Performance Analysis of Mobile Ad Hoc Network Routing Protocols Using ns-3 Simulations

Mobile ad hoc networks (MANETs) consist of mobile nodes that can communicate with each other through wireless links without reliance on any infrastructure. The dynamic topology of MANETs poses a significant challenge for the design of routing protocols. Many routing protocols have been developed to discover routes in MANETs through various mechanisms such as source, distance vector, and link state routing. In this thesis, we present a comprehensive performance comparison of several prominent MANET routing protocols. The protocols studied are Destination-Sequenced Distance-Vector (DSDV), Optimized Link State Routing (OLSR), Ad Hoc On-Demand Distance Vector protocol (AODV), and Dynamic Source Routing (DSR). We consider a range of network dynamicity and node density, model three mobility models: Steady-State Random Waypoint (SS-RWP), Gauss-Markov (G-M), and Lévy Walk, and use ns-3 to evaluate their performance on metrics such as packet delivery ratio, end-to-end delay, and routing overhead. We believe this study will be helpful for the understanding of mobile routing dynamics, the improvement of current MANET routing protocols, and the development of new protocols

A Simulation-Based Performance Evaluation of AODV and DSR in Mobile Ad-Hoc Networks (MANETs)

This work evaluates and compares the performance of two reactive routing protocols for mobile ad-hoc networks: Ad hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The study focuses on the design and evaluation of routing protocols in mobile ad-hoc networks. Study and implementation of these protocols are been carried out using network simulator (ns2) and metrics such as Packet Delivery Fraction, Average end-to-end Delay, Routing overhead and Normalized Routing are used for performance analysis. Results are presented as a function of these metrics and the graphs generated show that DSR performs better than AODV when fewer nodes are been used

Performance Evaluation of MANET Based Routing Protocols for VANETs in Urban Scenarios

Abstract. Vehicular Ad hoc NETworks (VANETs) are self-organizing ad hoc networks that are specifically designed for communication among vehicles where vehicles are themselves the nodes. Although routing protocols have already been analyzed and compared in the past for Mobile Ad hoc Networks (MANETs), simulations and comparisons of routing protocols for VANETs have almost always been done considering random motions with non-urban specific parameters. This paper studies the performance of Ad hoc On-Demand Distance Vector (AODV) and Destination Sequenced Distance Vector (DSDV) which are popular routing protocols in MANETS for routing among vehicular nodes in VANETs. The effects of urban motions on the simulation parameters, their consequences on routing performance are compared between the two protocols in this study. The VANET simulations showed that on-demand based protocol AODV performs better than the table-driven based DSDV protocol for two performance metrics for vehicular nodes moving in urban scenarios

Performance Analysis of On-Demand Routing Protocols in Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have recently gained a lot of popularity due to their rapid deployment and instant communication capabilities. WMNs are dynamically self-organizing, self-configuring and self-healing with the nodes in the network automatically establishing an adiej hoc network and preserving the mesh connectivity. Designing a routing protocol for WMNs requires several aspects to consider, such as wireless networks, fixed applications, mobile applications, scalability, better performance metrics, efficient routing within infrastructure, load balancing, throughput enhancement, interference, robustness etc. To support communication, various routing protocols are designed for various networks (e.g. ad hoc, sensor, wired etc.). However, all these protocols are not suitable for WMNs, because of the architectural differences among the networks. In this paper, a detailed simulation based performance study and analysis is performed on the reactive routing protocols to verify the suitability of these protocols over such kind of networks. Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Dynamic MANET On-demand (DYMO) routing protocol are considered as the representative of reactive routing protocols. The performance differentials are investigated using varying traffic load and number of source. Based on the simulation results, how the performance of each protocol can be improved is also recommended.Wireless Mesh Networks (WMNs), IEEE 802.11s, AODV, DSR, DYMO

A Survey of MANET Routing Protocols in Large-Scale and Ordinary Networks

An ad hoc network (MANET) consists of mobile nodes that communicate with each other. Routing in ad hoc network is a challenging task because nodes are mobile. Efficient routing protocols have better performance in such networks. Many protocols have been proposed for ad hoc networks such as: Ad hoc on-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), Dynamic Source Routing (DSR), and Geographic routing protocol (GRP). these approaches have not been evaluated for the same conditions in pervious researches. But in this study, the performance of these protocols is evaluated in various network conditions and with different packet size patterns. Also, different MAC layers like 802.11b, 802.11g in ordinary and large-scale networks are considered. For the evaluation, Different metrics like packet delivery ratio, end-to-end delay, Mac delay and Routing traffic received/sent, are applied. All simulations have been done using OPNET

