A Mobile Ad Hoc Network (MANET) is an autonomous ad hoc wireless network that consists of many nodes, in which the nodes dynamically move so that the topology changes [1
]. MANET can communicate without centralized administration and is supported by wireless communication technologies such as WiFi, ZigBee, and WiMAX [2
]. MANET is generally used in places where a permanent infrastructure cannot be formed, such as disaster areas, battlefields, cars, military formations, ships, and aircraft intended to form temporary networks, so that the devices can be free both in and out of network coverage [3
]. Nodes in MANET in the form of communication devices are laptops, smartphones, and sensors. Their performance characteristics include dynamic topology and limited bandwidth, battery life, processing power, and storage capacity [6
]. The MANET simulation’s mobility model is divided into four categories: random models, models with temporal dependency, models with spatial dependence, and models with geographic restrictions [7
]. In this research, we used mobile modeling of moving nodes to avoid obstacles [8
], randomly [9
], in a limited simulation space on an ad hoc network.
The challenges of routing and security should be identified properly before deploying a MANET [10
]. The routing protocols play an important role in ensuring reliable communication among nodes in MANET [11
]. Routing is the process of transmitting packets from one network to another [12
]. Routing protocols in MANET must also be able to adjust the changes in the changing network topology. Therefore, a reliable routing protocol is needed with a low overhead in managing MANET, which can be seen from the Quality of Service (QoS) parameters such as Packet Delivery Ratio (PDR), throughput, packet loss, and delay [13
Several kinds of research have been conducted on reactive and proactive routing protocols on MANET. Among the results, studies show that the Ad Hoc On-demand Distance Vector (AODV) protocol has good throughput and end-to-end delay [5
], good energy consumption [16
], is suitable for application to moving nodes [17
], and has a good performance with increased speed for average end-to-end metrics [18
]. In contrast, the Optimized Link State Routing (OLSR) protocol is a proactive routing protocol developed based on the link state routing algorithm and is an optimal technique to extract information relating to the network topology [19
]. OLSR has the advantage of the delay being relatively low because it is a routing table. Compared with AODV, OLSR has better throughput, packet loss, and delay [6
]. OLSR has the advantage of average end-to-end delays, where the delay is less than other protocols [20
], better in terms of dense and highly dynamic topology [21
], and suitable for delay-sensitive applications [22
Previous research using the AODV protocol has not examined the effect of the performance’s changing parameters. However, in an ad hoc network environment such as MANET, the route discovery and route maintenance process is the key concept that deals with topology changes [23
]. Other than that, routing parameter values such as Active Route Timeout (ART) also play an important role in providing stable routing in a dynamic environment, where the network topology changes continuously and quickly [23
]. Research on the performance of the default parameters has been carried out by [23
]. Studies [25
] examined the effects of route maintenance and HELLO messages parameters. The route maintenance parameters are Active Route Timeout (ART) and delete period constant (n), while HELLO messages include HELLO_INTERVAL and ALLOWED_HELLO_LOST. Both studies show that the default parameters of the AODV protocol do not always produce the best results. The best results from the two studies were generated by reducing the parameter values, such as changing the ART value to 2.5 (default value: 2.5) and the HELLO_INTERVAL value to 0.5 (default value: 1). The change in these parameters’ values can cause an increase or decrease in the routing overhead and PDR. If the parameter value changes too far from the default value, the resulting performance is strange.
Other studies of ART parameters on AODV protocols were conducted by [23
], and research on Delete Period Constant (DPC) parameters was conducted by [24
]. All three studies also show that the default values of AODV parameters do not always have optimal performance. The optimal MANET performance is produced with ART values smaller than the default values, the values of which are between 0.5 and 3. As well as DPC parameters, the best performance is produced by values of 6 for Variable Bitrate (VBR) traffic and 3 for Constant Bitrate (CBR) traffic.
This study examined the effect of route request parameters such as RREQ_RETRIES and MAX_RREQ_TIMOUT on the AODV protocol, which was then compared with the default AODV performance OLSR routing protocols. The performance metrics used in performance measurement were Packet Delivery Ratio (PDR), throughput, delay, packet loss, energy consumption, and routing overhead. Network performances are good if they have a high throughput and packet delivery ratio (PDR) and low packet loss and delay [6
The comparison between the AODV and OLSR routing protocols with the test scenarios used in this research shows that the OLSR protocol is only superior in terms of the delay metrics, whereas for other metrics, such as PDR, throughput, packet loss, energy consumption, and routing overhead, the AODV protocol is superior. This is due to the high overhead of the OLSR routing protocol because it is continuously sending routing packets at a certain interval [6
]. OLSR has a lower delay than the AODV protocol due to its nature, which stores routing information on each node, so packets are sent faster [6
]. However, this causes OLSR to send many routing packets to control the network topology, causing energy consumption and routing overhead to be very high. This impacts network congestion so that the OLSR routing protocol has a low PDR and throughput. The number of routing packages on the AODV and OLSR routing protocols, based on observation times, is shown in Table 4
. In this part of the discussion, we refer to the results at the velocity of 20 m/s, which shows the best results. Other speeds show poor performance, which may be due to the lack of movement of nodes to form new routes after the path is interrupted, resulting in many packets being dropped, thus increasing routing packets because the destination node is not immediately within the range of the source node, which causes a decrease in PDR and throughput.
