Integrated QoS Utility-Based Model for Cloud Computing Service Provider Selection

Salama, Maria; Shaikh, Faiz Uddin Ahmed; Zeid, Amir; Kouta, Mohamed

doi:10.1109/compsacw.2012.18

Cited by 17 publications

(8 citation statements)

References 13 publications

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“…The drawback with both and is that they give same importance to all the voters. In cloud service selection problem, metrics may have priority , for example, a computation‐intensive scientific application may give higher priority to performance in comparison with security. So, categorization of metrics is required in such a way that higher priority metrics should be in higher category.…”

Section: Cloud Service Providers Rankingmentioning

confidence: 99%

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A cloud service selection model using improved ranked voting method

Baranwal

Vidyarthi

2016

Concurrency and Computation

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SUMMARYCloud computing is an upcoming and promising solution for utility computing that provides resources on demand. As it has grown into a business model, a large number of cloud service providers exist today in the cloud market, which further is expanding exponentially. Many cloud service providers, with almost similar functionality, pose a selection problem to the cloud users. To assist the users in the best service selection, as per its requirement, a framework has been developed in which users list their quality of service (QoS) expectation, while service providers express their offerings. Experience of the existing cloud users is also taken into account in order to select the best cloud service provider. This work identifies some new QoS metrics, besides few existing ones, and defines it in a way that eases both the user and the provider to express their expectations and offers, respectively, in a quantified manner. Further, a dynamic and flexible model, using a variant of ranked voting method, is proposed that considers users' requirement and suggests the best cloud service provider. Case studies affirm the correctness and the effectiveness of the proposed model. Copyright

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Section: Cloud Service Providers Rankingmentioning

confidence: 99%

“…Salama et al . propose an integrated QoS utility‐based model, which calculates the utility of the service providers on the basis of user's QoS requirements (performance, dependability, reputation and service value) and selects a provider with maximum utility. Zhang et al .…”

Section: Related Workmentioning

confidence: 99%

A cloud service selection model using improved ranked voting method

Baranwal

Vidyarthi

2016

Concurrency and Computation

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“…SaaS application adheres to a defined time limit between service request and service response. Khanjani et al (2014), CSMIC (2014), Salama et al (2012), Badidi (2013), Song et al (2012), He et al (2012), these definitions were compared with those available in the literature provided by other SaaS quality models. The identification and definitions of the quality attributes that play an important role in SaaS customization or could be influenced by customization are presented in Table 9.…”

Section: Response Timementioning

confidence: 99%

Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia

Ali

Sultan

Ghani

et al. 2020

PeerJ Computer Science

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Despite the benefits of standardization, the customization of Software as a Service (SaaS) application is also essential because of the many unique requirements of customers. This study, therefore, focuses on the development of a valid and reliable software customization model for SaaS quality that consists of (1) generic software customization types and a list of common practices for each customization type in the SaaS multi-tenant context, and (2) key quality attributes of SaaS applications associated with customization. The study was divided into three phases: the conceptualization of the model, analysis of its validity using SaaS academic-derived expertise, and evaluation of its reliability by submitting it to an internal consistency reliability test conducted by software-engineer researchers. The model was initially devised based on six customization approaches, 46 customization practices, and 13 quality attributes in the SaaS multi-tenant context. Subsequently, its content was validated over two rounds of testing after which one approach and 14 practices were removed and 20 practices were reformulated. The internal consistency reliability study was thereafter conducted by 34 software engineer researchers. All constructs of the content-validated model were found to be reliable in this study. The final version of the model consists of 6 constructs and 44 items. These six constructs and their associated items are as follows: (1) Configuration (eight items), (2) Composition (four items), (3) Extension (six items), 4) Integration (eight items), (5) Modification (five items), and (6) SaaS quality (13 items). The results of the study may contribute to enhancing the capability of empirically analyzing the impact of software customization on SaaS quality by benefiting from all resultant constructs and items.

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“…Some studies use single quality attribute while some other studies use a multi-dimensional QoS attributes. Salama et al [3] propose a cloud service selection based on a group of broad, multi-dimensional QoS attributes. An integrated QoS-assured utility model is proposed to address the problem of cloud service selection.…”

Section: Related Workmentioning

confidence: 99%

Analysis and Representation of QoS Attributes in Cloud Service Selection

Eisa

Younas

Basu

2018

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)

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Cloud service selection is complicated by the prospect that there exist a large number of services and each service is characterized by multiple QoS attributes. Various commercial tools have been developed in order to help cloud consumers with selecting best cloud services. This paper provides an in-depth analysis of the three commercial cloud service selection tools as well as the way they represent QoS attributes. Accordingly, it proposes a new model that succinctly represents QoS attributes which cloud consumers can easily use (and understand) when selecting cloud services. The proposed model also classifies the QoS attributes into four main categories of technical, strategic & organizational, economic and political & legislative. These QoS attributes can also be seamlessly fed into the multi-criteria decision (e.g., MCDM)-which compares and ranks different QoS attributes of multiple alternatives in order to decide which services are most suitable for cloud consumers.

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Integrated QoS Utility-Based Model for Cloud Computing Service Provider Selection

Cited by 17 publications

References 13 publications

A cloud service selection model using improved ranked voting method

A cloud service selection model using improved ranked voting method

Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia

Analysis and Representation of QoS Attributes in Cloud Service Selection

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