A Simulation Study of Routing Protocols for Vehicular Ad Hoc Networks Based on OPNET

Ad Hoc Routing with Distributed Ordered Sequences

This paper proposes a mathematical framework to model and analyze the energy consumption of routing protocols in multihop wireless networks such Mobile Ad Hoc Networks (MANETs) or Sensor Networks (WSNs) by taking into account the protocol parameters, the traffic pattern and the network characteristics defined by the medium channel properties, the dynamic topology behavior, the network diameter and the nodes density. Moreover, our framework allows to classify routing protocols by exploring the relationship between application requirements and wireless network features. To the best of our knowledge, there is no such proposed framework that provides in-depth an analytical investigation of above relationship. We apply this model to a Beacon-less routing protocol Pizza-Forwarding (PF) compared to well known routing protocols such as Optimized Link State Routing, Ad Hoc On Demand Distance Vector Routing, Greedy Perimeter Stateless Routing and a Simple Random Walk Routing in order to underline their behavior according to the network features and application requirements. Finally, we show that Beacon-less routing protocol should be a best candidate to save energy in WSNs.

Vehicular Ad Hoc Networks (VANETs), a subclass of Mobile Ad Hoc Networks (MANETs), rely on efficient routing protocols to maintain reliable communication in highly dynamic and decentralized environments. While numerous routing strategies have been proposed, their performance varies significantly with the choice of underlying mobility models that simulate real vehicular movement. This study presents a two-phase evaluation of five widely used routing protocols—Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR), and Geographic Routing Protocol (GRP)—across fourteen realistic mobility models, including the Intelligent Driver Model (IDM), Car-Following Model (CFM), and Lighthill–Whitham–Richards (LWR) model. Simulations are executed using Simulation of Urban Mobility (SUMO), Network Simulator 3 (NS-3), and the Veins framework. The performance is assessed using eight key metrics: Packet Delivery Ratio (PDR), End-to-End Delay (E2ED), Throughput, Jitter, Energy Consumption, Packet Loss Ratio (PLR), Normalized Routing Load (NRL), and Link Breakage Rate (LBR). Among the evaluated protocol–mobility combinations, AODV paired with the CFM model demonstrated comparatively favorable performance under the considered simulation configuration: 93% PDR, 79.4 ms E2ED, 332 kbps throughput, 3.4 ms jitter, 3.48 J energy consumption, 7% PLR, 0.3 NRL, and 5 link breakages per simulation. This study provides a systematic and unified comparative evaluation of five widely used routing protocols across fourteen simulation-based vehicular mobility models. The findings provide scenario-specific comparative insights for simulation-based VANET performance evaluation and offer practical, simulation-based guidance for selecting suitable protocol–mobility model combinations under the evaluated experimental conditions.

Wireless internet has become popular in recent years due to the tremendous growth in the number of mobile computing devices and high demand for continuous network connectivity regardless of physical locations. In this paper, we investigate the effects of routing protocols on the performance of Transmission Control Protocol (TCP) variants in multi-hop wireless networks. Through simulations we study the effects of Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR), Ad hoc On demand Distance Vector (AODV) and Dynamic Source Routing (DSR) routing protocols on TCP Tahoe, TCP Reno, TCP Newreno, TCP with Selective Acknowledgment (SACK) option and TCP Vegas. The simulations are carried out for static as well as mobile nodes. The performance metric used is throughput. Another metric, expected throughput is used for the comparison of throughput when nodes are mobile.

Mobile Ad-hoc Networks (MANETs) operate without infrastructure where nodes can move randomly. Therefore, routing in MANETs is a challenging task. In this paper we evaluate the performance of three important MANET routing protocols: Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) when employed to forward scalable video contents. AODV and DSR are reactive protocols in that routing paths are established once needed. On the other hand, OLSR is a proactive routing protocol where routing information is exchanged and maintained continuously. The goal of the performance evaluation in this study is to assess the performance of AODV, DSR and OLSR in communicating scalable video contents. In the simulation part of this paper, a real video sequence is communicated where the characteristics and quality of the video decoded at receiver nodes are evaluated. NS2 along with extensions and other evaluation frameworks have been used to assess the performance of the MANET routing protocols when used for scalable video communication. The framework allows starting from a raw video that is encoded, packetized, transmitted through a network topology and collected at receiver to be decoded, played, and evaluated. Delay and timing constraints are taken into consideration when decoding the received video packets.

