SBADR: stable and bandwidth aware dynamic routing protocol for mobile ad hoc network

Ad Hoc Routing with Distributed Ordered Sequences

Mobile Ad hoc Networks (MANETs) are considered as a new paradigm of infrastructure-less mobile wireless communication systems. MANETs are being widely studied and it is the technology that is attracting a large variety of applications. Routing in MANETs is considered a challenging task due to the unpredictable changes in the network topology, resulting from the random and frequent movement of the nodes and due to the absence of any centralized control [1][2]. In this paper, we evaluate the performance of reactive routing protocols, Ad hoc On demand Distance Vector (AODV) and Dynamic Source Routing (DSR) and proactive routing protocol Destination Sequenced Distance Vector (DSDV). The major goal of this study is to analyze the performance of well known MANETs routing protocol in high mobility case under low, medium and high density scenario. Unlike military applications, most of the other applications of MANETs require moderate to high mobility. Hence it becomes important to study the impact of high mobility on the performance of these routing protocols. The performance is analyzed with respect to Average End-to-End Delay, Normalized Routing Load (NRL), Packet Delivery Fraction (PDF) and Throughput. Simulation results verify that AODV gives better performance as compared to DSR and DSDV.

Mobile ad hoc networks (MANETs) have several uses, including smart cities, medical applications, military uses, and rescue operations. They are also anticipated to be extremely well-liked in 5G since they have both basic and cutting-edge capabilities of the upcoming communication technology. Recently, there has been a lot of focus on 5G-based MANET. Its main characteristic is that quality of service (QoS) requirements are quite strict and nodes are continuously subjected to heavy traffic loads. Existing routing technologies have demonstrated shortcomings when implemented in 5G-based MANETs. In this manuscript, enhancing the ad hoc on-demand distance vector (AODV) routing protocol using graph learning-based spatial-temporal convolutional network to ensure quality of service in 5G-based MANET (EAODV-GLSTCN-QoS-5GMANET) is proposed. This research proposes a unique technique (GLSTCN-AODV) to increase the performance of MANET by integrating AODV protocol with the graph learning-based spatial-temporal convolutional network (GLSTCN). The GLSTCN's primary function in AODV is to update the state information database of each node to destination, maintain link stability, and find guaranteed QoS routes. The proposed EAODV-GLSTCN-5GMANET is implemented in MATLAB, and the performance of EAODV-GLSTCN-5GMANET is estimated under performance metrics likes packet delivery ratio (PDR), end-to-end (E2E) delay, and throughput. Finally, the proposed EAODV-GLSTCN-5GMANET method provides 27.20%, 25.81%, and 32.18% higher packet delivery ratio and 17.20%, 26.41%, and 32.18% higher throughput when comparing with existing techniques like improved technique of AODV routing protocol utilizing reinforcement learning for ensuring QoS in 5G-based MANET (AODV-RL-5GMANET), new deep Q-network design for QoS multicast routing in cognitive radio MANETs (DQN-MCR-CRMANET) and novel topology control algorithm for improving 5G-based MANET performance by flexibly adjusting coverage radius (TCA-MANET-FACR), respectively.

A Mobile Ad Hoc Network represents a system of wireless mobile nodes that can freely and dynamically selforganize into arbitrary and temporary network topologies, allowing people and devices to seamlessly communicate without any pre-existing communication architecture. The growth of real time multimedia application in such environments, has drawn a lot of attention to wireless networks that support quality of service (QoS). In this work, the QoS metrics, delay and link life time (LLT) of the path are dynamically calculated. Based on these values the routing decisions are made. Here the multipath routing protocol is taken as the base protocol. The proposed algorithm finds the multiple QoS routes only, based on the QoS metrics and stores only those paths in the routing table. The route is selected based on the integrated QoS metric and is used to transmit the data. The base protocol used is multipath AODV(Ad Hoc On demand Distance Vector ) routing protocol. The proposed protocol may take extra time during route discovery process to compute the additional QoS parameters, but this time is compensated by having only QoS paths for data transmission. A few patents on the QoS Routing for MANETS have been reviewed.The simulator NS-2.34 is used to simulate and compare the performance of the protocols in terms of the QoS metrics such as end-to-end delay, PDR in the MANET. Keywords: Mobile Ad Hoc Network (MANET), Quality of Service (QoS), Destination Sequence Distance Vector (DSDV), Dynamic Source Routing (DSR), Ad Hoc On demand Distance Vector (AODV), LLT (Link Life Time), RLT (Route Life Time), PLTR (Percentage Life Time Ratio), TCP (Transmission Control Protocol), CBR (Constant Bit Rate), PDR (Packet Delivery Ratio).

