investigation as proposed by several academic and industry groups. Further, the current research on sustainable cloud computing is organized into several categories: application design, sustainability metrics, capacity planning, energy management, virtualization, thermal-aware scheduling, cooling management, renewable energy and waste heat utilization. The existing techniques have been compared and categorized based on the common characteristics and properties. A conceptual model for sustainable cloud computing has been proposed along with discussion on future research directions.

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Section: Related Studiesmentioning

confidence: 99%

A Taxonomy and Future Directions for Sustainable Cloud Computing

2018

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“…The work focused on modeling and analysis of cloud service management, with the aim of maximizing the use of cloud computing resources at the lowest possible cost. Sousa et al [41] proposed a modeling strategy for planning cloud infrastructure when considering dependability and cost requirements. This approach is based on hierarchical and heterogeneous modeling that combines combinatorial and state-space models to represent and evaluate cloud infrastructures.…”

Section: Related Workmentioning

confidence: 99%

Decision making in cloud environments: an approach based on multiple-criteria decision analysis and stochastic models

et al. 2018

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Cloud computing is a paradigm that provides services through the Internet. The paradigm has been influenced by previously available technologies (for example cluster, peer-to-peer, and grid computing) and has now been adopted by almost all large organizations. Companies such as Google, Amazon, Microsoft and Facebook have made significant investments in cloud computing, and now provide services with high levels of dependability. The efficient and accurate assessment of cloud-based infrastructure is fundamental in guaranteeing both business continuity and uninterrupted public services, as much as is possible. This paper presents an approach for selecting cloud computing infrastructures, in terms of dependability and cost that best suits both company and customer needs. We use stochastic models to calculate dependability-related metrics for different cloud infrastructures. We then use a Multiple-Criteria Decision-Making (MCDM) method to rank the best cloud infrastructures, taking customer service constraints such as reliability, downtime, and cost into consideration. A case study demonstrates the practicability and usefulness of the proposed approach.

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“…Petri nets were used in (Sousa et al, 2014) as a tool for stochastic generation of dependability and cost models to represent cloud infrastructures.…”

Section: Related Workmentioning

confidence: 99%