Mobile Ad Hoc Network (MANET) comprises a group of mobile or wireless nodes that are placed randomly and dynamically which causes the constant change between nodes. When considering a routing protocol to deploy in any given situation on MANET, factors such as the mobility model, mobility of nodes, the network size and packet size should be carefully considered because the routing protocols configured with the mobility model can highly affect the performance of MANET. This paper analysed the impact of two different routing protocols (i.e. Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR)) on the performance of Random WayPoint (RWP) mobility model. Three measures of performance metrics (i.e. average throughput, average delay and average traffic received) were used. In all three-performance metrics, the simulated results indicated that Random WayPoint (RWP) configured with OLSR protocol performed better than RWP configured with DSR protocol. This indicates that the choice of a routing protocol for a specific mobility model should be considered in a network design.

A Mobile Ad Hoc Network (MANET) protocol requires proper settings to perform data transmission optimally. To overcome this problem, it is necessary to select the correct routing protocol and use the routing protocol’s default parameter values. This study examined the effect of route request parameters, such as RREQ_RETRIES and MAX_RREQ_TIMOUT, on the Ad Hoc On-demand Distance Vector (AODV) protocol, which was then compared with the default AODV performance Optimized Link State Routing (OLSR) protocols. The performance metrics used for measuring performance were Packet Delivery Ratio (PDR), throughput, delay, packet loss, energy consumption, and routing overhead. The results show that the OLSR protocol has a smaller delay than the AODV protocol, while in other measurements, the AODV protocol is better than OLSR. By reducing the combination value of RREQ_RETRIES, MAX_RREQ_TIMEOUT in AODV routing to (2, 10 s) and (3, 5 s), the protocol’s performance can be improved. The two combinations result in an average increase in throughput performance of 3.09%, a decrease in delay of 17.7%, a decrease in packet loss of 27.15%, and an increase in PDR of 4.8%. For variations in the speed of movement of nodes, 20 m/s has the best performance, while 5 m/s has the worst performance.

Wireless technology based on the IEEE 802.11 standard is widely deployed. This technology is used to support multiple types of communication services (data, voice, image) with different QoS requirements. MANET (Mobile Adhoc NETwork) does not require a fixed infrastructure. Mobile nodes communicate through multihop paths. The wireless communication medium has variable and unpredictable characteristics. Furthermore, node mobility creates a continuously changing communication topology in which paths break and new one form dynamically. The routing table of each router in an adhoc network must be kept up-to-date. MANET uses Distance Vector or Link State algorithms which insure that the route to every host is always known. However, this approach must take into account the adhoc networks specific characteristics: dynamic topologies, limited bandwidth, energy constraints, limited physical security, ... Two main routing protocols categories are studied in this paper: proactive protocols (e.g. Optimised Link State Routing - OLSR) and reactive protocols (e.g. Ad hoc On Demand Distance Vector - AODV, Dynamic Source Routing - DSR). The proactive protocols are based on periodic exchanges that update the routing tables to all possible destinations, even if no traffic goes through. The reactive protocols are based on on-demand route discoveries that update routing tables only for the destination that has traffic going through. The present paper focuses on study and performance evaluation of these categories using NS2 simulations. We have considered qualitative and quantitative criteria. The first one concerns distributed operation, loop-freedom, security, sleep period operation. The second are used to assess performance of different routing protocols presented in this paper. We can list end-to-end data delay, jitter, packet delivery ratio, routing load, activity distribution. Comparative study will be presented with number of networking context consideration and the results show the appropriate routing protocol for two kinds of communication services (data and voice).

In this paper we present a stepwise formal development of the Optimised Link State Routing (OLSR) protocol in Event-B. OLSR is a proactive routing protocol which finds routes for different destinations in advance by exchanging control messages through the network. As a consequence, whenever a data packet is injected into the network can be delivered to a certain destination immediately. To achieve this, routing tables in OLSR are continuously updated, by following a rather complicated algorithm. By modelling OLSR in Event-B, we address the scalability problem of our previous work [1], and structure the OLSR complexity in five distinct abstraction layers. These layers are manageable to understand and to verify and are linked to each other by refinement. As Event-B is supported by a theorem proving platform (Rodin), we model and prove functional properties of OLSR in an automated and interactive manner, at a highly general level. Our approach can serve as a proof-of-concept to be adapted to modelling and verifying of the other routing protocols for large-scale networks.

