Mashup service conflict detection and visualization method for Internet of Things

Oh, Hyeontaek; Ahn, Sanghong; Choi, Jun Kyun; Yang, Jing

doi:10.1109/gcce.2017.8229286

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…Oh et al [29] developed a framework for detecting ECA mashup service conflicts in a smart home environment. The proposed mechanism defines a context descriptor for each mashup service instance that includes the following properties: Instance IoT service, which performs actions when the mashup service is processed; Context condition, which is impacted by the instance; and Direction, i.e., direction of context change.…”

Section: Rule-based Conflict Identification Methodsmentioning

confidence: 99%

“…Huang et al [27], Permula et al [28], Shah et al [23] and Oh et al [29] defined conflicting situations in Event Trigger Action (ECA) rules, a popular mechanism to execute a rule in any IoT system. In an ECA rule-based format, events change the state of the IoT system, and if this change triggers the condition, the actuator performs the necessary actions.…”

Section: Ad Hoc Rule Conflictsmentioning

confidence: 99%

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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: Rule-based Conflict Identification Methodsmentioning

confidence: 99%

Section: Ad Hoc Rule Conflictsmentioning

confidence: 99%

Conflict Detection and Resolution in IoT Systems: A Survey

Pradeep

Kant

2022

IoT

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“…A context descriptor using a visualization model proposed in (Oh et al, 2017) for trigger contradictory action conflict that may happen between apps and In-deterministic conflict occurs against system policies.…”

Section: Multiple User Iot Apps Conflicts Detectionmentioning

confidence: 99%

Peer Review #2 of "A conflicts’ classification for IoT-based services: a comparative survey (v0.1)"

2021

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“…A context descriptor using a visualization model proposed in Oh et al (2017) for trigger contradictory action conflict that may happen between apps and In-deterministic conflict occurs against system policies. No clear definition of the mentioned conflict.…”

Section: Multiple User Iot Apps Conflicts Detectionmentioning

confidence: 99%

Figure 1: Example of building environment control via two users.

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Mashup service conflict detection and visualization method for Internet of Things

Cited by 6 publications

References 3 publications

Conflict Detection and Resolution in IoT Systems: A Survey

Conflict Detection and Resolution in IoT Systems: A Survey

Peer Review #2 of "A conflicts’ classification for IoT-based services: a comparative survey (v0.1)"

Figure 1: Example of building environment control via two users.

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