AOMDV Intelligent Decision (AOMDV-ID) to Minimize Routing Delay for Diverse VANETs

Kushwaha, Uday Singh; Dixit, Mukesh Kumar; Singh, Akhilesh Kumar

doi:10.1109/iconat53423.2022.9726097

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…We hope to modify the horizontal axis titles of Figures 11,12, and 13 to align them with the horizontal axis titles of Figure 14 and provide more accurate descriptions to avoid misunderstandings among readers. As shown in Figure 11, the packet loss rate using the AOMDV routing algorithm is higher than that of the AMS routing algorithm, which is because the path selection based on link cost enables the selection of paths with fewer hop counts and good network quality, reducing the impact of bad path quality on data transmission and improving the success rate of packet delivery.…”

Section: Modification Request #2mentioning

confidence: 99%

“…In [ 11 ], to address the problem that traditional routing repair incurs huge routing overhead in terms of energy and delay, an efficient routing recovery protocol with the endocrine cooperative particle swarm optimization algorithm (ECPSOA) was proposed, which uses multi-swarm evolution equations to improve the rate of convergence and accuracy of the repair algorithm and reduces routing overhead and energy consumption. To overcome the problem of link instability in VANET, a hybrid multipath routing protocol with intelligent decisions is proposed, which can find routes quickly and uses intermediate nodes for failure maintenance, thus reducing the average routing latency and improving reliability [ 12 ]. Reference [ 13 ] proposes a method based on node residual energy and link stability, which modifies the original AODV routing protocol and adds header information on node residual energy and stability to the RREQ routing request message, enabling the selection of nodes with high stability and sufficient residual energy during the routing discovery process.…”

Section: Introductionmentioning

confidence: 99%

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A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks

Suo

Liu

et al. 2023

Sensors

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With the advancement of urban rail transit towards intelligence, the demand for urban rail transit communication has increased significantly, but the traditional urban rail transit vehicle–ground communication system has been unable to meet the future vehicle–ground communication requirements. To improve the performance of vehicle–ground communication, the paper proposes a reliable low-latency multipath routing (RLLMR) algorithm for urban rail transit ad hoc networks. First, RLLMR combines the characteristics of urban rail transit ad hoc networks and uses node location information to configure a proactive multipath to reduce route discovery delay. Second, the number of transmission paths is adaptively adjusted according to the quality of service (QoS) requirements for vehicle–ground communication, and then the optimal path is selected based on the link cost function to improve transmission quality. Third, in order to enhance the reliability of communication, a routing maintenance scheme has been added, and the static node-based local repair scheme is used in routing maintenance to reduce the maintenance cost and time. The simulation results show that compared with traditional AODV and AOMDV protocols, the proposed RLLMR algorithm has good performance in improving latency and is slightly inferior to the AOMDV protocol in improving reliability. However, overall, the throughput of the RLLMR algorithm is better than that of the AOMDV.

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Section: Modification Request #2mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks

Suo

Liu

et al. 2023

Sensors

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show abstract

“…To conquer this dilemma, Ref. [25] proposes an AOMDV intelligent decision protocol (AOMDV-ID). AOMDV-ID acts as hybrid protocol (proactive and reactive).…”

Section: Related Workmentioning

confidence: 99%

“…AOMDV performs well, but it does not have intelligent decision capabilities to select immediate routes by their source without discovering new routes or selecting alternate routes via intermediate nodes during failure, which diminishes performance and enhances end-to-end delay. To conquer this dilemma, reference [25] proposes an AOMDV intelligent decision protocol (AOMDV-ID). AOMDV-ID acts as hybrid protocol (proactive and reactive).…”

Section: The Network Modelmentioning

confidence: 99%

A Dynamic Addressing Hybrid Routing Mechanism Based on Static Configuration in Urban Rail Transit Ad Hoc Network

Han,

Liu,

Guo

et al. 2023

Electronics

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With the rapid development of urban rail transit, the traditional urban rail wireless network based on fixed infrastructure is not in a position to meet the increasingly complex communication demand. At the same time, Ad Hoc network, as a special wireless mobile network, is developing rapidly. Applying this self-organized networking architecture to the urban rail vehicle–ground communication network can overcome the problems existing in the traditional urban rail communication system. The routing protocols that can achieve low delay and highly reliable data transmission are important in the urban rail transit scenario. Therefore, combined with the wireless Ad Hoc network and the characteristics of the urban rail transit scenario, this paper proposes a dynamic addressing hybrid routing mechanism based on static configuration. Using an improved AODV routing discovery algorithm and then writing the routing table into the router in advance for static configuration not only reduces network overhead but also prolongs the network’s lifetime. It also saves the delay of routing discovery. Then, the cluster head node dynamically monitors the link status, dynamically finds the path when the link needs to be replaced, and selects different update paths according to different types of communication services. Finally, each algorithm’s network performance parameters, like the routing discovery overhead, residual link lifetime, packet delivery rate, throughput, and end-to-end delay, are analyzed and compared.

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“…Because the ratio of the number of control messages RREQ, RREP, and RERR is compressed, the control overhead of the protocol is also compressed. With intelligent decision, the source node does not care about minimum hop distance route discovery and route rediscovery on failure, reducing end-to-end delay [21].…”

Section: E) Aomdv Protocol With Intelligent Decision Making (Aomdv-id)mentioning

confidence: 99%

Intelligent Decision Based Route Selection and Maintenance Approach Using AOMDV in VANET

Kushwaha¹,

Jain²

2022

IJRASET

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Vehicle Ad Hoc Network (VANET) is a dynamic network with a variety of applications in intelligent transport systems. There are several routing protocols for establishing paths between sending and receiving nodes. AODV is a reactive routing protocol that broadcasts a route request to all adjacent nodes, which forward the request to their neighbors. This process helps select the path from sender to receiver. The AODV protocol is the best routing protocol when you have a large number of communicating nodes. In this study, AODV and Ant Colony Optimization (ACO) techniques are applied to transfer data. Ant colony optimization algorithm is applied considering the initial coordinates of each node. Paths established using reactive routing protocols are likely to congest the network and also consume large amounts of network bandwidth. This research is based on using a multicast approach to establish a path from source to destination to reduce the potential for network congestion. It generates the shortest route and achieves higher throughput, less packet loss, and less delay than existing protocols.

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AOMDV Intelligent Decision (AOMDV-ID) to Minimize Routing Delay for Diverse VANETs

Cited by 7 publications

References 16 publications

A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks

A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks

A Dynamic Addressing Hybrid Routing Mechanism Based on Static Configuration in Urban Rail Transit Ad Hoc Network

Intelligent Decision Based Route Selection and Maintenance Approach Using AOMDV in VANET

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