Mobility plays a significant role in the overall performance of WBAN as mobile nodes can produce different topology at different points of time, which may cause a deficiency in the overall performance of WBAN. Mobility models help us to identify the pattern that a node follows during its movement; hence, with the help of this, we can identify the upcoming location and make our WBAN more efficient with respect to delay, throughput, and packet delivery. In this section, we have discussed two different mobility models for WBAN, which will be evaluated later with different routing protocols.
2.3. Related Work
Fahim et al. [
17] presented an evaluation analysis for different routing protocols in MANET with different mobility models. The mobility models used were Random Way Point (RWM), Reference Point Group Mobility (RPGM), and Column Mobility Model (CMM), along with different routing protocols such as AODV, DSR, DYMO, and DSDV. This study provides us with the guidelines for choosing routing protocols for different mobility models in different scenarios and has also shown the impact of different routings on different QoS parameters. In [
18], performance analysis for MANET is performed with three different mobility models for on-demand and table-driven routing protocols. This study shows that on-demand routing performs well in terms of memory consumption as compared to table-driven routing protocols. This study only focused on two ad hoc routing protocols which makes it very limited to decide what protocol is best suited for which mobility model, and also, it does not cover the use and importance of sink nodes placement and its movement as well.
Dhananjay et al. [
19] reviewed different routing protocols for VANETs. According to this study, an increasing number of node size of routing tables for OLSR routing protocol increases which degrades its performance, and by increasing the number of nodes, AODV suffers the problem of route failure. Similarly, if we consider GPSR and CAR, it suffers the problem of packet loss with an increased number of nodes in VANET. This study has considered the packet loss and route failure as issues, but sink node exhaustion is not considered. Moreover, sink mobility is untouched. Atta et al. [
20] selected the clustering-based routing protocols for their evaluation with different mobility models. Different categories of position and non-position-based protocols were compared in this study and have concluded that position-based routing performs well as compared to non-position-based routing protocols. Different protocols such as DECA, DEMC, and DEMC-R were evaluated and were compared with MAR, GRC, and GRC-R with different mobility models. In [
21], the author compared the performance of different routing protocols, such as AODV, DSR, DSDV, AOMDV, etc., for FANET (Flying Ad Hoc Networks). Through the analysis, HWMP was found to be the best protocol suited for FANET with different mobility patterns, and OLSR is the second-best for the same. Even though these protocols perform well in terms of packet loss, overall delay, and throughput but sink node placement still needs improvement as it keeps on being exhausted very early with an increased number of nodes.
Kumar et al. [
22] evaluated the outcomes of three routing protocols, i.e., AODV, DSR, and OLSR, by Varying the number and velocity of nodes. The analysis shows that OLSR was better than DSR and AODV in terms of average end-to-end delay and throughput with the increasing number of nodes in the network. Saini and Nath [
23] evaluated AODV and DSR based on pause time and speed. The outcomes show, on the one hand, that AODV performs better than DSR when the speed of the node is low and the pause time is static. While the DSR has better results as compared to AODV as far as throughput and end-to-end delay are concerned. Timcenko [
24] has examined the performance of mobile ad hoc network (MANET) routing protocols concerning group and entity mobility models. The following three widely used routing protocols were studied and compared: DSR, AODV, and DSDV. Network simulator version two (NS2) and its tools have been used for animation, and an analysis of findings was used in the simulations.
The authors Barakovic et al. [
25] examine the performance of DSDV, AODV, and DDSR, routing protocols based on data analysis from NS2 simulations with various load and mobility scenarios. Routing protocols function similarly in low-load and low-mobility environments. DSR, on the other hand, outperforms AODV and DSDV protocols as mobility and load increase. The researchers Sharma et al. [
26] determine the qualities, weaknesses, and strengths of numerous mobility models that describe mobile nodes whose movements are independent of one another. More information about these models will aid researchers in selecting a mobility model to utilize in the simulation. The authors have compared these models using numerous performance measures such as PDR, E2E, normalized routing load, and missed packets to demonstrate how the mobility models were chosen to affect the performance results of the ad hoc protocols to be simulated.
The authors Nayak and Vathasavai [
27] aim to focus on the performance of two reactive routing protocols, DSR and AODV, by evaluating several random mobility models and utilizing NetSim Simulator to see if the protocol’s applicability can be improved. As a result, the authors examine the impact of communication protocols on the changeable topology of MANETs by measuring throughput, E2E delay, PDR, and routing overhead. Hossein and Rahim [
28] investigated a DTN scenario, the performance of replication-based DTN routing protocols such as Epidemic, Probabilistic Routing Protocol using History of Encounters and Transitivity (PRoPHET), MaxProp, Resource Allocation Protocol for Intentional DTN (RAPID), Binary Spray and Wait (B-SNW), and Spray and Focus (SNF) is investigated against varying numbers of mobile nodes for three mobility models: Random Walk (RW), Random Direction (RD Three measures were used to evaluate and analyze performance using the Opportunistic Network Environment (ONE) simulator: delivery probability, average latency, and overhead ratio. The researched DTN routing protocols, on average, perform better in the SPMB movement model than other movement models, according to simulation data.
In Delay Tolerant Networks, the authors Spaho et al. [
29] compare the performance of Epidemic, Spray, and Wait for routing protocols, as well as their counterparts with congestion control and Epidemic with TCP. Random waypoint (RWP), steady-state random waypoint (SSRWP), and Triana city map-based movement has been used for evaluation, which resulted in outperformance of SSRWP over Triana and RWP evaluation scenarios. With ten pause time values, the FCM, SCM, RWM, and HWM mobility models are developed by the researchers Abdullah et al. [
30] to examine the performance of AODV, OLSR, and GRP protocols. These models are based on MANET participants’ variable speeds and pause times. In order to compare the performance of mobility models, various node statistics such as data drop rate, average end-to-end delay, media access time, network load, retransmission attempts, and throughput are employed. The simulation findings indicated that in most circumstances, the OLSR protocol outperforms the other two routing protocols and that it is better suited to networks that demand low latency, retransmission attempts, and high throughput. The authors Jawandhiya and Asole [
31] have discussed the significance of efficiency considerations and looked at how different routing protocols compare in terms of performance. In terms of PDR, Jitter, E2E Delay, and throughput under various circumstances. Along with this, they researched the behavior of these routing protocols in-depth and compared their performance in various scenarios [
32]. The summary is described in
Table 1.
It is clear from the above table that various researchers have performed comparisons of different routing protocol’s performance, but none of the above have performed the same for WBAN. This work is focused on the performance analysis of routing for WBAN, which will contribute to better assistance in the healthcare sector.