# Empowering WBANs: Enhanced Energy Efficiency Through Cluster-Based Routing and Swarm Optimization
## 2 Related Work
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference No** & **Techniques Used** & **Advantages** & **Limitations** \\ \hline \multirow{3}{*}{[11]} & \multirow{3}{*}{HEESR} & Improves energy consumption & The approach only considers network \\  & & by 6\%, throughput by 92\%, & parameters when evaluating system \\  & & and security by 93\%. & performance. \\ \hline \multirow{3}{*}{[12]} & \multirow{3}{*}{DECR} & Significantly increases the & Different heuristics are required to \\  & & overall network lifespan. & consider more optimal solutions. \\ \hline \multirow{3}{*}{[13]} & \multirow{3}{*}{MT-MAC} & User-aware clustering & Network topology changes are not \\  & & technique. & adequately analysed for movement \\  & & & effects. \\ \hline \multirow{3}{*}{[14]} & \multirow{3}{*}{ERSCR} & This further decreases the & The limitation of low-power \\  & & energy consumption and leads & radiofrequency (RF) transmitters is the \\  & & to better first node dies in the & short transmission range. \\  & & network. & \\ \hline \multirow{3}{*}{[15]} & \multirow{3}{*}{DLQoS} & Less delay. & Increasing control costs on a large scale \\  & & & WBAN. \\ \hline \multirow{3}{*}{[16]} & \multirow{3}{*}{BBNs} & Minimal network latency. & Greater protocol complexity. \\ \hline \multirow{3}{*}{[17]} & \multirow{3}{*}{ALOC} & Reduces the number of & Changes in network design may \\  & & transmissions. & decrease cluster lifespan. \\ \hline \multirow{3}{*}{[18]} & \multirow{3}{*}{EHCRP} & The methodology conserves & Routing overhead may have an impact \\  & & energy. & on protocol performance. \\ \hline \multirow{3}{*}{[19]} & \multirow{3}{*}{ERRS} & Longer network life and & \multirow{3}{*}{Consideration of mobility and scalability} \\  & & improved stabilization periods & ultimately maximize & is necessary. \\  & & reliability. & \\ \hline \multirow{3}{*}{[21]} & \multirow{3}{*}{SDC} & Clustering that is & Inadequate examination of the CH \\  & & self-organized. & selection process. \\ \hline \multirow{3}{*}{[22]} & \multirow{3}{*}{E-HARP} & An energy harvesting & Incompatible with inter-WBAN \\  & & technique isused. & communication. \\ \hline \multirow{3}{*}{[23]} & \multirow{3}{*}{DHCO} & Extends the network’s & \multirow{3}{*}{It is only appropriate for WSN.} \\  & & lifetime. & \\ \hline \multirow{6}{*}{Proposed} & \multirow{6}{*}{ABBSOA-MSSOA} & - Enhanced energy efficiency & \multirow{6}{*}{- Increased computational complexity when deployed in large-scale or highly dynamic WBANs.} \\  & & in WBANs through optimized & \\ \cline{1-1}  & & clustering and routing. & - Dependency on precise parameter \\ \cline{1-1}  & & - Balances exploration & tuning for consistent optimization \\ \cline{1-1}  & & - Adaptive to varying WBAN & results. \\ \cline{1-1}  & & network topologies, ensuring & \\ \cline{1-1}  & & robust performance. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of existing protocols in WBANs. tees energy conservation by tailoring sensor activation to current network circumstances and reducing unnecessary transmissions. To attack energy efficiency from numerous aspects, this strategy varies from previous approaches by merging two swarm intelligence methodologies. The study covers many energy-efficient routing and clustering methods. MT-MAC, DHCO, and ALOC all have pros and cons. They also boost network durability, security, and energy efficiency. The relevant literature describes energy-efficient routing and clustering methods for WBANs. The HEESR approach prioritizes data security and throughput over scalability. With modified grey wolf optimization, [PERSON] et al. 's DECR improved cluster head selection. Still, more heuristics are needed to achieve the same level of success regarding network lifespan. Although they succeeded with latency and delivery ratio improvements, [PERSON] et al. encountered difficulties with mobility when they added a node transfer mechanism to the MT-MAC protocol. [PERSON] et al. 's body-to-body routing algorithm prioritized load-balancing and emergency data prioritisation.