A Cloud Service Selection Method Based on Trust and User Preference Clustering

Wang, Yubiao; Wen, Junhao; Zhou, Wei; Tao, Bamei; Wu, Quanwang; Zhang, Tao

doi:10.1109/access.2019.2934153

Cited by 17 publications

(7 citation statements)

References 35 publications

(63 reference statements)

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“…A selection method for a cloud service using trust and user preference clustering was suggested in [29]. The model was based on a user preference similarity to build a hierarchical clustering algorithm.…”

Section: Related Workmentioning

confidence: 99%

Enhanced QoS-Based Model for Trust Assessment in Cloud Computing Environment

et al. 2020

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Trust management becomes an urgent requirement in the cloud environment and a trust relationship between service user and service provider is required. Trust is the estimation of the ability of cloud resources in completing a task based on some criteria such as availability, reliability, and resource processing power. In this paper, an enhanced QoS-based model for evaluating the trustworthiness of the cloud provider is introduced. The proposed model calculates the accumulative trust value which is updated dynamically at each transaction and reflects the current or latest transaction of the provider in the cloud. The trustworthiness of a cloud resource is evaluated based on its provider reputation history from user feedback ratings based on the covariance mathematical technique to evaluate the credibility of the user's feedback. The trustworthiness of a cloud resource is also evaluated by calculating the computing power of resources at run-time. Experimental results confirm the effect of user opinion and resources processing speed on trust value calculation, which in turn assesses the trustworthiness of the cloud provider. The simulation has been performed using the CloudSim with the platform Eclipse for developing the proposed model.

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Section: Related Workmentioning

confidence: 99%

Enhanced QoS-Based Model for Trust Assessment in Cloud Computing Environment

et al. 2020

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“…Wang et al [41] proposed a cloud service selection model based on the user preferences about the trust value of services. Therefore, this proposal finds out the similarity of service attribute preferences, scores and evaluation similarities.…”

Section: B Cloud Based Service Discoverymentioning

confidence: 99%

Service-oriented Broker for Effective Provisioning of Cloud Services – a Survey

Nagarajan¹,

Ramkumar²

2020

IJCDS

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Services computing plays a vital role in the field of information technology and enables users to perform web and cloud services in more efficient and effective manner. In the life cycle of services computing, phases such as service discovery, composition, and delivery of services and managing services as per the Service Level Agreements (SLA) have been received significant attention by the research community. Though web services and cloud services are two instances of services computing, their user communities significantly differ in various aspects, which include service specification, consumption, and adherence to service agreements. This paper approaches services computing from the perspective of two architectural paradigms namely Service-oriented Architecture (SOA) and Cloud computing. The existing research attempts performed in the phases of service discovery, composition and provisioning of services as per the SLA has been extensively reviewed from the perspective of SOA and Cloud. Based on the literature review, a number of research issues are also summarized towards achieving service excellence further. At the end, the paper emphasizes the need for service-oriented broker to enhance the discovery and provisioning process of cloud services.

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“…There are numerous attributes of cloud computing such as self-service on request, wide network accessibility, pooling of resources, quick elasticity as well as measured services [ 4 ]. The self-service on request platform user may access several computing proficiencies namely the time of server as well as network storage that is demanded spontaneously without human intervention.…”

Section: Introductionmentioning

confidence: 99%

“…ere are numerous attributes of cloud computing such as self-service on request, wide network accessibility, pooling of resources, quick elasticity as well as measured services [4].…”

Section: Introductionmentioning

confidence: 99%

Solving User Priority in Cloud Computing Using Enhanced Optimization Algorithm in Workflow Scheduling

Aggarwal

Kumar

Bhatt³

et al. 2022

Computational Intelligence and Neuroscience

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Cloud computing is a procedure of stockpiling as well as retrieval of data or computer services over the Internet that allows all its users to remotely access the data centers. Cloud computing provides all required services to the users, but every platform has its share of pros and cons, and another major problem in the cloud is task scheduling or workflow scheduling. Multiple factors are becoming a challenge for scheduling in cloud computing namely the heterogeneity of resources, tasks, and user priority. User priority has been encountered as the most challenging problem during the last decade as the number of users is increasing worldwide. This issue has been resolved by an advanced encryption standard (AES) algorithm, which decreases the response time and execution delay of the user-request. There are multifarious tasks, for instance, deploying the data on the cloud, that will be executed according to first come first serve (FCFS) and not on the payment basis, which provides an ease to the users. These investigated techniques are 30.21%, 25.20%, 25.30%, 30.25%, 24.26%, and 36.9 8% improved in comparison with the traditional FFOA, DE, ABC, PSO, GA, and ETC, respectively. Moreover, during iteration number 5, this approach is 15.20%, 20.22%, 30.56%, 26.30%, and 36.23% improved than that of the traditional techniques FFOA, DE, ABC, PSO, GA, and ETC, respectively. This investigated method is more efficient and applicable in certain arenas where user priority is the primary concern and can offer all the required services to the users without any interruption.

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A Cloud Service Selection Method Based on Trust and User Preference Clustering

Cited by 17 publications

References 35 publications

Enhanced QoS-Based Model for Trust Assessment in Cloud Computing Environment

Enhanced QoS-Based Model for Trust Assessment in Cloud Computing Environment

Service-oriented Broker for Effective Provisioning of Cloud Services – a Survey

Solving User Priority in Cloud Computing Using Enhanced Optimization Algorithm in Workflow Scheduling

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