Comparative Study of Routing Protocols for Mobile Ad-hoc networks

In this paper, we describe the Optimized Link State Routing Protocol (OLSR), a proactive routing protocol for Mobile Ad-hoc NETworks (MANETs). We evaluate its performance through exhaustive simulations using the Network Simulator 2 (ns2), and compare with other ad-hoc protocols, specifically the Ad-hoc On-Demand Distance Vector (AODV) routing protocol and the Dynamic Source Routing (DSR) protocol. We study the protocols under varying conditions (node mobility, network density) and with varying traffic (TCP, UDP, different number of connections/streams) to provide a qualitative assessment of the applicability of the protocols in different scenarios

Performance analysis of on-demand routing protocols in wireless mesh networks

Wireless Mesh Networks (WMNs) have recently gained a lot of popularity due to their rapid deployment and instant communication capabilities. WMNs are dynamically self-organizing, self-configuring and self-healing with the nodes in the network automatically establishing an adiej hoc network and preserving the mesh connectivity. Designing a routing protocol for WMNs requires several aspects to consider, such as wireless networks, fixed applications, mobile applications, scalability, better performance metrics, efficient routing within infrastructure, load balancing, throughput enhancement, interference, robustness etc. To support communication, various routing protocols are designed for various networks (e.g. ad hoc, sensor, wired etc.). However, all these protocols are not suitable for WMNs, because of the architectural differences among the networks. In this paper, a detailed simulation based performance study and analysis is performed on the reactive routing protocols to verify the suitability of these protocols over such kind of networks. Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Dynamic MANET On-demand (DYMO) routing protocol are considered as the representative of reactive routing protocols. The performance differentials are investigated using varying traffic load and number of source. Based on the simulation results, how the performance of each protocol can be improved is also recommended

Performance Improvement of AODV in Wireless Networks using Reinforcement Learning Algorithms

This paper investigates the application of reinforcement learning (RL) techniques to enhance the performance of the Ad hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad hoc networks (MANETs). MANETs are self-configuring networks consisting of mobile nodes that communicate without the need for a centralized infrastructure. AODV is a widely used routing protocol in MANETs due to its reactive nature, which reduces overhead and conserves energy. This research explores three popular Reinforcement Learning algorithms: SARSA, Q-Learning and Deep Q-Network (DQN) to optimize the AODV protocol's routing decisions. The RL agents are trained to learn the optimal routing paths by interacting with the network environment, considering factors such as link quality, node mobility, and traffic load. The experiments are conducted using network simulators to evaluate the performance improvements achieved by the proposed RL-based enhancements. The results demonstrate significant enhancements in various performance metrics, including reduced end-to-end delay, increased packet delivery ratio, and improved throughput. Furthermore, the RL-based approaches exhibit adaptability to dynamic network conditions, ensuring efficient routing even in highly mobile and unpredictable MANET scenarios. This study offers valuable insights into harnessing RL techniques for improving the efficiency and reliability of routing protocols in mobile ad hoc networks

Optimizing ad-hoc on-demand distance vector (AODV) routing protocol using geographical location data

This thesis summarizes the body of research regarding location-aided routing protocols for mobile ad-hoc networks (MANET). This study focuses on the use of geographical location information to reduce the control traffic overhead caused by the route discovery process in the ad-hoc on-demand distance vector (AODV) routing protocol. During this process, AODV will flood the entire network with route request packets. This introduces significant packet-handling overhead into the network. This thesis introduces Geographical AODV (GeoAODV), which uses geographical location information to limit the search area during the route discovery process to include only promising search paths. Also, this thesis benchmarks GeoAODV\u27s performance against Location Aided Routing (LAR) and examines four mechanisms for reducing the control-packet overhead introduced by the route discovery process: LAR Distance, LAR Zone, GeoAODV, and GeoAODV Rotate. OPNET Modeler version 16.0 was used to implement each of these mechanisms and compare their performance via network simulations. The results indicate that location-aided routing can significantly reduce the aforementioned control-packet overhead