Using DDS Based on Unified Data Model to Improve Interoperability of Smart Grids

Alaerjan, Alaa; Kim, Dae-Kyoo; Hua, Ming; Malik, Khalid Mahmood

doi:10.1109/sege.2018.8499513

Cited by 6 publications

(5 citation statements)

References 10 publications

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“…This is because SG consists of multiple power domains (i.e., operation, generation, distribution, and customer) each of which uses its own connectivity protocols [21]. Additionally, the diversity of data models and standards creates further data interoperability challenges in SG [22]. All these challenges result in deteriorating the connectivity of different power domains in SG.…”

Section: B Iot Context Applicationmentioning

confidence: 99%

Model-Driven Interoperability Layer for Normalized Connectivity Across Smart Grid Domains

Alaerjan

2021

IEEE Access

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The connectivity of heterogeneous components is the key factor behind the notion of the Internet of Things (IoT). Typically, IoT applications involve several communication protocols that are developed based on heterogeneous data models. This has complicated the connectivity within IoT applications. It has also caused significant interoperability issues. Therefore, in this paper we propose a novel connectivity layer which we refer to as the Distributed Data Interoperability Layer (DDIL). DDIL aims at addressing the connectivity issues that arise due to the heterogeneity of data models. In the approach, we construct DDIL into different software components. We then describe these components as a set of configurable features to allow DDIL to be tailored based on the requirements of each application. DDIL has the capabilities to address both syntactic and semantic interoperability. The featureoriented design of DDIL provides required flexibility which is a key concern in several IoT applications. Additionally, DDIL supports backward compatibility. It also allows utilizing preexisting technologies which supports rapid development of applications. We implemented the approach in a simulated smart grid environment. The results prove that DDIL has the capabilities to support the connectivity of different applications even if they are developed based on different protocols and heterogeneous data models.

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Section: B Iot Context Applicationmentioning

confidence: 99%

Model-Driven Interoperability Layer for Normalized Connectivity Across Smart Grid Domains

Alaerjan

2021

IEEE Access

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“…AsyncAPI descriptions are expected to be both human and machine readable. To achieve this goal, files defining a message-driven API are represented as JSON objects and conform to the JSON standards 2 . Such files allow describing, among other things, the message brokers of an architecture, the topics of interest, or the different formats of the messages associated with each of the topics.…”

Section: Motivationmentioning

confidence: 99%

“…Beyond AsyncAPI, asynchronous communication can also be defined with Data Distribution Service (DDS) [37], which is a data-centric publish/subscribe (DCPS) model for distributed application communication. While both DDS and AsyncAPI provide a specific language for data definition-the so-called Interface Definition Language (IDL) [39] in the case of the former, and JSON Schema in the case of the latter-they differ in different aspects: (i) DDS is oriented to the data itself and not the messages [2]; (ii) DDS is technology agnostic, and as a consequence, does not consider architectural elements such as the different protocols, servers and listening ports-to name a few-involved; and (iii) DDS has a more mature ecosystem. However, although DDS is technology agnostic, its implementations are more niche-focused 26 : most of the solutions focus on supporting C and C++ and support to other languages are provided via bridges to execute native code in compiled libraries.…”

Section: Model-based Approaches For Message-driven Architecturesmentioning

confidence: 99%

Model-driven development of asynchronous message-driven architectures with AsyncAPI

et al. 2021

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In the Internet-of-Things (IoT) vision, everyday objects evolve into cyber-physical systems. The massive use and deployment of these systems has given place to the Industry 4.0 or Industrial IoT (IIoT). Due to its scalability requirements, IIoT architectures are typically distributed and asynchronous. In this scenario, one of the most widely used paradigms is publish/subscribe, where messages are sent and received based on a set of categories or topics. However, these architectures face interoperability challenges. Consistency in message categories and structure is the key to avoid potential losses of information. Ensuring this consistency requires complex data processing logic both on the publisher and the subscriber sides. In this paper, we present our proposal relying on AsyncAPI to automate the design and implementation of these asynchronous architectures using model-driven techniques for the generation of (part of) message-driven infrastructures. Our proposal offers two different ways of designing the architectures: either graphically, by modeling and annotating the messages that are sent among the different IoT devices, or textually, by implementing an editor compliant with the AsyncAPI specification. We have evaluated our proposal by conducting a set of experiments with 25 subjects with different expertise and background. The experiments show that one-third of the subjects were able to design and implement a working architecture in less than an hour without previous knowledge of our proposal, and an additional one-third estimated that they would only need less than two hours in total.

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“…Alaerjan et al [84] designed a unified model between the two standards using mapping and extension methods. Based on the model, the authors demonstrated an architecture for data exchange using a network communication middleware called data distribution service (DDS).…”

Section: Mapping and Extensionmentioning

confidence: 99%

A Comprehensive Review of Practical Issues for Interoperability Using the Common Information Model in Smart Grids

et al. 2020

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Smart grids with interoperability improve grid reliability by collecting system information and transferring it to an energy management system and associated applications through a seamless end-to-end connection. To achieve interoperability, it is required to exchange the semantic information within the different domains. The international electrotechnical commission has established the Common Information Model (CIM) tool, which is a standard application programming interface for the exchange of semantic information in power systems. CIM provides a robust framework for accurate data sharing, merging, and transformation into reusable information. However, as CIM provides a basic framework for information exchange, various practical issues arise in establishing an energy management system capable of exchanging information using CIM. This paper aims to offer a comprehensive understanding by summarizing and categorizing the research on the practical use of CIM for interoperability in smart grids. Many papers are analyzed and the issues are classified into CIM extension, harmonization, and validation to address the issues that arise when establishing an integrated information exchange system.

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Using DDS Based on Unified Data Model to Improve Interoperability of Smart Grids

Cited by 6 publications

References 10 publications

Model-Driven Interoperability Layer for Normalized Connectivity Across Smart Grid Domains

Model-Driven Interoperability Layer for Normalized Connectivity Across Smart Grid Domains

Model-driven development of asynchronous message-driven architectures with AsyncAPI

A Comprehensive Review of Practical Issues for Interoperability Using the Common Information Model in Smart Grids

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