Ontology‐based service discovery framework for dynamic environments

Zeshan, Furkh; Mohamad, Radziah; Ahmad, Mohammad Nazir; Hussain, Syed Asad; Awada, Ahmad; Raza, Imran; Mehmood, Abid; Ulhaq, Ikram; Abdulgader, Arafat; Babar, Imran

doi:10.1049/iet-sen.2016.0048

Cited by 20 publications

(19 citation statements)

References 26 publications

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“…In order to handle such issues, ontologies can be used. Therefore, context-aware ontology [ 43 ] along with application ontologies [ 54 ] are used to model requests to discover services. However, for creating the service request, both ontologies were merged as presented in Figure 2 .…”

Section: Discussionmentioning

confidence: 99%

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A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments

Zeshan

Awada

Abdel‐Aty

et al. 2020

Sensors

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Distributed systems provide smart functionality to everyday objects with the help of wireless sensors using the internet. Since the last decade, the industry is struggling to develop efficient and intelligent protocols to integrate a huge number of smart objects in distributed computing environments. However, the main challenge for smart and distributed system designers lies in the integration of a large number of heterogeneous components for faster, cheaper, and more efficient functionalities. To deal with this issue, practitioners are using edge computing along with server and desktop technology for the development of smart applications by using Service-Oriented Architecture (SOA) where every smart object offers its functionality as a service, enabling other objects to interact with them dynamically. In order to make such a system, researchers have considered context-awareness and Quality of Service (QoS) attributes of device services. However, context modeling is a complicated task since it could include everything around the applications. Moreover, it is also important to consider non-functional interactions that may have an impact on the behavior of the complete system. In this regard, various research dimensions are explored. However, rich context-aware modeling, QoS, user priorities, grouping, and value type direction along with uncertainty are not considered properly while modeling of incomplete or partial domain knowledge during ontology engineering, resulting in low accuracy of results. In this paper, we present a semantic and logic-based formal framework (hybrid) to find the best service among many candidate services by considering the limitations of existing frameworks. Experimental results of the proposed framework show the improvement of the discovered results.

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Section: Discussionmentioning

confidence: 99%

“…In this regard, Zeshan et al [ 9 , 42 , 43 ] have proposed a framework that provides criteria to compare information systems. The criteria are classified into two categories: General Requirements ( Table 1 ) and Dynamic Requirements ( Table 2 ).…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments

Zeshan

Awada

Abdel‐Aty

et al. 2020

Sensors

Self Cite

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“…Location Real time systems are used for tracking the location automatically of people usually with in a confined area. Location awareness refers towards the people who can rate on the OSN posts [40]. Categorization It implies that concept is grouped into categorizes i.e.…”

Section: P E R F O R M a N C E M E A S U R E Precision Recall F-meanmentioning

confidence: 99%

“…Taxonomy It assists ontology engineers for finding possible inconsistencies through values assigning to identify concepts of taxonomy with defined set of rules.RolesRoles are used to define the temporal relationships with additional objects like a person in one role could be a director whereas in other role(s) he could be an actor. It can be used to separate individual's features and can help as reuse unit of ontology[40].RatingRating depicts the assessment of the OSN posts.Confidence LevelConfidence level shows the probability that a value assigned to an OSN post falls within specified values range.…”

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confidence: 99%

Ontology-based rumor identification system using social network data

Sarfraz

Ahmad

Zeshan

et al. 2022

Preprint

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With the tremendous expansion of online social networks (OSNs) such as Twitter and Facebook, have become not only one of the utmost effective modes for viral advertising. But also, the main source of news among people nowadays. Besides these encouraging features, however, comes the risk of rumor dissemination. Due to the enormous users of OSN, there is a considerable challenge to proficiently contain the viral spread of rumors. In addition, because of a huge number of news on OSN, the manual detection of rumors is not possible. So, we need an auto-detection and authentic knowledge sharing method in a machine-readable as well as the human-readable format for OSN. In this regard, several researchers, doing research in this domain. But no method deals with uniform, authentic, and machine-readable as well as human-readable knowledge sharing among OSN users. To address this issue, ontology-based systems can be used because ontology-based systems deal with all such kinds of issues very effectively. However, for effective categorization of OSN posts, ontology-based systems should consider roles, rating, confidence level, location, and post categorization while decision making about OSN posts. Whereas, several ontology-based methods presented for rumors verification, consider only a few requirements resulting in low accuracy of authenticated posts. Experimental results verify that the proposed ontology-based approach can produce accurate results according to human understanding.

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“…In cloud computing, service discovery [2] is to find a suitable cloud service that essentially meet out the cloud user requirement in the aspect of functional, non-functional and the budgetary constraints. Without considering these factors, it is not possible to discover the right services from the multiple cloud providers.…”

Section: Introductionmentioning

confidence: 99%

A Cloud Broker Framework for Infrastructure Service Discovery Using Semantic Network

Nagarajan¹,

Ramkumar²,

Shanmugam³

2018

IJIES

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Abstract:On demand provisioning with an acceptable pricing scheme of cloud computing attracts user to enter in to the cloud arena. In this paradigm, there are many cloud service providers involved to offer different level of services and the effectiveness of the service specification, identification of services is always a challenging one. Hence, we propose a broker based cloud computing framework for enabling the cloud user to specify their service requirements in terms of numerical representation. The infrastructure type of services such as computing and storage are considered for this proposal. With respect to the user specification, the proposed broker constructs the cloud ontology to represent the available services from the service repository. With the aid of ontological representation, the proposed broker discovers the infrastructure services from the available vendor. The appropriate services are represented using semantic network which enables the user to know about the available services as per their posted requirements. Finally, the broker recommends the services with its add-on features to the cloud users. A prototype model is developed to simulate the functioning of the broker based service discovery in the cloud and the results show the performance upgradation by comparing the traditional approach.

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Ontology‐based service discovery framework for dynamic environments

Cited by 20 publications

References 26 publications

A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments

A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments

Ontology-based rumor identification system using social network data

A Cloud Broker Framework for Infrastructure Service Discovery Using Semantic Network

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