OLSR vs DSR: A comparative analysis of proactive and reactive mechanisms from an energetic point of view in wireless ad hoc networks

The performance of mobile ad-hoc networks (MANET) is related to the efficiency of the routing protocols in adapting to frequently changing network topology and link status. This paper addresses the issue by comparing the relative performance of three key ad-hoc routing protocols: destination-sequenced distance vector (DSDV), ad-hoc on-demand distance vector (AODV) and optimized link state routing (OLSR). The protocols are tested based on two scenarios, namely, tactical networks for ships and sensor-based network nodes. Four performance metrics were measured by varying the maximum speed of mobile hosts, network size and traffic load, to assess the routing capability and protocol efficiency. The simulation results indicate that AODV performs better than OSLR and DSDV in the first scenario. Although OLSR also performed relatively well, the associated high routing overhead is the dominant reason for not choosing it. On the other hand, OLSR emerged as the protocol of choice for sensor networks, where the high routing overhead is counteracted by consistently better performance in all other metrics. Due to the slow evolution of the sensor network topology, OLSR performed satisfactorily for best effort traffic but needed subtle adjustments to balance between latency and bandwidth to meet the requirements of delay-sensitive applications

In ad-hoc networks, a communication link between two mobile computers is not always bi-directional, i.e. uni-directional, since transmission power of mobile computers are not the same. Though some ad-hoc routing protocols, e.g. Extended DSR (Dynamic Source Routing), support routing with unidirectional links, multiple flooding RREP are used and communication overhead is high. This paper proposes a new ad-hoc routing protocol TPSR (Transmission Power based Routing Protocol) that supports unidirectional links in mobile ad-hoc networks. In our protocol, we use information of transmission power of each node to detect the existence of unidirectional links and to transmit single unicast RREP. Our protocol shows better performance in terms of the number of required messages than extended DSR in such environments as having unidirectional links.

Ad hoc network and cloud computing are emerging technologies and so is the emerging concept derived from these technologies named as ad hoc cloud. All these concepts are discussed in this paper, and ad hoc cloud network is implemented using two scenarios, each with different ad hoc network protocol, namely, Optimized Link State Routing (OLSR) and Geographic Routing Protocol (GRP). OPNET Modeler 14.5 is used for the simulation model. In this simulation model, implementation of multi-hop ad hoc network is done with cloud servers using services such as HTTP, FTP, email, print, and database. The performance of the ad hoc cloud network using these two protocols is observed and compared. Based on these observations, results and comparison GPR perform better than OLSR.

This paper presents mathematical framework for calculating transmission probability in IEEE 802.11 p based networks at Medium access control (MAC) layer, mathematical framework for calculating energy costs of the chosen routing protocols at network layer, and enhancements in optimized link state routing (OLSR), dynamic source routing, (DSR) and fish-eye state routing (FSR) to tackle delay in vehicular ad hoc networks (VANETs). Besides the enhancements, we analyze ad hoc ondemand distance vector (AODV) along with OLSR, DSR, and FSR as well. To evaluate the effect of our proposed transmission probabilities in the selected routing protocols, we choose network throughput, end-to-end delay (E2ED), and normalized routing load (NRL) as performance metrics. We also investigate the effect of different mobilities as well as scalabilities on the overall efficiency of the enhanced and default versions of the selected protocols. Simulations results which are conducted in NS-2 show that overall DSR-mod outperforms rest of the protocols.

Background/Objectives: The capabilities of vehicular communications technology is ever expanding and due to this reason, vehicular Ad-hoc networks are known as the most essential devices for significant progressions in modern era. The main purpose is to entertain, to ensure safety and take precautionary measures in case of emergency. The enhanced network performance is always subjected to efficient routing in the networks. In fact, routing information is based on the routing protocols in every network system. This research aims to modify further to improve the implementation of routing protocols including Ad hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Dynamic MANET On-demand (DYMO) intended for VANETS which are viewed as progressively helpful and appropriate for Ad-hoc systems. Methods: The upgraded adaptation of AODV, DSR and DYMO are called as MOD-AODV, MOD-DSR and MOD-DYMO. Ad-hoc networks specifically in VANETs rely on simulation because of the complication and level of intricacy in deployment of such networks. However, for validation of such proposals the most important and representative factors are overlooked during the experiments. Moreover, a statistical analysis is presented that is based on 2K factorial that revealed the technique so as to decide the most extreme model viewpoints influencing the working of routing protocols under the system density and traffic loads. Three reactive routing protocols including Packet Delivery Ratio (PDR), Average End-to-End Delay (AE2ED) and Network Routing Overhead (NRO) are selected to break down the execution for the implementation of estimating parameters. Findings: At last, the outcomes show that at the expense of higher NRO, MOD-DYMO accomplished the better PDR and AE2ED than other routing protocols on varying nodes thickness and number of Constant Bit Rate (CBR) connections in all considered scenarios. Keywords: Optimized Link State Routing (OLSR), Routing, Routing Congestion, Wireless Multi-hop