A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network Article Swipe
Sami Abduljabbar Rashid
,
Mustafa Maad Hamdi
,
Lukman Audah
,
Mohammed Ahmed Jubair
,
Mustafa Hamid Hassan
,
Mohammed Salah Abood
,
Salama A. Mostafa
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.11591/ijai.v12.i2.pp667-677
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.11591/ijai.v12.i2.pp667-677
Vehicular ad-hoc network (VANET) is dynamic and it works on various noteworthy applications in intelligent transportation systems (ITS). In general, routing overhead is more in the VANETs due to their properties. Hence, need to handle this issue to improve the performance of the VANETs. Also due to its dynamic nature collision occurs. Up till now, we have had immense complexity in developing the multi-constrained network with high quality of forwarding (QoF). To solve the difficulties especially to control the congestion this paper introduces an enhanced genetic algorithmbased lion optimization for QoF-based routing protocol (EGA-LOQRP) in the VANET network. Lion optimization routing protocol (LORP) is an optimization-based routing protocol that can able to control the network with a huge number of vehicles. An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. This will result in low packet loss, delay, and energy consumption of the network. The exhaustive simulation tests demonstrate that the EGA-LOQRP routing protocol improves performance effectively in the face of congestion and QoS assaults compared to the previous routing protocols like Ad hoc on-demand distance vector (AODV), ant colony optimization-AODV (ACO-AODV) and traffic aware segmentAODV (TAS-AODV).
Related Topics
Concepts
Computer science
Computer network
Ad hoc On-Demand Distance Vector Routing
Routing protocol
Dynamic Source Routing
Network congestion
Vehicular ad hoc network
Destination-Sequenced Distance Vector routing
Wireless ad hoc network
Distributed computing
Routing (electronic design automation)
Network packet
Wireless
Telecommunications
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.11591/ijai.v12.i2.pp667-677
- https://ijai.iaescore.com/index.php/IJAI/article/download/21610/13629
- OA Status
- diamond
- Cited By
- 5
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4311410609
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4311410609Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.11591/ijai.v12.i2.pp667-677Digital Object Identifier
- Title
-
A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc networkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-12Full publication date if available
- Authors
-
Sami Abduljabbar Rashid, Mustafa Maad Hamdi, Lukman Audah, Mohammed Ahmed Jubair, Mustafa Hamid Hassan, Mohammed Salah Abood, Salama A. MostafaList of authors in order
- Landing page
-
https://doi.org/10.11591/ijai.v12.i2.pp667-677Publisher landing page
- PDF URL
-
https://ijai.iaescore.com/index.php/IJAI/article/download/21610/13629Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ijai.iaescore.com/index.php/IJAI/article/download/21610/13629Direct OA link when available
- Concepts
-
Computer science, Computer network, Ad hoc On-Demand Distance Vector Routing, Routing protocol, Dynamic Source Routing, Network congestion, Vehicular ad hoc network, Destination-Sequenced Distance Vector routing, Wireless ad hoc network, Distributed computing, Routing (electronic design automation), Network packet, Wireless, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1, 2023: 3Per-year citation counts (last 5 years)
- References (count)
-
25Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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