Deep learning solution for central-node integration challenge in clustered routing protocols during fire emergencies Article Swipe
Ola Khudhair Abbas
,
Fairuz Abdullah
,
Nurul Asyikin Mohamed Radzi
,
Aymen Dawood Salman
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s13638-025-02538-w
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s13638-025-02538-w
Many clustered routing protocols integrate mediator nodes within the network structure, such as relays, gateways, and forwarders. These nodes collect and aggregate data from the clusters and then submit the data to the Base Station (BS), facilitating communication between clusters. It eliminates the redundancy in data and minimizes the delay by reducing the transmission distance to the BS. However, integrating such nodes poses significant challenges in dynamic environments, such as fire incidents. Based on their location and responsibility, their loss often leads to increased packet loss and suboptimal routing decisions under changing network conditions. This paper proposes a solution to this challenge by introducing a novel adaptive routing protocol. A hybrid deep learning model is employed to predict the loss of such nodes and select a suitable alternative node, combining dual-layer convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTMs). The proposed protocol was validated against the non-adaptive approach during three scenarios and two fire directions. Key evaluation metrics used are the throughput, packet delivery ratio (PDR), packet loss ratio (PLR), delay optimization, and packet prioritization ratio. Simulation results demonstrate the effectiveness of the proposed approach in enhancing the central node’s performance during fire incidents and ensuring reliable delivery of monitored data to its destination. For the first fire scenario, the proposed approach records 8.08% PLR and 91.91% PDR, while for the second fire scenario, it records 8.27% PLR and 91.27% PDR. This study provides a robust framework for central node-based and clustered protocols, ensuring reliable communication in critical scenarios.
Related Topics
Concepts
No concepts available.
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s13638-025-02538-w
- https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdf
- OA Status
- gold
- References
- 43
- OpenAlex ID
- https://openalex.org/W4417162490
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4417162490Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1186/s13638-025-02538-wDigital Object Identifier
- Title
-
Deep learning solution for central-node integration challenge in clustered routing protocols during fire emergenciesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-09Full publication date if available
- Authors
-
Ola Khudhair Abbas, Fairuz Abdullah, Nurul Asyikin Mohamed Radzi, Aymen Dawood SalmanList of authors in order
- Landing page
-
https://doi.org/10.1186/s13638-025-02538-wPublisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdfDirect OA link when available
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
43Number of works referenced by this work
Full payload
| id | https://openalex.org/W4417162490 |
|---|---|
| doi | https://doi.org/10.1186/s13638-025-02538-w |
| ids.doi | https://doi.org/10.1186/s13638-025-02538-w |
| ids.openalex | https://openalex.org/W4417162490 |
| fwci | |
| type | article |
| title | Deep learning solution for central-node integration challenge in clustered routing protocols during fire emergencies |
| biblio.issue | 1 |
| biblio.volume | 2025 |
| biblio.last_page | |
| biblio.first_page | |
| is_xpac | False |
| apc_list.value | 1140 |
| apc_list.currency | GBP |
| apc_list.value_usd | 1398 |
| apc_paid.value | 1140 |
| apc_paid.currency | GBP |
| apc_paid.value_usd | 1398 |
| language | en |
| locations[0].id | doi:10.1186/s13638-025-02538-w |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S82675988 |
| locations[0].source.issn | 1687-1472, 1687-1499 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1687-1472 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | EURASIP Journal on Wireless Communications and Networking |
| locations[0].source.host_organization | https://openalex.org/P4310319965 |
| locations[0].source.host_organization_name | Springer Nature |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319965 |
| locations[0].source.host_organization_lineage_names | Springer Nature |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | EURASIP Journal on Wireless Communications and Networking |
| locations[0].landing_page_url | https://doi.org/10.1186/s13638-025-02538-w |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5106528707 |
| authorships[0].author.orcid | https://orcid.org/0009-0001-7850-4212 |
| authorships[0].author.display_name | Ola Khudhair Abbas |
| authorships[0].countries | MY |
