| Title |
Energy-Efficient Static Data Collector-based Scheme in Smart Cities |
| ID_Doc |
40602 |
| Authors |
Rajab, AD |
| Title |
Energy-Efficient Static Data Collector-based Scheme in Smart Cities |
| Year |
2022 |
| Published |
Cmc-Computers Materials & Continua, 72, 1 |
| DOI |
10.32604/cmc.2022.025736 |
| Abstract |
In the Internet of Things (IoT)-based smart city applications, employing the Data Collectors (DC) as the data brokers between the nodes and Base Station (BS) can be a promising solution to enhance the energy efficiency of energy-constrained IoT sensor nodes. There are several schemes that utilize mobile DCs to collect the data packets from sensor nodes. However, moving DCs along the hundreds of thousands of sensors sparsely distributed across a smart city is considered a design challenge in such schemes. Another concern lies in how these mobile DCs are being powered. Therefore, to overcome these limitations, we exploit multiple energy-limited Static Data Collectors (SDC) which are deployed at the locations optimized so that the energy consumption of both nodes and SDCs is minimized. Likewise, an Unmanned Aerial Vehicle (UAV)-enabled wireless power transfer is considered for sustaining the SDCs to avoid their energy depletion and data packet loss. The sustainable charging process operates periodically in each cycle so that the UAV flies from a charging station and after recharging the SDCs, it comes back to the station to be recharged. In this study, we formulate a problem to optimize the movement trajectory and charging time of UAV so that sustainable operation of SDCs during a cycle can be achieved. Unlike the prior studies, our proposed scheme determines the optimal trajectory and charging time at the beginning of each cycle which leads to increase accuracy in comparison with long-term optimization-based schemes. The outcomes of simulation experiments show that the proposed scheme achieves improved network performance in terms of data delivery ratio (12.5%); system throughput (6.6%); total energy consumption (59.19%); and network lifetime (58%) as compared to previous related works. |
| Author Keywords |
Smart city; wireless sensor network; power constraint; energy efficiency |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000767341900032 |
| WoS Category |
Computer Science, Information Systems; Materials Science, Multidisciplinary |
| Research Area |
Computer Science; Materials Science |
| PDF |
https://www.techscience.com/cmc/v72n1/46946/pdf
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