Autor: |
Jeremy Lynn Reed, Ali Saman Tosun, Turgay Korkmaz |
Jazyk: |
angličtina |
Rok vydání: |
2024 |
Předmět: |
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Zdroj: |
IEEE Access, Vol 12, Pp 128085-128096 (2024) |
Druh dokumentu: |
article |
ISSN: |
2169-3536 |
DOI: |
10.1109/ACCESS.2024.3404468 |
Popis: |
IoT edge computing is a network design model that captures and processes data at the network edge. The results are forwarded to a cloud service or, if additional processing is needed, a middle tier. By processing data at the edge and middle tier, edge networks achieve better load-balancing and improve performance; however, traditional edge network deployments represent a rigid participation model. Edge networks require physical access to an IoT device and often lock the device to a single edge network. These constraints make it difficult to construct the ideal network, as they reject IoT devices deployed at the network edge but not owned by the network administrator. Our goal is to remove these limitations by creating a network protocol that supports broader participation of IoT devices, cryptographically secures network data, and improves network performance by increasing captured data at the network edge. The protocol is named Snap to symbolize the ease of self assembly. Our experimental research focuses on temperature stability and the cycle efficiency of an HVAC system by utilizing a Snap network to combine two existing edge networks and increase the number of temperature measurement points. The additional measurement points improved the efficiency of the HVAC cycle strategy by increasing the square footage of measured building space. The additional temperature capture points supported an adjustment to the HVAC cycle strategy which resulted in reducing the disparity between the requested and resulting temperatures. Snap networks support a broader range of IoT sensors leading to increased measurement density, sample rate frequency, and coverage of the network edge. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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