| authorships[0].affiliations[0].raw_affiliation_string | General Directorate of Education in Misan Governorate, Iraqi Ministry of Education, Amarah, Misan, 10045, Iraq |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I79156528 |
| authorships[0].affiliations[1].raw_affiliation_string | Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[0].institutions[0].id | https://openalex.org/I79156528 |
| authorships[0].institutions[0].ror | https://ror.org/03kxdn807 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I79156528, https://openalex.org/I874769580 |
| authorships[0].institutions[0].country_code | MY |
| authorships[0].institutions[0].display_name | Universiti Tenaga Nasional |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ola Khudhair Abbas |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | General Directorate of Education in Misan Governorate, Iraqi Ministry of Education, Amarah, Misan, 10045, Iraq, Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[1].author.id | https://openalex.org/A5036405930 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1030-7554 |
| authorships[1].author.display_name | Fairuz Abdullah |
| authorships[1].countries | MY |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I79156528 |
| authorships[1].affiliations[0].raw_affiliation_string | Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[1].institutions[0].id | https://openalex.org/I79156528 |
| authorships[1].institutions[0].ror | https://ror.org/03kxdn807 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I79156528, https://openalex.org/I874769580 |
| authorships[1].institutions[0].country_code | MY |
| authorships[1].institutions[0].display_name | Universiti Tenaga Nasional |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Fairuz Abdullah |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[2].author.id | https://openalex.org/A5068466678 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0481-7686 |
| authorships[2].author.display_name | Nurul Asyikin Mohamed Radzi |
| authorships[2].countries | MY |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I79156528 |
| authorships[2].affiliations[0].raw_affiliation_string | Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[2].institutions[0].id | https://openalex.org/I79156528 |
| authorships[2].institutions[0].ror | https://ror.org/03kxdn807 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I79156528, https://openalex.org/I874769580 |
| authorships[2].institutions[0].country_code | MY |
| authorships[2].institutions[0].display_name | Universiti Tenaga Nasional |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Nurul Asyikin Mohamed Radzi |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Institute of Power Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia |
| authorships[3].author.id | https://openalex.org/A5051940127 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-1435-725X |
| authorships[3].author.display_name | Aymen Dawood Salman |
| authorships[3].countries | IQ |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I171256487 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Computer Engineering, University of Technology–Iraq, Baghdad, 10066, Iraq |
| authorships[3].institutions[0].id | https://openalex.org/I171256487 |
| authorships[3].institutions[0].ror | https://ror.org/01w1ehb86 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I171256487 |
| authorships[3].institutions[0].country_code | IQ |
| authorships[3].institutions[0].display_name | University of Technology - Iraq |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Aymen Dawood Salman |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Computer Engineering, University of Technology–Iraq, Baghdad, 10066, Iraq |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-12-09T00:00:00 |
| display_name | Deep learning solution for central-node integration challenge in clustered routing protocols during fire emergencies |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-12-11T00:21:10.989143 |
| primary_topic | |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1186/s13638-025-02538-w |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S82675988 |
| best_oa_location.source.issn | 1687-1472, 1687-1499 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1687-1472 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | EURASIP Journal on Wireless Communications and Networking |
| best_oa_location.source.host_organization | https://openalex.org/P4310319965 |
| best_oa_location.source.host_organization_name | Springer Nature |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319965 |
| best_oa_location.source.host_organization_lineage_names | Springer Nature |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | EURASIP Journal on Wireless Communications and Networking |
| best_oa_location.landing_page_url | https://doi.org/10.1186/s13638-025-02538-w |
| primary_location.id | doi:10.1186/s13638-025-02538-w |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S82675988 |