The results presented in Table 5
indicate that the number of routing packets on the AODV protocol does not change after reaching 41. This is due to there being no route changes at 10–200 s. The AODV routing protocol does not send routing packets. Unlike the OLSR routing protocol, although there is no route change on the network, the protocol will still send routing packets for a certain period of time to maintain the routing tables on each node, so the number of generated routing packages increases. Many of these routing packets cause the network traffic to become dense, causing a decrease in the OLSR routing protocols’ performance in terms of PDR, throughput, packet loss, delay, and energy consumption.
The effect of the parameters RREQ_RETRIES and MAX_RREQ_TIMEOUT on the AODV protocol shows that reducing the value of RREQ_RETRIES and MAX_RREQ_TIMEOUT improves the routing performance, as seen from PDR, throughput, and packet loss. This is because by reducing, in particular, the MAX_RREQ_TIMEOUT value, the route search can be made faster when a route change occurs. A route change occurs once in the test scenario to send a packet from node 0 to node 3. The first route that is formed directly connects node 0 to node 3, which is one hop away. This route lasts until node 0 propagates the RRER message due to node 3, moving away from node 0 and approaching node 2, causing node 3 to be outside the node’s reach.
In the movement of node 3, previously formed routes cannot be used, so that packets cannot be sent. The route is reformed after node 3 is within reach of node 2. In the formation of the new route, it is necessary to resend the RREQ. The length of time for an RREQ packet depends on the RREQ_RETRIES and MAX_RREQ_TIMEOUT values.
When there is a delay between sending RRER packets and new RREQ packets, node 0 tries to improve the route by sending RREQ packets, but because the destination of node 3 is still beyond the reach of all member nodes, the routing table is not formed, resulting in a delay in sending RREQ packets because the RREQ packet delivery limit has been reached according to the RREQ_RETRIES and MAX_RREQ_TIMEOUT values. Table 5
shows the time at which the routing table was formed at node 0, according to the RREQ_RETRIES and MAX_RREQ_TIMEOUT values.
shows that reducing RREQ_RETRIES and MAX_RREQ_TIMEOUT values can speed up the delivery of RREQ packets to speed up route formation. The faster the route is formed, the faster data packets can be sent to increase PDR, throughout, and packet loss.
In the case of delay, the effects of the RREQ_RETRIES and MAX_RREQ_TIMEOUT parameters do not have a pattern. This is because of the generated delay value from when the packet was sent after the route was formed. The average energy consumption shows that an increase in the value of MAX_RREQ_TIMEOUT reduces energy consumption. This is because when there is a higher MAX_RREQ_TIMEOUT value, there is a long delay in packet delivery caused by route changes. Hence, the number of sent packets decreases. The lowest average consumption is generated by the MAX_RREQ_TIMEOUT value of 11 s. It decreases energy consumption by 0.399%. The routing overhead shows that changes of MAX_RREQ_TIMEOUT do not affect performance. This is because MAX_RREQ_TIMEOUT only delays sending RREQ packets and does not reduce the number of RREQ packets sent. What affects routing overhead is the value of RREQ_RETRIES, which can reduce the number of packets sent and increase the number of packets that can be sent. The optimal RREQ_RETRIES parameter obtained from this research is 2, while the optimal MAX_RREQ_RETRIES value is 5 s. The results are in good agreement with studies conducted by [25
], which show that the default parameter values of the AODV protocol do not always produce the best results.
The results of this study show that the OLSR protocol has a shorter delay than the AODV protocol. The OLSR protocol has a delay of 0.02 s compared with that of the AODV protocol of 0.156 s, while, for other performance metrics, the AODV protocol is better than OLSR at every speed variation. OLSR has 11% lower PDR, 8% lower throughput, 46% higher packet loss, 49% higher energy consumption, and 94% higher routing overhead. This result shows that the AODV protocol can adapt better to topology change than the OLSR protocol.
In the AODV routing algorithm, by reducing the combination value of RREQ_RETRIES, MAX_RREQ_TIMEOUT to (2, 10 s) and (3, 5 s), this can improve protocol performance. The two combinations resulted 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%, a decrease in energy consumption of 19%, a decrease in routing overhead of 4.8%, and an increase in PDR of 4.8%. From these results, it can be concluded that reducing the combined value of RREQ_RETRIES and MAX_RREQ_TIMEOUT can improve the AODV protocol’s performance; the AODV protocol performs better than OLSR due to the low number of generated routing packets.
Regarding variations in node movement speed, performance increases as the speed increases and decreases as the node speed decreases. A speed of 20 m/s has the best performance, while 5 m/s has the worst performance. These results apply to all performance metrics, including PDR, throughput, packet loss, delay, and energy consumption. These results indicate that node movement speed affects the formation of new routes after the path is cut off. These results may not be valid under different scenarios, so further research is needed.