Name
Abstract | ||
|---|---|---|
The unprecedented growth of Internet of Things (IoT) underpinned by machine to machine communication, analytics and actuation is spearheading the development of autonomic IoT applications in areas such as Smart Cities. Such autonomic IoT applications have minimal human involvement in the decision making and actuation process. A key challenge in developing such autonomic IoT applications is uncertainty in the data produced by the IoT devices with data freshness being a critical aspect. In this paper, we address this challenge by introducing Age of Data (AoD), a metric to quantify the freshness of the data produced by IoT devices. We analyse the impact of AoD on IoT applications and propose a model for computing AoD that can be used by IoT applications in the decision making process. We validate the proposed model via experimental evaluations using real-world data obtained from parking sensors. Our analysis found that in real-world scenarios, 21.4% of sensors provide data that is outdated by several hours. We show that incorporating AoD in the application logic leads to improved application decision making. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/CCNC49033.2022.9700640 | 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) |
DocType | ISSN | ISBN |
Conference | 2331-9852 | 978-1-6654-3162-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kaneez Fizza | 1 | 0 | 0.34 |
| Prem Prakash Jayaraman | 2 | 2 | 3.14 |
| Abhik Banerjee | 3 | 0 | 1.01 |
| Dimitrios Georgakopoulos | 4 | 2554 | 580.54 |
| Rajiv Ranjan | 5 | 0 | 0.34 |