| primary_location.source.issn | 1687-1472, 1687-1499 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1687-1472 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | EURASIP Journal on Wireless Communications and Networking |
| primary_location.source.host_organization | https://openalex.org/P4310319965 |
| primary_location.source.host_organization_name | Springer Nature |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319965 |
| primary_location.source.host_organization_lineage_names | Springer Nature |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://link.springer.com/content/pdf/10.1186/s13638-025-02538-w.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | EURASIP Journal on Wireless Communications and Networking |
| primary_location.landing_page_url | https://doi.org/10.1186/s13638-025-02538-w |
| publication_date | 2025-12-09 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W2943986432, https://openalex.org/W3119709224, https://openalex.org/W4401387964, https://openalex.org/W4396922990, https://openalex.org/W4401607384, https://openalex.org/W4378982370, https://openalex.org/W2765878715, https://openalex.org/W4393965210, https://openalex.org/W4384007720, https://openalex.org/W2783214249, https://openalex.org/W4205960680, https://openalex.org/W4220766727, https://openalex.org/W4221072072, https://openalex.org/W4376275269, https://openalex.org/W4397008692, https://openalex.org/W4387647315, https://openalex.org/W4395070071, https://openalex.org/W4400884057, https://openalex.org/W4401482513, https://openalex.org/W2909996676, https://openalex.org/W3140599371, https://openalex.org/W2791191836, https://openalex.org/W3002968620, https://openalex.org/W3215246071, https://openalex.org/W4309531324, https://openalex.org/W3190872122, https://openalex.org/W4379468263, https://openalex.org/W4402758955, https://openalex.org/W4393108925, https://openalex.org/W4396620648, https://openalex.org/W4402069144, https://openalex.org/W4390224875, https://openalex.org/W4377085252, https://openalex.org/W4389428576, https://openalex.org/W4394958475, https://openalex.org/W3135878613, https://openalex.org/W4313419997, https://openalex.org/W4394952835, https://openalex.org/W4296526515, https://openalex.org/W4385190584, https://openalex.org/W3205916482, https://openalex.org/W4392386117, https://openalex.org/W3126814579 |
| referenced_works_count | 43 |
| abstract_inverted_index.A | 110 |
| abstract_inverted_index.a | 98, 105, 126, 237 |
| abstract_inverted_index.It | 41 |
| abstract_inverted_index.as | 13, 70 |
| abstract_inverted_index.by | 51, 103 |
| abstract_inverted_index.in | 45, 66, 188, 249 |
| abstract_inverted_index.is | 115 |
| abstract_inverted_index.it | 227 |
| abstract_inverted_index.of | 121, 184, 201 |
| abstract_inverted_index.on | 74 |
| abstract_inverted_index.to | 32, 56, 83, 100, 117, 204 |
| abstract_inverted_index.BS. | 58 |
| abstract_inverted_index.For | 207 |
| abstract_inverted_index.Key | 158 |
| abstract_inverted_index.PLR | 217, 230 |
| abstract_inverted_index.The | 142 |
| abstract_inverted_index.and | 16, 21, 27, 47, 77, 87, 124, 136, 154, 175, 197, 218, 231, 243 |
| abstract_inverted_index.are | 162 |
| abstract_inverted_index.for | 222, 240 |
| abstract_inverted_index.its | 205 |
| abstract_inverted_index.the | 9, 25, 30, 33, 43, 49, 53, 57, 119, 148, 163, 182, 185, 190, 208, 212, 223 |
| abstract_inverted_index.two | 155 |
| abstract_inverted_index.was | 145 |
| abstract_inverted_index.Base | 34 |
| abstract_inverted_index.Many | 1 |
| abstract_inverted_index.PDR, | 220 |
| abstract_inverted_index.PDR. | 233 |
| abstract_inverted_index.This | 95, 234 |
| abstract_inverted_index.data | 23, 31, 46, 203 |
| abstract_inverted_index.deep | 112 |
| abstract_inverted_index.fire | 71, 156, 195, 210, 225 |
| abstract_inverted_index.from | 24 |
| abstract_inverted_index.long | 138 |
| abstract_inverted_index.loss | 80, 86, 120, 170 |
| abstract_inverted_index.such | 12, 61, 69, 122 |
| abstract_inverted_index.then | 28 |
| abstract_inverted_index.this | 101 |
| abstract_inverted_index.used | 161 |
| abstract_inverted_index.(BS), | 36 |
| abstract_inverted_index.8.08% | 216 |
| abstract_inverted_index.8.27% | 229 |
| abstract_inverted_index.Based | 73 |
| abstract_inverted_index.These | 18 |
| abstract_inverted_index.delay | 50, 173 |
| abstract_inverted_index.first | 209 |
| abstract_inverted_index.leads | 82 |
| abstract_inverted_index.model | 114 |
| abstract_inverted_index.node, | 129 |
| abstract_inverted_index.nodes | 7, 19, 62, 123 |
| abstract_inverted_index.novel | 106 |
| abstract_inverted_index.often | 81 |
| abstract_inverted_index.paper | 96 |
| abstract_inverted_index.poses | 63 |
| abstract_inverted_index.ratio | 167, 171 |
| abstract_inverted_index.study | 235 |
| abstract_inverted_index.their | 75, 79 |
| abstract_inverted_index.three | 152 |
| abstract_inverted_index.under | 91 |
