A Conflict Detection Framework for IoT Services in Multi-resident Smart Homes

Chaki, Dipankar; Bouguettaya, Athman; Mistry, Sajib

doi:10.1109/icws49710.2020.00036

Cited by 25 publications

(10 citation statements)

References 19 publications

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“…Chaki et al [24], Abusafia et al [25], and Lakhdari et al [26] discusses various types of conflicts of available IoT services. Chaki et al [24] proposed a novel IoT conflict model that encompasses both functional and nonfunctional properties of IoT services in a multiresident environment where residents may have different habits, resulting in IoT service conflicts.…”

Section: Ad Hoc Rule Conflictsmentioning

confidence: 99%

Conflict Detection and Resolution in IoT Systems: A Survey

Pradeep

Kant

2022

IoT

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Internet of Things (IoT) systems are becoming ubiquitous in various cyber–physical infrastructures, including buildings, vehicular traffic, goods transport and delivery, manufacturing, health care, urban farming, etc. Often multiple such IoT subsystems are deployed in the same physical area and designed, deployed, maintained, and perhaps even operated by different vendors or organizations (or “parties”). The collective operational behavior of multiple IoT subsystems can be characterized via (1) a set of operational rules and required safety properties and (2) a collection of IoT-based services or applications that interact with one another and share concurrent access to the devices. In both cases, this collective behavior often leads to situations where their operation may conflict, and the conflict resolution becomes complex due to lack of visibility into or understanding of the cross-subsystem interactions and inability to do cross-subsystem actuations. This article addresses the fundamental problem of detecting and resolving safety property violations. We detail the inherent complexities of the problem, survey the work already performed, and layout the future challenges. We also highlight the significance of detecting/resolving conflicts proactively, i.e., dynamically but with a look-ahead into the future based on the context.

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Section: Ad Hoc Rule Conflictsmentioning

confidence: 99%

Conflict Detection and Resolution in IoT Systems: A Survey

Pradeep

Kant

2022

IoT

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“…27 . The work presented in 28 focuses on detection of the multi-user conflicts in the smart environment. The detection of multi-user conflict is formulated as ontology conflict by detecting whether the conflict occurred in one application or in multiple applications, and whether the conflict is a functional conflict or a non-functional conflict.…”

Section: Related Workmentioning

confidence: 99%

Resolving User Conflicts in Multi-user Context-aware Home Environment

Aljawarneh

Dhomeja

Malkani

et al. 2021

Preprint

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Context-awareness is an enabling technology of pervasive computing that allows applications to adapt themselves in responseto contexts (e.g. activity, location, temperature level, etc.). However, an issue of user conflicts in context-aware applicationsmay arise when multiple users want to access the same application. Our research focuses on this issue and proposes aconflict resolution approach that resolves the conflicts in context-aware home applications. The proposed approach takes intoconsideration the users’ special case contexts (e.g. illness of user) along with their priorities and preferences. The proposedapproach is also useful in cases where multiple users with multiple special cases try to access one application or service.To show the usefulness of the proposed approach, we have integrated the proposed conflict manager with the UbiREAL, asimulated context-aware home environment. The conflict manager utilizes different strategies and different approaches toresolve user conflicts according to the involved situation to suit the need of the family. The prototype evaluation shows thatthe users are satisfied with the proposed system and suggests that the use of users’ special case contexts in detecting andresolving the user conflicts is essential and necessary in the context-aware smart home environments.

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“…We represent the notion of IoT service, IoT service event and IoT service request to explain the concept of IoT service conflict. The definitions of IoT service, IoT service event and IoT service request have been adopted from [6].…”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

“…We adopt the conflict detection algorithm proposed in [6]. This component is not the core of our contributions; however, it produces the input for the conflict resolution module, which holds the present work's core contributions.…”

Section: Conflict Detectionmentioning

confidence: 99%

Dynamic Conflict Resolution of IoT Services in Smart Homes

Chaki¹,

Bouguettaya²

2021

Preprint

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We propose a novel conflict resolution framework for IoT services in multi-resident smart homes. The proposed framework employs a preference extraction model based on a temporal proximity strategy. We design a preference aggregation model using a matrix factorization-based approach (i.e., singular value decomposition). The concepts of current resident item matrix and ideal resident item matrix are introduced as key criteria to cater to the conflict resolution framework. Finally, a set of experiments on real-world datasets are conducted to show the effectiveness of the proposed approach.

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A Conflict Detection Framework for IoT Services in Multi-resident Smart Homes

Cited by 25 publications

References 19 publications

Conflict Detection and Resolution in IoT Systems: A Survey

Conflict Detection and Resolution in IoT Systems: A Survey

Resolving User Conflicts in Multi-user Context-aware Home Environment

Dynamic Conflict Resolution of IoT Services in Smart Homes

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