2020
DOI: 10.3390/electronics9040564
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Sustainable IoT Sensing Applications Development through GraphQL-Based Abstraction Layer

Abstract: Internet of Things (IoT) networks are mostly comprised of power-constrained devices, therefore the most important consideration in designing IoT applications, based on sensor networks is energy efficiency. Minor improvement in energy conservation methods can lead to a significant increase in the lifetime of IoT devices and overall network. To achieve efficient utilisation of energy, different solutions are proposed such as duty cycling optimization, design changes at the MAC layer, etc. In this paper, we propo… Show more

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Cited by 11 publications
(5 citation statements)
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“…The frontend is tasked with managing the user interface and issuing GraphQL queries to the server, while the backend addresses GraphQL queries, performs required database operations, and delivers the requested data back to the client. This improves application performance and scalability [37,38]. Furthermore, using GraphQL on both the client and server allows for consistent and unified data interaction, regardless of the data's origin.…”
Section: Application Layermentioning
confidence: 99%
“…The frontend is tasked with managing the user interface and issuing GraphQL queries to the server, while the backend addresses GraphQL queries, performs required database operations, and delivers the requested data back to the client. This improves application performance and scalability [37,38]. Furthermore, using GraphQL on both the client and server allows for consistent and unified data interaction, regardless of the data's origin.…”
Section: Application Layermentioning
confidence: 99%
“…Additionally, oneM2M requires an interworking proxy to connect with the legacy IoT products and technologies [26]. Other authors suggest using GraphQL to abstract device functionalities [27], or propose a data-driven agent-based abstraction layer, which aims to minimize the overhead of representing the information generated by devices and services [28].…”
Section: Related Workmentioning
confidence: 99%
“…Execution of comprehensible queries (using GraphQL [16]) autonomously from the source node to aggregate and access core data. GraphQL helped propose a scheme to query multiple resource data with a single reference request.…”
Section: Hazard and Operability (Hazop) Analysismentioning
confidence: 99%