Background:AMobileAdHocNetwork (MANET) consistsofmany independentnodes that operate over awireless topology with numerous Quality of Service (QoS) requirements. So, a robust routing protocol that also provides QoS parameters to its different range of applications is needed. Various network parameters like node density, node mobility, field size etc. also effects the QoS parameters of MANETs. Methods: The traditional reactive routing protocols do not have any backup route in case of a node failure and hence are not effective for MANETs. Ad Hoc on Demand Distance Vector Backup Routing (AODV BR) protocol performs better than traditional routing protocols but is not effective when the backup route fails. So, to counter this problem, the authors had proposed AODV nth BR that keeps on providing backup routes when multiple nodes fail and hence successfully transfers the data to the destination. The nodes for backup routing are selected based on their distance from the failed node and energy efficiency. Results: In this paper, the performance of AODV nth BR has been compared with AODV, DSR and AODV BR protocol under varying node density (nodes 20, 60,100) and node mobility conditions (5m/s, 20m/s, 50m/s). The values for Packet Delivery Fraction (PDF) for 60 nodes at speed 20m/s in case of AODV nth BR protocol after 6000 rounds is 0.3054. Comparatively, value of AODV BR is 0.2664, AODV is 0.1936 and DSR is 0.1056. QoS performance is measured in terms of end to end delay, packet delivery fraction and lifetime of devices and it has been shown through simulated results that AODV nth BR protocol gives better output than traditional routing protocols. Conclusion: From the simulated results explained in detail in the paper, it has been observed that route after link breakage is found to be best with AODV nth BR protocol and this can be clearly seen in the QoS parameters obtained.Keywords: AODV BR, AODV nth BR, MANETs, Node Density, Node Mobility

Multi hop links are used to communicate between nodes in a Mobile Ad Hoc Network (MANET). Data packets are routed through intermediate nodes in the network to the destination node since each node functions as a router. Dynamic routing protocols are being developed for network communication efficiency. Routing protocols in MANETS face problems such as versatility, scalability, and restricted bandwidth. A fuzzy logic approach is suggested as part of the study. In this work, a fuzzy logic methodology is planned to choose the best routes in order to better QoS End-to-end delay (Ae), when a node leaves the network (Nl), A fuzzy rule-based scheme NR includes the number of packets dropped (ND) and the number of path error RRER caused parameters. Simulations are carried out in this study using the proposed fuzzy approach process Simulations are carried out in this study using the future process fuzzy approach. The measurement criteria are throughput and the number of packets dropped. The tentative results obtained show that the proposed fuzzy approach improves the QoS better than existing regular Ad hoc On-demand Distance Vector ( AODV) routing protocol. In the final stage of investigation, the use of a hybrid optimization approach to choose the best route is suggested. The proposed hybrid optimization is based on the Genetic Algorithm (GA) and the Hill Climbing algorithm. The hybrid optimization aids in the resolution of the local minimum problem Hill-climbing begins with an infeasible solution and continues until a viable solution is found, at which point the viable solution is returned to GA. The simulation results show that the throughput is high. When compared to the AODV protocol, the proposed Fuzzy-Hybrid GA method yields about 29.56 percent more and 6.33 percent more when compared to the Fuzzy-GA solution.

Wireless sensor network (WSN) with several sensors is used to group measurements of certain physical quantities or environmental conditions, including sound, temperature, pressure, vibration, motion, or pollution, at various locations and ranges. In WSNs, several protocols address the issue of routing. Sensor nodes in WSN usually have limited energy resources and storage capacities. Therefore, the issue of energy usage in sensors and protocols is very important. This paper analyzes and compares the quality of service (QoS) performances of three important routing protocols of the mobile ad-hoc network (MANET) including Ad-hoc on-demand distance vector (AODV), dynamic source routing (DSR), and destination sequenced distance vector (DSDV), in a smart building case study. The QoS evaluation metrics include residual energy of nodes, instant throughput (IT), average throughput (AT), packet delivery ratio (PDR), packet loss ratio (PLR), and route discovery latency (RDL) based on IEEE 802.15.4 MAC protocol standard. The simulation is carried out using NS2, and the WSN has 16 fixed and 4 mobility nodes with different speeds and paths. The simulation results illustrate that average throughput in AODV is 1.985118 (kbps), however, the figures for DSR and DSDV are 1.977780 and 1.720700 (kbps), respectively. PDR, also, in DSR stands at 1.0, but the figures for AODV and DSDV are lower with the range of 0.999572 and 0.997930, respectively. Overall, The DSR protocol provides a better performance compared to AODV and DSDV routing protocols in terms of PLR and PDR. Also, AODV has better efficiency in RDL and AT compared to other assumed protocols.

