Ontology-Based Context-Aware Management for Wireless Sensor Networks

Lee, Keun-Wang; Cha, Si-Ho

doi:10.1007/978-3-642-23321-0_55

Cited by 3 publications

(7 citation statements)

References 3 publications

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“…5) Rule-based inference, ontologies and knowledge graphs: These methods are all based on semantics, associating meaning to collected data. In systems that rely on semantic adaptation mechanisms, knowledge is usually represented by defining a set of concepts and the relationship between them [21]. In this way data can be interpreted contextually, that is, detached from the syntax or structure, by using annotation techniques to infer knowledge from the interpreted data [52].…”

Section: A a Taxonomy Of Observed Adaptation Mechanismsmentioning

confidence: 99%

“…3) Reasoning processes are initiated either from an observed event, an internal process or a prediction, for instance in [34], [32], [27]. 4) Reasoning and learning mechanisms are distributed throughout the architecture, for instance in [21], [19], [29], [41]. 5) Learning mechanisms are placed in conjunction with a component responsible for assessing the situation, for instance in [24], [38], [31].…”

Section: A Patterns Observed In Literaturementioning

confidence: 99%

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Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model

Bråten

Kraemer

Palma

2021

IEEE Internet Things J.

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Research on autonomous management for largescale deployments of constrained devices is still a maturing field in the Internet of Things (IoT). Although much research has been conducted on how to achieve autonomous management in specific cases, there is a need for literature investigating which mechanisms can achieve such behavior in a generalized way. In this review, we present a comprehensive and structured study of the mechanisms for autonomous device management of constrained IoT devices in the light of management tasks, operational environment, network topology, resource constraints, scalability and management categories. Data extracted from 32 relevant cases is first organized and analyzed according to a synthesized taxonomy of observed adaptation mechanisms, and then combined with state-of-the-art models of autonomous operations, identifying common patterns for autonomous management. Based on our findings we substantiate best practices for designing and implementing solutions around adaptation mechanisms. We then present a generalized model for autonomous device management that describes and explains the processes required for autonomous operation, unifying the insights from previous works as one cohesive archetype.

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Section: A a Taxonomy Of Observed Adaptation Mechanismsmentioning

confidence: 99%

Section: A Patterns Observed In Literaturementioning

confidence: 99%

Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model

Bråten

Kraemer

Palma

2021

IEEE Internet Things J.

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“…There exist few ontology-based context models specifically for WSNs. In [20], a centralized model for context management in WSN is proposed. In this model, all contexts are organized in an ontology structure and stored on a relational database of a base station that functions as sensor sink in the WSN.…”

Section: Ontology Based Context Modelingmentioning

confidence: 99%

“…In [21], a scheduling approach for distributed description logic (DL) reasoning is proposed. Unlike in [20], where context reasoning is performed centrally at a base station, here the reasoning tasks can be offloaded to several sensor nodes in the WSN based on context parameters such as sensor node resource and network characteristics.…”

Section: Ontology Based Context Modelingmentioning

confidence: 99%

“…Network heterogeneity can increase the difficulty of network management due to the large amount of different information needed to be shared and understood between heterogeneous entities in the network. While there exist ontology-based context models for mitigating this complexity issue through system context awareness in a heterogeneous operating environment, most if not all of them are focused on modeling application or system level contexts (e.g., [19,20,21]), with very few or no ontology models proposed for network level contexts. Therefore, to bridge this gap in research, this paper is proposing an ontology-based context modeling approach with the aim of supporting distributed and automated WSN management in IoT.…”

Section: Open Issuesmentioning

confidence: 99%

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An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

Liu

Seet

Al-Anbuky

2013

JSAN

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Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a global scale. However, the IoT system can suffer from poor performances when its underlying networks are not optimized. In this paper, an ontology model for representing and facilitating context sharing between network entities in WSNs is proposed for the first time. The context model aims to enable optimal context-aware management of WSNs in IoT, which will also harness the rich context knowledge of IoT systems

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Extending the RPL Routing Protocol to Agricultural Low Power and Lossy Networks (A-LLNs)

Chen

Chanet

Hou

et al. 2013

International Journal of Agricultural and Environmental Information Systems

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The routing protocol for low power and lossy network (RPL) started to be designed by the ROLL working group of IETF since the year of 2008. Until the RFC6550 was released, this standard with its routing algorithms and four application scenarios, such as home and building automation, industrial control, and urban environment, have been grounded. As a main jigsaw of the paradigm of the Internet of Things (IoT), RPL plays the major role and has become an impressed technical tendency in the field of wireless communication. However, it is still very difficult to find effective approaches to simulate and evaluate RPL's behaviors and other extensions of its applicability, especially in the domain of precision agriculture. Notice that wireless sensor network (WSN) has been deployed a wide variety of wireless sensing devices, and should be one valued supported part of the promising IoT ecosystem. In this paper, first the authors provide a brief presentation of the related protocols including their standardization, the existing implementations, and a group of simulation experiment results obtained from the RPL capable COOJA simulator with its developed modules. Second, the authors then focus on the utilization of this protocol in the agricultural low power and lossy network (A-LLN) area and propose their dedicated instances hybrid network architecture to meet its specific requirements. Moreover, the Web of things (WoT), a trend and new vision of IoT, is appended in the authors' proposal to provide a novel dimension in design of A-LLN since it enables a full interoperability with current web application and higher efficiency of development. As a conclusion, the authors summarized their ongoing work and future solutions of the current technology issues.

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Ontology-Based Context-Aware Management for Wireless Sensor Networks

Cited by 3 publications

References 3 publications

Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model

Autonomous IoT Device Management Systems: Structured Review and Generalized Cognitive Model

An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

Extending the RPL Routing Protocol to Agricultural Low Power and Lossy Networks (A-LLNs)

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