# Conceptual Framework for Future WSN-MAC Protocol to Achieve Energy Consumption Enhancement
## 3 State-of-the-Art Approaches for MAC-Protocols Optimization
### Game Theory-Based Approaches  
Game theory has been used for the goal of MAC scheduling for nearly a decade. For example, [39] proposed the simplified game-theoretic MAC (G-MAC) protocol for tuning the contention window based on the game theory model assigned to each node, with various actions, such as transmitting, listening, and sleeping, representing player 1. On the other side, player 2, which represents the remaining n-1 nodes, can select one of three actions: transmitting (which can be divided into successful or failed), listening, or sleeping. The goal is to enable a cooperative game by considering the energy as a utility function for minimization. The authors of this work provided an analytical model that can be used to obtain the optimal sleep probability equilibrium to guarantee convergence.  
The game theory energy-efficient MAC protocol, which was named energy-efficient TDMA (G-ETDMA) based on game theory for intra-cluster WSNs, was proposed in [40] and mainly depends on a game theory approach to reduce node energy consumption. On the other hand, a study by [41] found that the sender node did not send any data until the receiver's beacon signal was received. Therefore, data are routed on multiple paths in the data collection network because each sender receives a beacon signal from several nodes. An optimization framework is proposed to reduce energy waste for the most power-hungry network nodes in this context. Studies conducted by [42] allow adjustable system parameters to be set to achieve a fair equilibrium point that minimizes system latency and energy consumption by two times. As an illustration, this formulation was applied to six recent wireless sensor network (WSN) MAC protocols. Research by [43] proposed the use of multilayer nodes with distributed MAC, which is referred to as Distributed-MAC (DS-MAC), where the listening time of the nodes is controlled based on the neighboring communication. Game theory optimization helps address route loss constraints while selecting a route towards the base stations (BS).  
Table 2 lists a summary of game theory-based approaches that have been proposed for enhancing the performance of the MAC protocol for WSN.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference Paper** & **Approach** & **Type** & **Contribution** & **Results** \\ \hline \multirow{4}{*}{[37]} & \multirow{4}{*}{TSCH MAC} & & Presenting a centralized mechanism to schedule & \multirow{4}{*}{Outperforms previous analogous systems in terms of performance} \\  & & & TSCH time-slots with & & \\  & & & the optimal usage of resources & & \\ \hline \multirow{4}{*}{[38]} & \multirow{4}{*}{DSME-GTSs} & & Beacon slot collision & \multirow{4}{*}{Minimizes the number of time-slots used while maximizing the usage of available available} \\  & & & problem based on & \\ \cline{1-1}  & & & proposing a & \\ \cline{1-1}  & & non-conflicting beacon scheduling mechanism & & \\ \cline{1-1}  & & using association order & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference Paper** & **Approach** & **Type** & **Contribution** & **Results** \\ \hline \multirow{4}{*}{[39]} & Simplified game-theoretic MAC & \multirow{4}{*}{Asynch-CSMA} & Tuning the contention & The throughput of the system increases, the delay and packet-loss-rate are reduced, while maintaining relatively low energy consumption \\  & & & theory model assigned to & \\ \cline{1-1}  & & & each node & \\ \cline{1-1}  & & & consumption & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Game theory-based MAC approaches.