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

@article{Chaki2020ACD,
  title={A Conflict Detection Framework for IoT Services in Multi-resident Smart Homes},
  author={Dipankar Chaki and Athman Bouguettaya and Sajib Mistry},
  journal={2020 IEEE International Conference on Web Services (ICWS)},
  year={2020},
  pages={224-231}
}
We propose a novel framework to detect conflicts among IoT services in a multi-resident smart home. A novel IoT conflict model is proposed considering the functional and non-functional properties of IoT services. We design a conflict ontology that formally represents different types of conflicts. A hybrid conflict detection algorithm is proposed by combining both knowledge-driven and data-driven approaches. Experimental results on real-world datasets show the efficiency of the proposed approach… Expand
Fine-grained Conflict Detection of IoT Services
TLDR
A fine-grained conflict model is developed considering the functional and non-functional properties of IoT services and is designed using the concept of entropy and information gain from information theory to detect conflicts. Expand
Conflict Detection in IoT-based Smart Homes
TLDR
A novel framework that detects conflicts in IoT-based smart homes and proposes a generic knowledge graph to represent the relations between IoT services and environment entities to capture different types of conflicts in a single resident smart home setting. Expand
Adaptive Priority-based Conflict Resolution of IoT Services
TLDR
A novel conflict resolution framework for IoT services in multi-resident smart homes considering the residents’ contextual factors and the proposed priority model is designed using the concept of the analytic hierarchy process. Expand
A conflicts’ classification for IoT-based services: a comparative survey
TLDR
Evidence is provided that the existing approaches have a gap in covering different conflicts’ levels and types which yields to minimize the correctness and safety of IoT systems, and the need to develop a safety and security compiler or tool for IoT systems is pointed out. Expand
Proactive Composition of Mobile IoT Energy Services
TLDR
A novel proactive composition framework of wireless energy services in a crowdsourced IoT environment that includes providers' and consumers’ mobility patterns and energy usage behavior is proposed. Expand
Incentive-Based Selection and Composition of IoT Energy Services
TLDR
A novel incentive-based framework is designed that considers the context of the providers and consumers to determine rewards for sharing wireless energy and proves the efficiency of the proposed approach. Expand
Dynamic Conflict Resolution of IoT Services in Smart Homes
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.Expand

References

SHOWING 1-10 OF 30 REFERENCES
Convenience-Based Periodic Composition of IoT Services
TLDR
A spatio-temporal proximity technique to prune loosely correlated composite IoT services and a periodic composite IoT service model is proposed to model the regularity of Composite IoT services occurring at a certain location in a given time interval. Expand
Discovering Spatio-Temporal Relationships among IoT Services
TLDR
A spatio-temporal proximity model in terms of spatial-proximity and temporal- Proximity to discard insignificant IoT service relationships is introduced and a new algorithm is proposed to discover proximate spatio -temporal IoT service relationship. Expand
Automatic Resolution of Policy Conflicts in IoT Environments Through Planning
The Internet of Things (IoT) is a highly agile and complex environment managed via the Internet. The management of such an environment requires robust automated mechanisms, since manual curationExpand
IoTC2: A Formal Method Approach for Detecting Conflicts in Large Scale IoT Systems
TLDR
This paper provides a formal method approach, IoT Confict Checker (IoTC2), to ensure safety of controller and actuators’ behavior with respect to conflicts and defines the safety policies for controller, actions, and triggering events and implements them in Prolog to prove the logical completeness and soundness. Expand
Ontology-Based Smart Home Solution and Service Composition
TLDR
An ontology-based framework is proposed to facilitate the automatic composition of appropriate applications for smart homes that dynamically adjusts the environment parameters to match the customer needs and to encompass the available resource. Expand
Service Conflict Management Framework for Multi-user Inhabited Smart Home
TLDR
Through implementing and evaluating the framework to a smart home test-bed, it was found that the proposed framework dynamically detected and flexibly resolved multi-user conflicts which occurred among the services of multiple applications, as well as within a single application. Expand
An ontology-based approach to conflict resolution in Home and Building Automation Systems
TLDR
This work proposes and validates an ontological framework for conflict detection and resolution backed by knowledge-based analysis and performs automatic environment actuations maximizing users comfort and energy efficiency. Expand
Service Mining for Internet of Things
TLDR
A service mining framework is proposed that enables discovering interesting relationships in Internet of Things services bottom-up and a set of metrics to evaluate the interestingness of discovered service relationships are presented. Expand
Restful Web Services Composition Using Semantic Ontology for Elderly Living Assistance Services
TLDR
This work proposes a framework to enable RESTful web services composition using semantic ontology for elderly living assistance services creation in WoO based smart home environment using a semantic modelling technique for manual and semiautomated service composition. Expand
Conflict Detection Scheme Based on Formal Rule Model for Smart Building Systems
TLDR
A new rule conflict detection scheme tailored for the smart building system based on a formal rule model UTEA based on User, Triggers, Environment entities, and Actuators and improves the performance in terms of error/missed-detection rates and running time. Expand
...
1
2
3
...