A Fuzzy Based Trust Evaluation Model for Service Selection in Cloud Environment

A Fuzzy Based Trust Evaluation Model for Service Selection in Cloud Environment

Priya G. (VIT university, Vellore, India) and Jaisankar N. (VIT University, Vellore, India)
Copyright: © 2019 |Pages: 15
DOI: 10.4018/IJGHPC.2019100102
OnDemand PDF Download:
No Current Special Offers


Cloud computing is a popular computing paradigm among several computing environments, but a deficit in trust among the users and the service providers prevents the large adoption of the cloud in most of the businesses. Cloud service providers should give assurances for providing the reliable services to the cloud consumers. The proposed work explains about the architecture of the trust evaluation model and considered four service measurement indexes (SMI) namely: availability, success rate, turnaround efficiency and feedback about a resource. The trust value for each resource is estimated by the fuzzy evaluation engine in which a fuzzy input set is derived from the SMI parameters. By applying a fuzzy inference rule on fuzzy input sets will yield a fuzzy output set and finally, the most trusted resource value is calculated by defuzzification process called center of gravity. The proposed work is done the implementation by using cloudsim with jfuzzycloud.
Article Preview


Over past two decades, cloud computing makes enormous changes in almost all the domains namely healthcare, education, social networks, online shopping and so on. It provides everything such as software, platform and infrastructure as a service. Cloud computing is dynamic in nature, supports pay as you go model. Cloud computing has four categories such as private cloud, public cloud, community and hybrid cloud for deploying an application (Spinola, 2009; Pilevari et al., 2013). Cloud computing helps the cloud user to pay for the resources that they have used instead of spending huge amount on operating, maintaining and integration (Baliyan & Kumar, 2013). The growth of cloud applications and services are numerous. It is the most challenging task for the cloud users to choose the most reliable service and the same way cloud service provider would like to offer the services to the reliable customer (Manuel et al., 2011). Trust plays an important role in helping the cloud user to find the reliable service. There are various types of trust model in which reputation-based model, recommendation-based model and service level agreement (SLA) based model are widely used in cloud environment (Govindaraj & Jaisankar, 2017). Further the trust model can be classified into feedback-based trust model, fuzzy based trust model, statistical based trust model and datamining-based trust model.

Trust on a cloud resource is evaluated based on the security measurement indexes. SLA is one of the important metric to evaluate the trust. It is an agreement between cloud consumer and cloud service provider and it contains the responsibilities of both cloud user and the cloud provider, bill amount for the services and Quality of service requirements. If any problem is occurred during the specified time bound then it should have the mechanism to solve it (Mohamed, 2013).

Trust value for a resource is evaluated by the medium feedback given by the cloud customers (Priya G &Jaisankar N, 2016). Various trust models are proposed based on the quality of service parameters, past identity and present competencies of the cloud providers. Trust value of a resource is evaluated based on availability, reliability, turnaround efficiency and data integrity (Manuel, 2015;Gholami & Arani, 2015; Zhang et al., 2010). Kumar Goyal et al. (2012) have evaluated the trust based on the QoS parameters namely initial time, bandwidth, processing speed, price, and fault rate and scheduling is finished through the trust value provided by the data center.

Garg et al. (2011) have proposed a SMIcloud (Service Measurement Index) framework to measure the quality of a cloud service and prioritize the cloud services. The mechanism will make the healthy competition among the cloud service provider to guarantee the service level agreements. Siegel and Perdue (2012) have stated that SMI defines the significant measures which are used to facilitate the contrast of cloud services by means of non-cloud services and cloud services offered by the different service providers. Cloud service is characterized by the various measures namely accountability, agility, assurance, performance, financial, usability and security and privacy. The Service Measurement Index will discourse 50 parameters.

Complete Article List

Search this Journal:
Open Access Articles: Forthcoming
Volume 14: 6 Issues (2022): Forthcoming, Available for Pre-Order
Volume 13: 4 Issues (2021)
Volume 12: 4 Issues (2020)
Volume 11: 4 Issues (2019)
Volume 10: 4 Issues (2018)
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing