A comparative analysis of cloud computing services using multicriteria decision analysis methodologies

Papathanasiou, Jason; Kostoglou, Vassilis; Petkos, Dimitris

doi:10.1504/ijids.2015.068117

Cited by 14 publications

(6 citation statements)

References 16 publications

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“…Similarly Negative Ideal Alternative includes the worst attribute values like minimum benefit attributes and maximum cost attributes. The TOPSIS method chooses the alternative which is nearest to the ideal solution and farthest from the negative ideal solution [15,16]. The outline of the TOPSIS method is presented in the following.…”

Section: Brief Overview Of Topsis Methodsmentioning

confidence: 99%

Implementing Fuzzy TOPSIS in Cloud Type and Service Provider Selection

Basu

Ghosh

2018

Advances in Fuzzy Systems

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Cloud computing can be considered as one of the leading-edge technological advances in the current IT industry. Cloud computing or simply cloud is attributed to the Service Oriented Architecture. Every organization is trying to utilize the benefit of cloud not only to reduce the cost overhead in infrastructure, network, hardware, software, etc., but also to provide seamless service to end users with the benefit of scalability. The concept of multitenancy assists cloud service providers to leverage the costs by providing services to multiple users/companies at the same time via shared resource. There are several cloud service providers currently in the market and they are rapidly changing and reorienting themselves as per market demand. In order to gain market share, the cloud service providers are trying to provide the latest technology to end users/customers with the reduction of costs. In such scenario, it becomes extremely difficult for cloud customers to select the best service provider as per their requirement. It is also becoming difficult to decide upon the deployment model to choose among the existing ones. The deployment models are suitable for different companies. There exist divergent criteria for different deployment models which are not tailor made for an organization. As a cloud customer, it is difficult to decide on the model and determine the appropriate service provider. The multicriteria decision making method is applied to find out the best suitable service provider among the top existing four companies and choose the deployment model as per requirement.

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Section: Brief Overview Of Topsis Methodsmentioning

confidence: 99%

Implementing Fuzzy TOPSIS in Cloud Type and Service Provider Selection

Basu

Ghosh

2018

Advances in Fuzzy Systems

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“…Papathanasiou ve ark. 2015 bulut depolama servisi seçiminde en önemli kriterin güvenlik, ikinci en önemli kriterin dosya paylaşım yeteneği olduğunu belirtmiştir [21]. Kullanıcılar bulut depolama servislerini 85.9% oranında dosya paylaşım amacıyla kullanmaktadırlar [8].…”

Section: Kavramsal Ve Metodoloji̇k çErçeve (Conceptual and Methodologiunclassified

“…Papathanasiou ve ark. 2015 kullanıcıların genellikle Windows işletim sistemi kullandıklarını ancak Linux ve benzeri işletim sistemleri kullanan bireyler için bu değişkenin önem arz ettiğini belirtmiştir[21]. Pocatilu ve ark.…”

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Bütünleşik SWARA - COPRAS Yöntemi Kullanarak Bulut Depolama Hizmet Sağlayıcılarının Değerlendirilmesi

