# Game theory-based Routing for Wireless Sensor Networks: A Comparative Survey
## 3 Game Theory-Based Routing Protocols in WSNs
### Routing Protocols Based on Evolutionary Games
#### 3.3.1 Game Theoretic Energy Balanced (GTEB) Routing Protocol
The strategy set \(S\) contains two elements, \(S=\left\{T,\overline{T}\right\}\), where T presents the data transmission of a node and \(\overline{T}\) presents no data transmission of a node. We do not further elaborate the methods to determine the pay-off calculation and Nash equilibrium that were obtained by the authors of [40], as our focus in this section of the paper is EGT. In Figure 6, a sender (\(S\)) forwards a packet to one of the subregions based on the EGT. \(R_{1}\), \(R_{2}\), \(\ldots\), \(R_{K}\) are subregions in the figure and \(R_{2}\) is the subregion selected using EGT. Within that region, a forwarding node is selected using CGT. The ratio of the number of delivered packets and the total number of generated packets is defined as packet delivery ratio in GTEB. If any sensor node fails to function properly, owing to energy depletion, the time taken until that event occurs is considered to be the network lifetime. The energy consumption per packet is defined as the average energy required for a packet to be successfully transmitted. GTEB was compared with real-time load distribution [69] and reserve path adaptive routing [70]. Compared to these protocols, the GTEB increased the network lifetime by approximately 33-129%. The rate of packet arrival was 1-14 packets per second in the simulation scenario in [40]. The intelligent spreading of traffic over wide regions through energy balanced forwarding process helped to increase the network lifetime in this protocol. The GTEB also reduced redundant transmission of the data packet through the game-theoretic approach, which eventually led to the reduction of energy consumption by up to 40 percent when compared to the other examined protocols. The packet delivery ratio was also higher in GTEB than the state-of-the-art protocols. Technical strengths:  
* Creates an energy balance and increases network lifetime significantly;
* Intelligent method to evenly distribute network traffic in a WSN. * Technical weaknesses:  
Figure 6: Subregion and node selection. * Sensor nodes are capable of reporting a nearby event to the destination on a periodic manner. If the destination is far away, this may lead to energy wastage;
* The protocol is more energy efficient when there are more nodes in a subregion. If there is only one node in a subregion, the data packet is to be transmitted directly to the destination. This is a serious flaw in the protocol, as this may lead to energy wastage;
* The network lifetime was the most prioritized routing metric for GTEB. Unfortunately, the authors did not compare GTEB with a sufficient number of protocols for this metric. It was compared only to the probabilistic forwarding method and that does not prove the superiority of GTEB over the state-of-the-art protocols. Applications:
* Applicable for energy-efficient geographical routing. Possible future improvement:
* Mathematical ambiguity can be removed from the protocol. In one case, K was denoted as a set of subregions in the network, but later K was introduced as a set of strategies, which was ambiguous.