A Novel Algorithm for AODV to Enhance the Efficiency and Performance of the MANET

Deepika J, Dr. Rangaiah L Research scholar, Department of ECE, RajaRajeswari College of Engineering, Bangalore, under VTU, Belgavi, India. Professor & Head,Department of ECE, RajaRajeswari College of Engineering, Bangalore,560074,India. Article History: Received:11 January 2021; Accepted: 27 February 2021; Published online: 5 April 2021 Abstract:Network security and performance are significant topics discussed in academic and Industrial research. Every application depends on the performance and efficiency of the network. Routing protocols and mechanisms play an essential role. AODV routing protocol is considered standard in many aspects, primarily due to the increasing efficiency requirements in various applications. There are different approaches in the literature trying to improve the performance. Some studies considered multiple parameters such as density and mobility of the data nodes. This research study evaluates the two critical parameters that contribute to the overall efficiency and performance of the network – throughput and route resilience. A new version of enhanced AODV is proposed in this paper that uses an iterative approach to check for each parameter and adjust the values accordingly until the required threshold level of efficiency is reached. The solution is explained in different categories pertaining to each network parameter. The proposed algorithm is simulated on a network tool, and the results show that the enhanced version of the routing protocol is promising and can be further extended to introduce new modes for higher efficiency and lower power consumption.

increase in density resulted in a decrease of the delay in the new enhanced method when compared to AODV. This research study and results are more appropriate to an application with more node density. The density of the nodes and the region we are not considered in the current research study, but the existing studies show that the parameters such as packet delivery and network throughput can cause significant influence on the efficiency of the system [1]. AODV routing protocol is not restricted to Ad Hoc networks and wireless sensor networks but can also be easily extended to IoT applications. A common approach used by the researchers in this field is the comparison of AODV routing protocol with other protocols for a specific application. Packet delivery rate and drop rate are considered to be effective measures of comparing the efficiency. Dynamic routing protocols have been proposed in the literature for addressing specific problems such as the mobility of the nodes. The results of the research studies have also been compared with other protocols such as OLSR, and it was found that AODV has better performance [7]. RREP and RREQ are the packets sent in the routing protocol, which increases the traffic when there are too many data packets in the network, and it is overloaded. The functionality and performance of the system deteriorate. The research literature provides proof on using various metrics, but the common feature found in many studies relates to the two critical parameters -route resilience and throughput. This research study proposes an enhanced AODV design with throughput, route resilience, and power consumption parameters.

Design
The design of the enhanced network is divided into two parameters -Throughput and route resilience. Message rate, communication rate, and data rate metrics are used to measure these parameters. The first step is to check if the routes are available for data transmission. Data values in the round table represent the different nodes and the path to be taken by the data packets. The information from the routing table may or may not be available depending on the design of the network [8]. If the route is not available in the table, the process of discovery is initiated in which the possible mathematical calculations for discovering the new route are initialized. If the routes are available in the table, the next step is to check for the communication range.
A small set of test packets are sent through the communication channel, and the throughput is recorded. A preferred value of throughput is compared with the threshold value. The necessary condition is to have the throughput greater than the threshold value so that the communication and the data packets last for the entire session, as shown in figure 1. If the throughput is less than the threshold, then the communication range is increased until the value increases beyond the threshold. This data is compared with the standards for data rate in which noiseless channels are used for improving efficiency. The data rate is calculated for the initial stages when the required starting time is determined. The throughput is calculated after determining the data rate and compared with the threshold level, as shown in figure 2. The signal levels are increased for enhanced communication only after checking the data parameters, the highlight of the improved algorithm. The route Discovery process should not be advertised to all the nodes, especially when there are specific adjustments to be made with the communication range and message rate [9]. If the route Discovery process is advertised, the control packet data is increased, and the network is flooded with additional data packets. The route discovery should always result in updating the values in the routing table In a slightly different enhancement of the existing algorithm, the first step is to check if the roots are available in the routing table and then proceed with the reachability of the node. If the node is not reachable, an alternative route is checked, as shown in figure 3.
If no alternative is available, then the route discovery process is initiated. This enhanced version of the flowchart provides an additional requirement of checking if an alternative route is available, which makes the algorithm efficient because the route discovery process is delayed unless absolutely necessary [

Fig.3. Route Resilience using a new algorithm 4. Results
The proposed routing protocol based on AODV is simulated on the OMNeT++ tool. Various libraries are available on the tool, and the C++ framework is used for designing and coding. This software tool is available free of cost for non-commercial purposes and academic projects. The total number of packets sent in the simulation are 1662.The results are discussed as follows.
Default   The communication range was also checked using simulation, and the message size of 1000B was used, and the data packets sent and received are compared. The throughput values were found to be increasing for a higher communication range measured from <1m to 500m. The graph that compares the packet sent and received for different data rates ranging from 1Mbps to 10Mbps is plotted.
The chart clearly shows that the data packets received are increasing steadily as the data rates are increased ( figure 8).
The network is iterative in nature and found to perform efficiently. AODV is efficient only for smaller networks but the enhanced network is found to have higher efficiency for large networks with many nodes.

DATA RATE
Packet sent packet received

Route Resilience
Route resilience is the concept used to enhance the efficiency by increasing the throughput. The approach used for this is to check for different routes. The proposed enhanced algorithm checks for alternative routes and the simulation shows that this approach is efficient in improving the throughput. The enhanced algorithm has resulted in a throughput value of 0.43719 compared to default network with 0.19614.

Conclusion
This research paper proposes a new enhancement to the standard network and simulates the results by varying various parameters. This research study simulated the existing AODV routing protocol with specific parameters considered and enhanced the method using an iterative approach by adjusting various parameters to increase the efficiency and throughput. Throughput and route resilience are analyzed in this study. Route resilience parameter has shown significant improvement in throughput. Power consumption parameter is considered the future scope of the study. It is possible to achieve low power operations on MANETs and wireless sensor networks.