Çakır

Karabiyik

2017

Bilişim Teknolojileri Dergisi

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Özet-Teknolojinin hızlı gelişimi ile birlikte DVD, USB ve hatta harici disklerin yerini bulut depolama servisleri almaya başlamıştır. Bulut depolama; sunucular tarafından ağ üzerinde sanal biçimde oluşturulan havuzlarda veri depolanmasıdır. Bulut depolamada kullanıcılar internet üzerinde kendilerine ait bir depolama alanına sahip olmakta ve dosyalarını bu alanda saklayabilmektedirler. Bu çalışmanın amacı; büyük çaplı veri merkezlerini işleten ve depolama için alan sunan çeşitli bulut depolama hizmet sağlayıcıları arasından en iyisinin seçilmesidir. Seçim konusunda literatürde karşılaşılan çeşitli kriterler söz konusudur. Kriterler eşit öneme sahip olmadığından, kriterlerin önem düzeyleri SWARA yöntemi ile belirlenmiştir. Oluşturulan kriterler ışığında COPRAS yöntemi ile en iyi bulut depolama hizmet sağlayıcısının seçimi yapılmıştır. En yüksek önem derecesine sahip kriterin "Güvenlik" kriteri olduğu ve en düşük öneme sahip kriterin ise "Müşteri Hizmetleri" olduğu sonucuna ulaşılmıştır. En iyi bulut depolama hizmet sağlayıcısının Google Drive olduğu bilgisine ulaşılırken; diğer bulut depolama hizmet sağlayıcılarından Yandex.Disk ikinci, iCloud Drive üçüncü, Dropbox dördüncü, Box beşinci ve OneDrive altıncı sırada yer almaktadır.Anahtar Kelimeler-Bulut Depolama, Bulut Depolama Hizmet Sağlayıcıları, SWARA Yöntemi, COPRAS Yöntemi Evaluation of Cloud Storage Service Providers Using Integrated SWARA -COPRAS MethodAbstract-Along with the rapid development of technology; DVD, USB and even external drives have begun to receive cloud storage services. In cloud storage; data is stored in virtual pools which are created by the servers on the network. In cloud storage, users have their own storage space on the internet and can store their files in this area. The purpose of this study is to choose the best cloud storage service provider among various types of them that operate large data centers and provide space for storage. There are various criteria in the literature about selection. As the criteria do not have equal qualifications, the importance levels of the criteria are determined by the SWARA method. In the light of criteria created, the best cloud storage service provider has been chosen with the COPRAS method. While "Safety" criterion has been attended to the highest priority, "Customer Support Services" has the lowest priority. Google Drive is found as the best performing cloud service provider. Yandex.Disk, iCloud Drive, Dropbox, Box and OneDrive follow Google Drive cloud service provider respectively.

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“…Papathanasiou et al [49] offered a concise practical approach to choose a CSP. The authors have explored AHP and PROMETHEE and the Goal programming techniques for assessing the weights of the selection criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integrated MCDM Approach for Cloud Service Selection Based on TOPSIS and BWM

Youssef

2020

IEEE Access

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Cloud Computing (CC) has become increasingly popular since it provides a wide variety of customized and reliable computational services. With the rapid growth of this technology, more and more IT services providers compete to offer high-quality and cost-effective cloud services that best fulfill their customers' needs. Given the vast diversity of these offers, the choice of the most appropriate Cloud Service Provider (CSP) became a dilemma that confuses most cloud customers. Many diverged criteria have to be considered to precisely evaluate services offered by several CSPs, some of these criteria cannot be quantified easily such as usability and security. The selection of the best CSP is thus a complex Multi-Criteria Decision Making (MCDM) problem that needs to be addressed efficiently. Previous studies of this problem employed MCDM methods that are either unfeasible when it is difficult or meaningless to quantify alternatives over criteria or computationally expensive and inconsistent when relative preferences of alternatives and criteria are used instead. In this paper, we propose a novel MCDM approach that is feasible, efficient and consistent using relative preferences of criteria and alternatives. The proposed approach incorporates Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Best Worst Method (BWM) to rank CSPs using evaluation criteria characterizing their services. The integrated approach has been tested and validated through a use-case scenario which demonstrates its effectiveness and correctness. We have also compared the proposed approach to the most commonly used MCDM approach, Analytical Hierarchical Process (AHP). The results clearly show that the proposed approach outperforms AHP in terms of computational complexity and consistency; hence, it is more efficient and reliable than AHP. INDEX TERMS Cloud computing (CC), cloud service providers (CSPs), multiple-criteria decision-making (MCDM), best worst method (BWM), technique for order of preference by similarity to ideal solution (TOPSIS), analytical hierarchical process (AHP).

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A comparative analysis of cloud computing services using multicriteria decision analysis methodologies

Cited by 14 publications

References 16 publications

Implementing Fuzzy TOPSIS in Cloud Type and Service Provider Selection

Implementing Fuzzy TOPSIS in Cloud Type and Service Provider Selection

Bütünleşik SWARA - COPRAS Yöntemi Kullanarak Bulut Depolama Hizmet Sağlayıcılarının Değerlendirilmesi

An Integrated MCDM Approach for Cloud Service Selection Based on TOPSIS and BWM

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