Advances in electronic systems, wireless communication protocols, and intelligent devices allowed the development of networks of mobile devices such as cars, drones, and robots. The field of mobile ad hoc networks (MANETs) comprises networks where the mobility of the devices is one of the fundamental elements that characterise these networks. However, the node’s mobility leads to constant changes in the network’s topology, representing a challenge to routing protocols designed for MANETs. Although there is effort from researchers to tackle the intricacies of routing protocols in MANETs, there is still room for improvement as new applications with challenging specifications continue to arise. This research enriches the existing theoretical perspective by presenting an innovative method for optimising the routing performance of the ad hoc on-demand distance vector (AODV) protocol. Grounded on multi-objective metaheuristics, we aim to improve AODV’s routing recovery performance concerning routing delay, energy consumption, packet loss ratio, and route load metrics. To gauge the quality of our contribution, we compare its performance to the standard AODV, a mono-objective optimised AODV, and four other well-known routing protocols with different routing approaches. The results indicate that the proposed solution was superior to the original AODV with average improvements of 56.0%, 59.3%, 48.1% and 0.7% on route load, routing delay, packet loss ratio and energy consumption, respectively. It also presented competitive results compared to other routing protocols.

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.

In Mobile Ad-Hoc Networks (MANET), the increasing demand for multimedia application is more challenging and the existing routing protocols are not adequate owing to the complex design requirements of Quality of Service (QoS) routing. This paper proposes a stateless position-based solution for QoS routing issues and offers an efficient end-to-end communication guarantee. The proposed Stateless QoS (SQoS) routing protocol is based on adaptive compass greedy routing to determine a qualified path which satisfies the QoS requirements and the void handling scheme overcomes the local maximum issue. In addition, the SQoS routing utilises the node overhearing capacity to obtain the link quality measurement to provide a guarantee for efficient end-to-end transmission through the identification of high-quality links for multimedia streams. The performance of the proposed SQoS routing protocol is compared with existing QoS-GPSR. Finally, the performance evaluation proves that the SQoS routing protocols outperform the existing protocols.

Introduction: The future of healthcare systems relies on faster communication between sensors and smart devices, which can assist in taking decisions for betterment of patients. The responsiveness of wireless health care system in case of medical urgencies is crucial factor for survival of patient’s life. The routing protocol of infrastructure less based are playing key role in sending the information in such medical related emergencies. Therefore, it is important to study and identify the best routing protocol in wireless healthcare based system using Mobile Ad-hoc networks (MANETS). Methods: MANET routing protocols such as Ad-hoc On Demand Vector (AODV), Secure AODV (SAODV) and Hybrid Wireless Mesh Protocol (HWMP) through their routing environment are simulated through this research study. It is essential to highlight the effect of various attacks affecting the routing methodology of these protocols. Since Distributed Denial of Service (DDoS) attack is popularly talked about and is most vulnerable attack present in MANET environment, so this research study analyses AODV, SAODV and HWMP under DDoS attacks through various simulation parameters. Results: In this research study, most suitable routing protocols to handle DDoS attacks are simulated and estimated in terms of delay and packet delivery ratio in the scenario of changing nodes. This aids in providing implications to enhance existing protocols and alleviate the consequences of DDoS investigation by such attacks. Discussion: For ensuring the optimized routing, privacy and security of patient’s data during transmission in healthcare sector, MANET could be used as one of the important technology combined with IoT. For dealing with end to end data transmission of patient's sensitive data, MANET protocol plays a vital role in sending the information securely. Conclusion: The performance of AODV, SAODV and HWMP (Hybrid Wireless Mesh Protocol) are compared and tabularized which are the most popularly utilized protocols in healthcare environment. The simulation results shows that the HWMP out performed than AODV and SAODV routing protocol, in terms of evaluation metrics namely end-to-end delay and Packet Delivery Ratio (PDR) and could be considered as much less vulnerable against DDoS attacks prevailing in wireless healthcare sector using MANET.

