## 4 Taxonomy of MAC Protocols Based on Their Use of WuR Technology
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name of** & **Description** & **Special Feature** & **Potential Drawback** \\ \hline \multirow{4}{*}{**S-MAC [25]**} & & Good energy conserving properties with & \\  & & an ability to make trade-offs between & Scalability issues are not addressed. \\  & & energy and latency according to & Network topology is considered constant \\  & & traffic conditions. The protocol has & with constant number of nodes. \\  & & been implemented efficiently in & \\  & & hardware at real-world scenarios. & \\ \hline \multirow{4}{*}{**V-MAC [46]**} & & VMAC is embedded in Body QoS to make & \\  & & it radio-agnostic, so that it can control & \\  & & and schedule wireless resources without & \\  & & knowledge of the implementation details & Energy efficiency is not considered at all. \\  & & of the underlying MAC protocol. & Evaluation of QoS parameters is given more \\  & & BodyQ6s adopts an asymmetric architecture, & importance than that of the energy concerns. \\  & & in which most processing is done at the & \\  & & resourceful aggregator while less processing & \\  & & is done at the resource limited sensor nodes. & \\ \hline \multirow{4}{*}{**DQBAN-MAC [47]**} & & High QoS support with limited & Global time synchronization is \\  & & protocol overhead. Less computational & a limiting factor. Power hungry \\  & & complexity and easy implementation. & due to extended operation of \\
**DQBAN-MAC [47]** & Body Area & Novel integration of fuzzy rule & cross-layer optimization. Fuzzy logic \\  & & Network MAC & scheduling along with TDMA-based & will become a burden for the sensor \\  & & approach renders a performance & nodes in case of dynamic \\  & & oriented cross-layer optimized MAC & data-load variations. \\ \hline \multirow{4}{*}{**R-MAC [48]**} & & Avoidance of overbearing, frequent & \\  & & commutation between sleep and wake & \\  & & up modes, and data collisions are & Not very energy efficient in low data \\  & & Access & good results of this novel approach. & rate application. Aimed at high data rate \\  & & Control Protocol & R-MAC protocol also adjusts the duration of & application in large scale networks \\  & & the sleep and active periods according to the & \\  & & traffic load in order to avoid data collisions. & \\ \hline \multirow{4}{*}{**UB-MAC [49]**} & & Urgency-based & Critical nodes’ packet transmissions are & The proposed protocol is only \\  & & MAC Protocol & prioritized over non critical nodes & evaluated mathematically. Network may \\  & & packet transmissions. & fail for different network topology and \\  & & & number of nodes in a network is limited \\ \hline \multirow{4}{*}{**EEE-MAC [50]**} & & Algorithm is good at preserving network & \\  & & topology and connectivity while introducing & \\  & & or reducing extra nodes. Smaller rate of & The protocol is not analysed for QoS parameters. \\  & & detection in energy consumption in higher & It is stated that QoS may hinder the energy \\  & & data load conditions. Energy efficiency is & efficiency for smaller networks \\  & & good compared to S-MAC and B-MAC & \\ \hline \multirow{4}{*}{**FE-MAC [51]**} & & High network lifetime with energy efficiency & \\  & & and load balance. Routing capability of the & Resource utilization is exhaustive. \\  & & network layer is also embedded in & Requires a relatively large memory \\  & & MAC protocol & the protocol. Highly scalable and & and high computational power. \\  & & energy-efficient with more number of nodes & \\ \hline \multirow{4}{*}{**QL-MAC [52]**} & & High data throughput is achieved. & Extremely high energy consumption. \\  & & Support dynamic payload in variable & No mechanism to ensure QoS parameters \\  & & MAC protocol & network conditions. Computational complexity & in the protocol. No hardware implementation \\  & & is minimal & is done. \\ \hline \multirow{4}{*}{**RL-MAC [53]**} & & Reinforcement & QoS aware design. A total of 55\% power & Complex implementation of reinforcement \\  & & learning-based & savings is achieved in a star & learning algorithm to control the duty-cycle. \\ \cline{1-1}  & & MAC protocol & topology network. & Requires large resources to accumulate \\ \cline{1-1} \end{tabular}
\end{table}