A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks
The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide us...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2012-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/6/7548 |
| _version_ | 1818001470826479616 |
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| author | Nenad Kojić Irini Reljin Branimir Reljin |
| author_facet | Nenad Kojić Irini Reljin Branimir Reljin |
| author_sort | Nenad Kojić |
| collection | DOAJ |
| description | The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—<em>i.e.</em>, neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance. |
| first_indexed | 2024-04-14T03:34:39Z |
| format | Article |
| id | doaj.art-5a1cdb4073d34557bb29c619787934fe |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:34:39Z |
| publishDate | 2012-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5a1cdb4073d34557bb29c619787934fe2022-12-22T02:14:50ZengMDPI AGSensors1424-82202012-06-011267548757510.3390/s120607548A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh NetworksNenad KojićIrini ReljinBranimir ReljinThe networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—<em>i.e.</em>, neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.http://www.mdpi.com/1424-8220/12/6/7548artificial intelligenceHopfield neural networkMANETmulticriteria optimizationrouting protocolwireless mesh network |
| spellingShingle | Nenad Kojić Irini Reljin Branimir Reljin A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks Sensors artificial intelligence Hopfield neural network MANET multicriteria optimization routing protocol wireless mesh network |
| title | A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks |
| title_full | A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks |
| title_fullStr | A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks |
| title_full_unstemmed | A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks |
| title_short | A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks |
| title_sort | neural networks based hybrid routing protocol for wireless mesh networks |
| topic | artificial intelligence Hopfield neural network MANET multicriteria optimization routing protocol wireless mesh network |
| url | http://www.mdpi.com/1424-8220/12/6/7548 |
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