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Smart city article details
| Title | Oqr-Sc: An Optimal Qos Aware Routing Technique For Smart Cities Using Iot Enabled Wireless Sensor Networks |
|---|---|
| ID_Doc | 40968 |
| Authors | Karunkuzhali D.; Meenakshi B.; Lingam K. |
| Year | 2022 |
| Published | Wireless Personal Communications, 125, 4 |
| DOI | http://dx.doi.org/10.1007/s11277-022-09725-8 |
| Abstract | Internet of things (IoT) makes a machines optimization in everyday which processing the data by very intelligently and make communication more effectively and efficiently. In smart city environments, the data collection and communication play an important role in defining quality. Since the research period, it has been recommending a new data acquisition and data communication software framework for IoT smart applications. For further improvements, we recommend an optimal QoS aware routing technique for smart cities using IoT enabled wireless sensor networks (OQR-SC). In data gathering phase, the proposed system introduce chaotic bird swarm optimization (CBSO) algorithm for IoT sensor cluster formation; the improved differential search (IDS) algorithm used to estimate the faith degree of each sensor node, the highest trust node act as cluster head (CH). In data transferring phase, first illustrates lightweight signcryption technique for data encryption between two IoT sensors. Then, we use optimal decision making (ODM) algorithm to compute the optimal path between source-destination in IoT platform. Finally, the proposed OQR-SC technique is implemented using network simulation (NS2) tool and analyzes the performance of proposed technique with existing state-of-art techniques. The result summarizes that average energy consumption of proposed OQR-SC technique is 12.39% lower than the existing techniques; the average network lifetime of proposed OQR-SC technique is 15.96% higher than the existing techniques; the average delay of proposed OQR-SC technique is 21.08% lower than the existing techniques; and the average throughput of proposed OQR-SC technique is 17.89% higher than the existing techniques. |
| Author Keywords | Chaotic bird swarm optimization; Improved differential search; Internet of things; Optimal decision making; Optimal QoS aware routing technique for smart cities |
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