Performance Comparison of Multicast Routing Protocols Based on Route Discovery Process for MANET

Adhvaryu, Kinjal

doi:10.1007/978-981-15-0146-3_9

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…In order to implement our algorithms for attaining better performance for routing in MANETs, we exploit open source simulator Network Simulator-3 (NS-3) [44][45][46] to implement the topologies that generates the routing data as inputs for ML algorithms training and testing phases. Initially MANET's scenarios are implemented to monitor the performance of existing routing protocols such as AODV, DSR, DSDV and OLSR in terms of E2E delay, throughput and PDR.…”

Section: Proposed Methodologymentioning

confidence: 99%

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

2021

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Routing protocols in Mobile Ad Hoc Networks (MANETs) play a pivotal role in ensuring quality of service (QoS) and improving network performance. Selection of optimal routing protocol and suitable parameters for a given network scenario is a major task that ultimately affects the behavior of network. This work exploits machine learning (ML) techniques for the selection of adequate routing parameters and protocol by regression of parameters in given network scenario to ensure optimal performance. The network is trained based on parametric setup of expanding ring search mechanism (ERS) and random early detection (RED) technique to estimate network throughput, end to end (E2E) delay and packets delivery ratio (PDR) and is tested via wide-ranging simulations in varying network topologies. Both RED and ERS mechanisms are aimed to control link and node level congestion in the reactive routing protocols and our aim is to select the best suited parameters for given network topologies based on ERS and RED parametric setups and improve performance for ensuring QoS. ML algorithms are trained and tested for their performance in varying network topologies. We have exploited these models with best performance for ERS and RED based routing in given topological arrangements. The performance of the ML algorithms is evaluated on the basis of root mean squared error (RMSE) and mean absolute error (MAE) for regression settings. Prediction models with up to par RMSE and MAE out-turns are attained and exploited for selection of suitable ERS and RED parameters and routing protocols in order to ensure the QoS for given network scenario. Variants of standard routing protocols are devised based on their performance and the ML techniques are exploited for prediction of QoS parameters to decide on the optimal variant that attains significant improvement in performance. Results are shown to confirm that considerable improvement in QoS is attained. INDEX TERMS Ad hoc multi hop wireless networks, congestion control, expanding ring search, machine learning, mobile ad hoc networks, on demand routing protocols, random early detection, regression, quality of service.

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Section: Proposed Methodologymentioning

confidence: 99%

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

2021

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“…Routing protocol based on topology in VANETs uses mainly ad-hoc network routing protocols and employs the existing link information in the network to forward packets. It is divided into two categories: table driven routing or proactive [19] and ondemand routing or reactive [20] (Fig. 3).…”

Section: Routing Protocols Based On Topology In Vanetsmentioning

confidence: 99%

Improving AODV Performance by Software Defined Networking Using NS3

Brahmia

Tolba

Hafs

2022

Applied Computer Systems

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Nowadays, vehicular networks attract car manufacturers, network researchers, and governments as well. They represent one of the building blocks, for the intelligent transportation systems. Our task is to study the employment of SDN advantages to facilitate and improve the performance of vehicular ad-hoc networks. The goal of the research is to evaluate AODV routing protocol performance improved with SDN technology applied on VANET network in specified environment of a city. We have evaluated three parameters: packet delivery ratio, end-to-end delay and throughput using SUMO and NS3 simulators. The implemented evaluation protocol shows the importance of the adopted approach.

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“…Retransmissions are managed through buffer aided decodable network coding and priority aid. A route discovery mechanism for location based prediction model is proposed in [15]. The model is named as Hop-Prediction-ERS-AODV (HP-ERS-AODV), designed to discover the destination node based on previous hop counts.…”

Section: Related Workmentioning

confidence: 99%

“…Routing protocols in MANETs (i.e., AODV, DYMO, DSR) deploy ERS for searching the route towards the target node [4,11,13,15]. Each protocol has its own respective values for TTL_ START, TTL_INCREMENT, TTL_THRESHOLD and NETWORK_DIAMETER values with different WAITING_TIMEs for implying ERS mechanism.…”

Section: Per Hop Behavior For Packets Executionmentioning

confidence: 99%

Adaptive Expanding Ring Search Based Per Hop Behavior Rendition of Routing in MANETs

Durr-e-Nayab¹,

Zafar²,

Basheri³

2021

Computers, Materials &Amp; Continua

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Routing protocols in Mobile Ad Hoc Networks (MANETs) operate with Expanding Ring Search (ERS) mechanism to avoid ooding in the network while tracing step. ERS mechanism searches the network with discerning Time to Live (TTL) values described by respective routing protocol that save both energy and time. This work exploits the relation between the TTL value of a packet, traf c on a node and ERS mechanism for routing in MANETs and achieves an Adaptive ERS based Per Hop Behavior (AERSPHB) rendition of requests handling. Each search request is classi ed based on ERS attributes and then processed for routing while monitoring the node traf c. Two algorithms are designed and examined for performance under exhaustive parametric setup and employed on adaptive premises to enhance the performance of the network. The network is tested under congestion scenario that is based on buffer utilization at node level and link utilization via back-off stage of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). Both the link and node level congestion is handled through retransmission and rerouting the packets based on ERS parameters. The aim is to drop the packets that are exhausting the network energy whereas forward the packets nearer to the destination with priority. Extensive simulations are carried out for network scalability, node speed and network terrain size. Our results show that the proposed models attain evident performance enhancement.

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Performance Comparison of Multicast Routing Protocols Based on Route Discovery Process for MANET

Cited by 4 publications

References 9 publications

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

Improving AODV Performance by Software Defined Networking Using NS3

Adaptive Expanding Ring Search Based Per Hop Behavior Rendition of Routing in MANETs

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