Today, the use of Mobile Ad Hoc Network (MANET) is becoming increasingly popular due to its flexibility and ease of use wherever and whenever. MANET is able to adapt to many applications, such as disaster management and military operations. The MANET routing protocol consists of two types, namely Proactive Routing Protocols and On Demand Routing Protocols. Destination-Sequence Distance-Vector (DSDV) is an example of a protocol that includes Proactive Routing Protocols. Meanwhile, Ad Hoc on-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) are examples of protocols that include On Demand Routing Protocols or Reactive Routing Protocols. Because routing protocols greatly affect MANET performance significantly, it is necessary to study the performance of routing protocols. This paper discusses the performance comparison of MANET routing protocol based on RandomWaypoint mobility model. The experiment was carried out by applying the MANET routing protocol to the RandomWaypoint mobility model. Routing protocols used are AODV, DSDV and DSR. The simulation is done using NS-2 software. The total of nodes used in simulations is 100, 150, 200 and 250 nodes respectively. Length of simulation time 900 s. The simulation area take place in urban residential areas. Performance evaluation is performed on variable packet delivery ratio (PDR), throughput, average end to end delay, packet loss and normalized routing load (NRL).

This paper conduct a comprehensive simulation study on the behavior of TCP-friendly Rate Control (TFRC) protocol over Ad-Hoc On Demand Vector (AODV) routing protocol and Dynamic Source Routing (DSR) protocol. The aim are first, to measure the performance of TFRC in terms of throughput, delay and jitter. The second objective is to identify which Mobile Ad-Hoc Network (MANET) routing protocols work well with TFRC. We conduct the experiment by sending multimedia streaming traffic carried by TFRC over AODV and DSR respectively. Random-Waypoint mobility model is used for both experiments. Results obtained shows that in average TFRC over AODV has more throughput and less delay as compared with TFRC over DSR. However, in terms of jitter, TFRC over DSR gives better result.

Networks are being used in various areas and the demand of users nowadays has motivated the emergence of the Mobile Ad Hoc Network (MANET). MANET is a dynamic network without fixed infrastructure due to their wireless nature and can be deployed as multi-hop packet networks. It is a wireless network and has dynamic topology due to its node mobility. There are two types of MANET, homogeneous and heterogeneous MANET. An architecture has been designed in previous work to model these two types of MANET. Three scenarios have been defined from this architecture: scenario I (communication entirely within MANET, homogeneous MANET), scenario II (communication between MANET and wireless LAN, heterogeneous MANET) and scenario III (communication between MANET with wireless LAN and wired LAN, heterogeneous MANET). MANET has its own routing protocols which can compromised with frequent route exchange, dynamic topology, bandwidth constraint and multi-hop routing. Ad hoc On Demand Distance Vector (AODV) is one of the routing protocols in MANET. The aim of this research is to assess the effects of different packet size with the implementation of AODV routing protocols in homogeneous and heterogeneous MANET through the simulation method. The three scenarios above have been developed in the OMNeT++ network simulator. The results achieved from the test have been evaluated using the metrics assigned, throughput and packet delivery ratio (PDR). The tests show that the increase of throughput and PDR performance was parallel with the increase of packet size. From the test also, we can conclude that the performance due to the packet size effect in homogeneous MANET is better than in heterogeneous MANET.

In recent years, with the increasing popularity of Internet technology and the advent of the 5G communication era, the applications related to mobile IoT have exploded, and wireless Ad Hoc network has received more and more attention. In traditional Ad Hoc networks, data are often transmitted between nodes in the form of "multi-hops", and the transmission range and available energy of nodes are limited. Thus, in Ad Hoc networks, a reliable and energy-efficient data transmission protocol is needed. In this paper, we studied the existing multipath routing protocols and proposed a multiple performances based routing protocol E <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> LR, ( residual Energy, Energy consumption, Loop, Routing protocol ) for the shortcomings of Ad Hoc networks. This protocol has the following improvements to the existing multi-path routing protocols: (1) In the route discovery process, depending on the energy level of the nodes, the nodes make three different decisions on the received RREQ packets: discard, randomly delayed forwarding, and immediate forwarding, to filter out the nodes with lower energy and thus improve the network performance. (2) When selecting available paths, try to select nodes whose lifetime are close to each other. This can reduce the number of interruptions in the transmission path and improve the stability of the transmission path during data transmission. (3) When transmitting data, multiple paths stored in the source node are recycled to transmit data, thus balancing the node energy. Simulation results show that the E2LR routing protocol can effectively reduce the frequency of route initiation, shorten the data transmission delay, reduce the packet loss rate in the network compared with existing multipath routing protocols.