An Extension of NS-3 Simulator to Support Efficient MANET Performance Analysis

Bugarcic, Pavle; Jevtić, Nenad; Malnar, Marija

doi:10.1109/telsiks46999.2019.9002027

Cited by 2 publications

(2 citation statements)

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“…The simulation network of the VANET network simulator 3.29 is used in the study of Bugarcic, Jevtic & Malnar (2019) . NS-3 has a mobility model that uses the trace file of NS-2.…”

Section: Conceptual Designmentioning

confidence: 99%

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Alameri

Komárková

Al-Hadhrami

et al. 2022

PeerJ Computer Science

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Mobile ad-hoc networks (MANETs) and wireless mesh networks (WMNs) are used in a variety of research areas, including the military, industry, healthcare, agriculture, the Internet of Things (IoT), transportation, and smart cities. The swift advancement in MANET technology is the driving force behind this rising adoption rate. Routing over MANET is a critical problem due to the dynamic nature of the link qualities, even when nodes are static. A key challenge in MANETs is the need for an efficient routing protocol that establishes a route according to certain performance metrics related to the link quality. The routing protocols utilised by the nodes in WMNs and MANETs are distinct. Nodes in both types of networks exchange data packets through the routing protocols. For this highly mobile network, the ad-hoc On-Demand Distance Vector (AODV) routing protocol has been suggested as a possible solution. Recent years have attracted researchers’ attention to AODV since it is a routing technique for ad-hoc networks that prevents looping. The architecture of this routing protocol considers several factors, including the mobility of nodes, the failure of connection links, and the loss of packets. In this systematic review, one of the key focuses is bringing attention to the classic AODV, which was developed after discussing the recent development of several versions of AODV. The AODV routing protocol performs a path strength check to generate a more reliable and secure route between the source and destination nodes. In AODV, investigations demonstrate advances in both the format protocol approach and the network simulation-2 (NS-2), and these improvements were made in the same scenario used to revitalise AODV. It has been discovered that the AODV is more effective in several aspects, such as throughput, end-to-end delay, packet delivery ratio (PDR), energy consumption, jitter, packet loss ratio, and network overhead. Furthermore, this paper presents this systematic review based on AODV modifications in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It also provides a methodological framework for the papers’ selection.

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“…The simulation network of the VANET network simulator 3.29 is used in the study of Bugarcic, Jevtic & Malnar (2019) . NS-3 has a mobility model that uses the trace file of NS-2.…”

Section: Conceptual Designmentioning

confidence: 99%

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Alameri

Komárková

Al-Hadhrami

et al. 2022

PeerJ Computer Science

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“…However, it optionally allows to write simulation scripts in Python. It has been widely used in the implementation and analysis of different types of wireless networks such as the work done in [86][87][88][89]. In all of our simulations, the ns-3.32 simulator version is used.…”

Section: Ns-3 Simulatormentioning

confidence: 99%

Adaptive Multicast Routing Protocol Based on Reinforcement Learning

Mohammed

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Current Mobile Ad-hoc Network (MANET) multicasting approaches either suffer from low Packet Delivery Ratio (PDR) or high overhead. These methods rely on metrics like hop count to find the optimal path to the destination. Once the path is selected, all packets are sent over the same path as long as it is available. However, a path that is deemed optimal at a specific instance of time may not retain its optimality at a subsequent moment due to node mobility. Moreover, using a metric like hop count that does not consider link quality can lead to poor PDR, as it can favor an unreliable path over a reliable one just because it is the shortest. To tackle these concerns, Q-Learning Adaptive -Multicast Ad hoc On-Demand Distance Vector Routing (QLA-MAODV) protocol is proposed. It is an adaptive and bandwidthefficient multicast routing protocol based on Q-learning. Unlike traditional methods, QLA-MAODV prioritizes link reliability over simple metrics like hop count, aiming to build a more stable multicast tree. The protocol utilizes the periodic Group Hello (GRPH) messages to explore the environment, identifying alternative paths for use in case of path degradation. The protocol continuously updates path costs, facilitating proactive switching to more reliable paths. Simulations in Network Simulator 3 (NS-3) reveal the protocol's superiority over the traditional Multicast Ad-hoc On-demand Distance Vector (MAODV) protocol. Additionally, it outperforms a modified version, MAODV-Route Reliability (MAODV-RR), that uses link reliability as the routing metric, demonstrating improvement in PDR and reduced multicast-related overhead.

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An Extension of NS-3 Simulator to Support Efficient MANET Performance Analysis

Cited by 2 publications

References 10 publications

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Systematic review on modification to the ad-hoc on-demand distance vector routing discovery mechanics

Adaptive Multicast Routing Protocol Based on Reinforcement Learning

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