A Survey on Service Discovery Mechanism

Shinde, Gitanjali Rahul; Olesen, Henning Salling

doi:10.1007/978-981-10-7245-1_23

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…IoT devices providing and accessing services are smaller and more resource constrained, which makes it difficult to apply the traditional approaches of service discovery. Therefore, a lightweight discovery approach is needed that works effectively with devices having restricted size, partial computational ability, limited energy and limited memory [6].…”

Section: Service Registrymentioning

confidence: 99%

Virtualization Based Efficient Service Matching and Discovery in Internet of Things

et al. 2020

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Internet of Things (IoT) is getting more popular day by day, which triggers its adoption for solving domain specific problems. Cities are becoming smart by gathering the context knowledge through sensors and controlling specific parameters through actuators. Dynamically discovering and integrating different data streams from different sensors is a major challenge these days. In this paper, a service matchmaking algorithm is presented for service discovery utilizing IoT devices and services in a particular geographic area. It helps us to identify services based on a variety of parameters (location, query size and processing time, etc.). Customization of service selection and discovery are also explored. The conceptual framework is provided for the proposed model along with a matchmaking algorithm based on IoT devices virtualization. The simulation results elaborate the increased complexity of processing time with respect to the increasing pool of available services. The average processing time varies as the number of conditions are multiplied. Query size and complexity increases with additional number of filters and conditions which results in the reduction of the number of matching services. Moreover, upon decreasing the radius of geographic search area, the number of candidate services decreases for service matching algorithm. This is based on the assumption that IoT devices and services are evenly distributed in a given geographic area. Similarly, the remaining energy of IoT devices is also assumed to be uniformly distributed and, therefore, if we are interested in IoT devices or services with more residual energy, then a limited number of IoT devices or services will fulfill this criterion.

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Section: Service Registrymentioning

confidence: 99%

Virtualization Based Efficient Service Matching and Discovery in Internet of Things

et al. 2020

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“…Some attempts to apply SOA at Device-Level in Industrial Automation were proposed in the context of the European project SIRENA [28] by the implementation of web services (e.g., DPWS) [10,29]. In this case, a decentralized discovery approach based on WS-Discovery (Web Services Dynamic Discovery) is used to find out the available devices by sending broadcast announcements over the Ethernet network [30,31]. An RTE network is then initialized to interconnect all discovered devices with the PLC.…”

Section: Auto-configuration In Industrial Environmentsmentioning

confidence: 99%

Automatic Configuration of OPC UA for Industrial Internet of Things Environments

Gutierrez-Guerrero

Holgado-Terriza

2019

Electronics

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Software technologies play an increasingly significant role in industrial environments, especially for the adoption of Industrial Internet of Things (IIoT). In this context, the application of mechanisms for the auto-configuration of industrial systems may be relevant for reducing human errors and costs in terms of time and money, improving the maintenance and the quality control. OPC UA (OLE for Process Control Unified Architecture) systems are usually integrated into an industrial system to provide a standard way for setting a secure and reliable data exchange between industrial devices of multiple vendors and software systems. In this paper, a novel mechanism for the auto-configuration of OPC UA systems is proposed from an initial setup of industrial devices interconnected to a basic Ethernet network. The auto-configuration of the OPC UA is self-managed over the TCP/IP protocol. This mechanism allows automating the configuration process of the OPC UA server automatically from the programmable logic controller (PLC) devices connected to a basic Ethernet network. Once the PLC devices are identified, they exchange information directly with OPC using a Modbus protocol over the same Ethernet network. To test the feasibility of this approach, a case study is prepared and evaluated.

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Matching and Discovery Algorithms in Internet of Things: Open Issues, Challenges, and Future Directions

Aljarbouh,

Zubov

2024

Lecture Notes in Networks and Systems

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A Survey on Service Discovery Mechanism

Cited by 6 publications

References 17 publications

Virtualization Based Efficient Service Matching and Discovery in Internet of Things

Virtualization Based Efficient Service Matching and Discovery in Internet of Things

Automatic Configuration of OPC UA for Industrial Internet of Things Environments

Matching and Discovery Algorithms in Internet of Things: Open Issues, Challenges, and Future Directions

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