Ontology based Service Discovery for Intelligent Transport Systems using Internet of Things

Pattar, Santosh; Sandhya, C. R.; Vala, Darshill; Buyya, Rajkumar; Venugopal, K. R.; Iyengar, S. S.; Patnaik, L. M.

doi:10.1109/icinpro43533.2018.9096694

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Numerical analysis validated our theoretical analyses and illustrated that: (1) The overall timeliness performance of the preemptive system was significantly improved by controlling generation rate. (2) The proposed approximate optimal generation rates for the self-preemption strategy were surprisingly accurate in the light load case and even in other cases. It could be seen in Figure 4 that the relative error η was no more than 2.5 × 10 −4 for all total arrival rates λ ∈ (0, 1).…”

Section: Discussionmentioning

confidence: 88%

“…IoT has been widely used in various fields, such as Intelligent Transport System (ITS), Smart Grid (SG), and Internet of Vehicles (IoV) [2][3][4]. It is worth noting that, for a considerable part of practical applications, the freshness of the data streams and status updates in the IoT are of great significance for strategies analysis and decision-making [5].…”

Section: Introductionmentioning

confidence: 99%

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Internet of Things: The Optimal Generation Rates under Preemption Strategy in a Multi-Source Queuing System

Zhang

Chen

2021

Entropy

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With the rapid development and wide application of the Internet of Things (IoT), how to provide timely and fresh information for strategic analysis and decision-making has become a key issue. Recent studies have shown that preemption strategies are of great importance to the improvement of information freshness. In view of this, we focus on the multi-source preemptive queuing model and investigate how to control the generation rate of each source to achieve the optimal overall information freshness. Specifically, we consider two typical preemption strategies: self-preemption strategy and global-preemption strategy. Noting that the urgency requirements of the systems on the data of each source are different, we propose the weighted average age of information (AoI) to characterize the overall information freshness of the system. For the self-preemption strategy, we prove that the optimal generation rate allocation is a convex problem and present an efficient algorithm to find the optimal solution. Additionally, we also derive a closed-form approximate optimal solution under light load cases to meet the demands for rapid deployment. For the global-preemption strategy, we directly derive the closed-form optimal solution of the corresponding problem. By comparing the optimized weighted average AoIs, the performance achieved by the global-preemption system was better than that achieved by the self-preemption system in terms of the overall timeliness. The numerical analysis verified the correctness of the theoretical analysis and that the proposed approximate solution had high accuracy not only under light load cases but also under other cases.

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Section: Discussionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Internet of Things: The Optimal Generation Rates under Preemption Strategy in a Multi-Source Queuing System

Zhang

Chen

2021

Entropy

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“…We conceptualize and architect ITS system domain knowledge along with user requirements and preferences, namely, the association of IoT devices, ITS components, services and users with each other, to address the complex service request conflict-free. We also present implementation details of a prototype system that demonstrates the capabilities of the proposed ontology [82].…”

Section: Scenario 01 (Agriculture)mentioning

confidence: 99%

Smart Anonymity: a mechanism for recommending data anonymization algorithms based on data profiles for IoT environments

Neves,

Souza,

Lima

et al. 2024

J Supercomput

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The Internet of Things (IoT) has grown rapidly in recent years. However, coupled with a large number of devices and the huge volume of data generated by these devices, an impasse arises: the privacy of the data of IoT device users. The goal of this research is to propose a solution that recommends which data anonymization algorithm is the most suitable for the dataset according to its characteristics. Among the contributions of this research, we can highlight the creation of metrics for classifying IoT data. Using the metrics to create two Ontologies that use Description Logic for classification of IoT data. The use of Description Logic brings as positive points the verification of inconsistency and discovery of new facts to validate data. The evaluation results demonstrate that the use of the proposed approach brings benefits for user privacy.

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“…To abet the search technique, it is essential to annotate the sensors with semantic knowledge using ontology [15]. Hence, we have used Semantic Sensor Network Ontology (SSN) to interpret the attributes of the sensors and establish a link between them [11,14]. It also enables us to achieve interoperability among heterogeneous devices and applications in the IoT [7].…”

Section: Execution Flow Of the Search Systemmentioning

confidence: 99%

Context-Oriented User-Centric Search System for the IoT Based on Fuzzy Clustering

Pattar¹,

Cr²,

Vala³

et al. 2020

Advances in Computational Intelligence, Security and Internet of Things

Self Cite

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The Internet of Things (IoT) paradigm envisions to support the creation of several applications that aids in the betterment of the society from various sectors such as environment, finance, industry etc. These applications are to be user-centric for their larger acceptance by the society. With the increase in the number of sensors that should are getting connected to the IoT infrastructure, there is an augmented increase in the amount of data generated by these sensors. Therefore it becomes a fundamental requirement to search for the sensors that produce the most applicable data required by the application. In this regard, context parameters of the sensors and the application users can be utilized to effectively filter out sensors from a large group. This paper proposes a sensor search scheme based on semantic-weights and fuzzy clustering. We have modified the traditional fuzzy c-means clustering algorithm by incorporating the semantic and context attributes of the sensors to obtain fuzzy clusters. During the query resolution phase, the query is directed to the most appropriate cluster. These clusters are formed through the use of linguistic variables rather than quantitative attributes and thus aid in effective user-centric search results. Experimental results indicate that the proposed scheme achieves better performance when compared to the existing techniques.

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Ontology based Service Discovery for Intelligent Transport Systems using Internet of Things

Cited by 5 publications

References 4 publications

Internet of Things: The Optimal Generation Rates under Preemption Strategy in a Multi-Source Queuing System

Internet of Things: The Optimal Generation Rates under Preemption Strategy in a Multi-Source Queuing System

Smart Anonymity: a mechanism for recommending data anonymization algorithms based on data profiles for IoT environments

Context-Oriented User-Centric Search System for the IoT Based on Fuzzy Clustering

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