| abstract_inverted_index.while | 221 |
| abstract_inverted_index.(CNNs) | 135 |
| abstract_inverted_index.(PDR), | 168 |
| abstract_inverted_index.(PLR), | 172 |
| abstract_inverted_index.91.27% | 232 |
| abstract_inverted_index.91.91% | 219 |
| abstract_inverted_index.during | 151, 194 |
| abstract_inverted_index.hybrid | 111 |
| abstract_inverted_index.memory | 140 |
| abstract_inverted_index.neural | 133 |
| abstract_inverted_index.packet | 85, 165, 169, 176 |
| abstract_inverted_index.ratio. | 178 |
| abstract_inverted_index.robust | 238 |
| abstract_inverted_index.second | 224 |
| abstract_inverted_index.select | 125 |
| abstract_inverted_index.submit | 29 |
| abstract_inverted_index.within | 8 |
| abstract_inverted_index.Station | 35 |
| abstract_inverted_index.against | 147 |
| abstract_inverted_index.between | 39 |
| abstract_inverted_index.central | 191, 241 |
| abstract_inverted_index.collect | 20 |
| abstract_inverted_index.dynamic | 67 |
| abstract_inverted_index.metrics | 160 |
| abstract_inverted_index.network | 10, 93 |
| abstract_inverted_index.predict | 118 |
| abstract_inverted_index.records | 215, 228 |
| abstract_inverted_index.relays, | 14 |
| abstract_inverted_index.results | 180 |
| abstract_inverted_index.routing | 3, 89, 108 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 59 |
| abstract_inverted_index.adaptive | 107 |
| abstract_inverted_index.approach | 150, 187, 214 |
| abstract_inverted_index.changing | 92 |
| abstract_inverted_index.clusters | 26 |
| abstract_inverted_index.critical | 250 |
| abstract_inverted_index.delivery | 166, 200 |
| abstract_inverted_index.distance | 55 |
| abstract_inverted_index.employed | 116 |
| abstract_inverted_index.ensuring | 198, 246 |
| abstract_inverted_index.learning | 113 |
| abstract_inverted_index.location | 76 |
| abstract_inverted_index.mediator | 6 |
| abstract_inverted_index.networks | 134 |
| abstract_inverted_index.node’s | 192 |
| abstract_inverted_index.proposed | 143, 186, 213 |
| abstract_inverted_index.proposes | 97 |
| abstract_inverted_index.protocol | 144 |
| abstract_inverted_index.provides | 236 |
| abstract_inverted_index.reducing | 52 |
| abstract_inverted_index.reliable | 199, 247 |
| abstract_inverted_index.solution | 99 |
| abstract_inverted_index.suitable | 127 |
| abstract_inverted_index.aggregate | 22 |
| abstract_inverted_index.challenge | 102 |
| abstract_inverted_index.clustered | 2, 244 |
| abstract_inverted_index.clusters. | 40 |
| abstract_inverted_index.combining | 130 |
| abstract_inverted_index.decisions | 90 |
| abstract_inverted_index.enhancing | 189 |
| abstract_inverted_index.framework | 239 |
| abstract_inverted_index.gateways, | 15 |
| abstract_inverted_index.incidents | 196 |
| abstract_inverted_index.increased | 84 |
| abstract_inverted_index.integrate | 5 |
| abstract_inverted_index.minimizes | 48 |
| abstract_inverted_index.monitored | 202 |
| abstract_inverted_index.protocol. | 109 |
| abstract_inverted_index.protocols | 4 |
| abstract_inverted_index.scenario, | 211, 226 |
| abstract_inverted_index.scenarios | 153 |
| abstract_inverted_index.validated | 146 |
| abstract_inverted_index.(BiLSTMs). | 141 |
| abstract_inverted_index.Simulation | 179 |
| abstract_inverted_index.challenges | 65 |
| abstract_inverted_index.dual-layer | 131 |
| abstract_inverted_index.eliminates | 42 |
| abstract_inverted_index.evaluation | 159 |
| abstract_inverted_index.incidents. | 72 |
| abstract_inverted_index.node-based | 242 |
| abstract_inverted_index.protocols, | 245 |
| abstract_inverted_index.redundancy | 44 |
| abstract_inverted_index.scenarios. | 251 |
| abstract_inverted_index.short-term | 139 |
| abstract_inverted_index.structure, | 11 |
| abstract_inverted_index.suboptimal | 88 |
| abstract_inverted_index.alternative | 128 |
| abstract_inverted_index.conditions. | 94 |
| abstract_inverted_index.demonstrate | 181 |
| abstract_inverted_index.directions. | 157 |
| abstract_inverted_index.forwarders. | 17 |
| abstract_inverted_index.integrating | 60 |
| abstract_inverted_index.introducing | 104 |
| abstract_inverted_index.performance | 193 |
| abstract_inverted_index.significant | 64 |
| abstract_inverted_index.throughput, | 164 |
| abstract_inverted_index.destination. | 206 |
| abstract_inverted_index.facilitating | 37 |
| abstract_inverted_index.non-adaptive | 149 |
| abstract_inverted_index.transmission | 54 |
| abstract_inverted_index.bidirectional | 137 |
| abstract_inverted_index.communication | 38, 248 |
| abstract_inverted_index.convolutional | 132 |
| abstract_inverted_index.effectiveness | 183 |
| abstract_inverted_index.environments, | 68 |
| abstract_inverted_index.optimization, | 174 |
| abstract_inverted_index.prioritization | 177 |
| abstract_inverted_index.responsibility, | 78 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5106528707 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I79156528 |
| citation_normalized_percentile |