Sirait, Fadli and Jusoh, Mohd Taufik Bin and Dimyati, Kaharudin and Din, Muhammad Faiz Bin Md (2022) Determining optimal zone radius of zone routing protocol based on deep recurrent neural networks in the next generation wireless backhaul networks. International Journal on Advanced Science, Engineering and Information Technology, 12 (5). 2147 – 2155. ISSN 20885334, DOI https://doi.org/10.18517/ijaseit.12.5.15747.
Full text not available from this repository.Abstract
Next-generation wireless networks are becoming more popular and rely on reliable backhaul networks to work properly. Wireless backhaul networks also adopt various innovative technologies to improve capacity and provide more flexible deployments to meet networks' high-quality requirements. One of the essential innovations to maintain the wireless backhaul performance is combining the existing routing protocol technology and the deep learning concept. The concept of deep learning is gaining traction as a powerful way to add intelligence to wireless networks with complex topologies and radio environments. This is because conventional routing protocols do not learn from their previous experiences with various network anomalies. This paper proposed a predictive model of zone radius value using the deep recurrent neural network variant, namely the long short-term memory recurrent neural network (LSTMRNN) algorithm. Determination of zone radius value conducted by measuring the whole of nodes routing zone using various network performance as input parameters such as Routing Overhead, Energy Consumption, Throughput, and User Usage. Performance measurements such as mean square error (MSE), error distribution histogram, training state, regression, correlation, and time series response are gauged and compared for static and mobile node environments. Results showed that the proposed algorithm can accurately predict zone radius for both environments. However, the accuracy of the proposed algorithm is higher when implemented in a static node environment. © 2022, International Journal on Advanced Science, Engineering and Information Technology. All Rights Reserved.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Lstm-rnn; Routing protocol; Wmn; Zone radius; Zrp |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 29 Dec 2023 03:53 |
| Last Modified: | 29 Dec 2023 03:53 |
| URI: | http://eprints.um.edu.my/id/eprint/43861 |
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