A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware

Pradeep, Preeja; Krishnamoorthy, Shivsubramani; Vasilakos, Athanasios V.

doi:10.1016/j.pmcj.2021.101342

Cited by 17 publications

(7 citation statements)

References 32 publications

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“…After surveying the chosen set of pervasive middleware, it is valuable to analyze and evaluate each of them. It bears noting that the selection of the pervasive middleware that is surveyed and assessed in this section is based on the surveys [Baldauf et al, 2007, Perera et al, 2013, Madhusudanan et al, 2018, Pradeep and Krishnamoorthy, 2019. However, these surveys do not cover all objectives that are identified in section 1.2.…”

Section: Middleware Comparative Study and Discussionmentioning

confidence: 99%

“…In fact, as seen in Table 3.2, reviewed middleware used different context modeling for achieving context-awareness. Undoubtedly, ontology has dominated the landscape of modeling context data in the majority of investigated middleware solutions [Chen et al, 2003, Gu et al, 2004, Wei and Chan, 2013, Celdrán et al, 2014, Evchina et al, 2015, Hoque et al, 2017, Pradeep et al, 2021. Extra criteria are enforced by the adoption of ontology such as modularity, high-level context abstraction, powerful reasoning, semantic interoperability and probably advanced context-awareness [Li et al, 2015].…”

Section: Middleware Comparative Study and Discussionmentioning

confidence: 99%

“…Extra criteria are enforced by the adoption of ontology such as modularity, high-level context abstraction, powerful reasoning, semantic interoperability and probably advanced context-awareness [Li et al, 2015]. However, some of these ontologybased middleware solutions [Chen et al, 2003, Celdrán et al, 2014, Evchina et al, 2015, Hoque et al, 2017, Pradeep et al, 2021 fail to provide context autonomy and evolution. Moreover, solutions, such as Music and Campus [Rouvoy et al, 2008, Wei andChan, 2013], support higher context autonomy in a single framework.…”

Section: Middleware Comparative Study and Discussionmentioning

confidence: 99%

“…The present section is structured into two parts. The first part surveys relevant middleware from several surveys [Baldauf et al, 2007, Perera et al, 2013, Madhusudanan et al, 2018, Pradeep and Krishnamoorthy, 2019 (see subsection 3.2.1). The second part provides a discussion on the surveyed middleware solutions (see subsection 3.2.2).…”

Section: Pervasive Middlewarementioning

confidence: 99%

“…Adaptive Ubiquitous Middleware-driven context-aware IoT ecosystem, AUM-IoT [Pradeep et al, 2021] primarily considers healthcare and transportation domains and provides relevant contextaware services by utilizing the functionalities and capabilities of fog and cloud computing via multi-communication protocol bridge. The AUM-IoT architecture consists of five layers: perception, middleware, fog, cloud and application.…”

Section: Aum-iotmentioning

confidence: 99%

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Towards an Approach for Intelligent Adaptation Decision-Making of Pervasive Middleware

Jabla¹

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This thesis describes research to gain insight into pervasive middleware solutions and context-aware solutions that expand their perspective from static to dynamic pervasive environments. The motivation behind this research arose from a need to reconsider and replace today's context-aware solutions with more intelligent solutions to account for dynamic environments and users' preferences changes at runtime. In this context, the end goal is to focus on offering intelligent context-aware solutions that could deal with the automatic context model evolution and new decisions generation according to context changes at runtime. To do so, in the current thesis, we illustrate a hybrid approach termed IConAS -a means of combining the practical advantages of context evolution with the decision-making adaptation. This combination leads to intelligent context-aware solutions that could reflect changes occurring in their surrounding dynamic environments at runtime. The thesis concentrates on the three important contributions as follows:• Definition of the IConAS approach that combines two main approaches. This hybrid approach aims to offer intelligent context-aware solutions through augmenting an existing middleware. The purpose of this augmentation is to support runtime and automatic context evolution and decision-making adaptation in order to reflect changes in dynamic environments;Next, I would like to extend my heartiest gratitude and thanks to my co-supervisor Prof. Maha Khemaja, who believed in me from the beginning of this thesis and who never ceased to encourage, guide and kindly nudge me forward when I doubt my ability or could not see the finish line. This thesis would not have been achievable without her constant feedback, her enormous research contributions and her emotional support. I am sincerely thankful to my external evaluators of the thesis, Prof.

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Section: Middleware Comparative Study and Discussionmentioning

confidence: 99%