A multi-agent-based framework for cloud service discovery and selection using ontology

Parhi, Manoranjan; Pattanayak, Binod Kumar; Patra, Manas Ranjan

doi:10.1007/s11761-017-0224-y

Cited by 23 publications

(23 citation statements)

References 31 publications

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“…The system was developed using JADE and Apache Jena API [30]. Beside that developing a perfect service of semantic technique which considers the preferences of customer for computing similarity relating grade headed for significance of both clouding service's metaphors.…”

Section: Discussionmentioning

confidence: 99%

Unified Ontology Implementation of Cloud Computing for Distributed Systems

Ageed

Ibrahim

Sadeeq

2020

CJAST

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The ability to provide massive data storage, applications, platforms plus many other services leads to make the number of clouds services providers been increased. Providing different types of services and resources by various providers implies to get a high level of complexity. This complexity leads to face many challenges related to security, reliability, discovery, service selection, and interoperability. In this review, we focus on the use of many technologies and methods for utilizing the semantic web and ontology in cloud computing and distributed system as a solution for these challenges. Cloud computing does not have an own search engine to satisfy the needs of the providers of the cloud service. Using ontology enhances the cloud computing self-motivated via an intelligent framework of SaaS and consolidating the security by providing resources access control. The use RDF and OWL semantic technologies in the modeling of a multi-agent system are very effective in increases coordination the interoperability. One of the most efficient proposed frameworks is building cloud computing marketplace that collects the consumer's requirements of cloud services provider and managing these needs and resources to provide quick and reliable services.

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Section: Discussionmentioning

confidence: 99%

Unified Ontology Implementation of Cloud Computing for Distributed Systems

Ageed

Ibrahim

Sadeeq

2020

CJAST

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“…Parhi et al [24,25] proposed a multi-agent-based framework for the discovery and selection of cloud services. The work used the domain depended ontology for ensuring a standard vocabulary for specifying cloud service descriptions by the cloud service providers and at the same time indicate the cloud user about their service preferences.…”

Section: B Cloud Based Service Discoverymentioning

confidence: 99%

“…Similarly, during the requirement specification, the user may face the problem in understanding the service details. This scenario is termed as uncertainties [23,24,25] and should be addressed properly by adopting the fuzzy logic-based principle named 'linguistic variables' [32,33].…”

Section: I) Elimination Of Incorrect Service Detailsmentioning

confidence: 99%

“…ii) Dynamic service discovery: Though many literatures [23,24,25,26,27,38] expressed the capabilities and action list of the broker in service discovery, the challenges are still existing while performing dynamic discovery of services. To cater this, a service-oriented broker must be constructed to perform tasks such as pre-processing, ranking, and for construction of ontology towards facilitating automatic service discovery.…”

Section: I) Elimination Of Incorrect Service Detailsmentioning

confidence: 99%

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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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“…Similarly, Sahar et al [19] and Abid et al [13] have used specific QoS parameters for their evaluation and missing other parameters. Arezoo et al [10], Saurabh et al [6], Parhi et al [17], and Sahar et al [19] provide selection for one type of [30], Abid et al [13], and Ibrahim et al [2], all are providing selection for all types of services but have different limitations as mentioned in Table 3. Therefore, in view of the evaluation assessment, we infer that the proposed technique is more efficient and reliable in terms of feedback biasness, fixation of parameters and types of services.…”

Section: A Comparison and Performance Evaluationmentioning

confidence: 99%

Internet Service Selection Using Service Association Factor (SAF)

Rabbani

Aslam

2019

ITC

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The modern organizations are equipping themselves with modern current regime of online application infrastructures through cloud, fog, and edge computing. In the presence of several opportunities, the selection criterion for such Internet-based services becomes vital, especially, when there is no supporting information available. Existing recommender systems provide services by evaluating the quality of service parameters, k-mean clustering, and fuzzy logic techniques on customer's feedback. However, these schemes typically rely on customers' feedback and do not provide any information on the interrelationship between the services. Feedback may be self-generated or biased and leading to improper recommendation to service seekers. To resolve the issue, we propose an innovative service association factor method that calculates the value of interrelationships among services appearing together as a package. This technique is implemented based on an intelligent agent that evaluates the values of the associations on standards and quality attributes. It enables the users to select the best services on their preferences. The proposed agent works on fog environment near to the customers. The technique is tested on leading cloud vendors. The results show that the system meets the desires of service seekers in all service models in an efficient manner.

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A multi-agent-based framework for cloud service discovery and selection using ontology

Cited by 23 publications

References 31 publications

Unified Ontology Implementation of Cloud Computing for Distributed Systems

Unified Ontology Implementation of Cloud Computing for Distributed Systems

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

Internet Service Selection Using Service Association Factor (SAF)

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