# Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks
## 2 Related Work
Researchers in [18] tried to solve the energy conservation problem but they made many assumptions in their approaches like nodes from clusters should have a lot of information about their neighbor, also they ignored the selfishness of the nodes too. The selection/election of CH in the cluster is a very important task. Appropriate CH election is an essential consideration and, as mentioned earlier, location and connectivity are two of the most important parameters for such selection. Other techniques do exist in the literature, like in ref. [19] a fuzzy logic technique was used, considering neighbor nodes and residual energy parameters. In ref. [20], the trajectory-based clustering method for CH selection was introduced and in ref. [21], relative density parameter was used to improve LEACH. GT has been increasingly used in WSNs for a variety of issues, like efficient energy usage, more control over power transmission, data collection, and communication security. More specifically, GT has been very successful in the design schemes of WSNs. Normally, the nodes in WSNs act selfishly by conserving their residual energy by denying the receiving information from associates. This mostly happens in the multi-hop network during transmission. To get the optimum values for energy efficiency it the noncooperative game theoretic approach was used, like [22] where authors used the same approach for the election of the CHs in clustering. A node calculates the optimal probability by itself and declares itself as a CH or not, depending upon the maximization of payoff. GT together with the concept of the hierarchical topology is used in some algorithms. In ref. [23], authors have developed a game-theoretic scheme considering residual energy and average energy loss for maximizing payoff from CH selection. Similarly, in ref. [24] coalitional GT was adopted to determine the most efficient route in a group, considering the power consumption. In other works such as [25], routing in WSNs was done using Bayesian game, where Harsanyi transformation was used to create a static game of complete but imperfect information. A topology control algorithm in [26], based on the ordinal potential game, was proposed by designing a payoff function that considers two parameters only, which are network connectivity and the energy balance of nodes. In ref. [27], evolutionary game theory (EGT) was found to be affected by the frequency of the competing strategies in the population in the communication networks. It was noticed that the authors in [28] considered an evolutionary game approach for duty cycle and fuzzy logic for routing, but with only two parameters--residual energy and distance. While on another hand, double time Nash equilibrium was counted for suitable CH selection in [29] but they considered only parameter residual energy. An evolutionary game model \"Game theory based Energy Efficient Clustering routing protocol (GEEC)\" [30] was proposed to extend the network lifetime by achieving the energy exhaust equilibrium. The nodes were divided into two categories of candidates for CH or cluster member (CM). A game was designed to illustrate the possibilities for both categories for being CHs. Some incentives, in the form of profits and penalties, were designed to push the nodes toward their willingness for being CHs. The work is well-presented and all the possible aspects associated with the game processing are presented. Moreover, the proposed mechanism was compared with LEACH and LEACH-C. The results claim that GEEC gave better results than the experimented protocols. In another article [31], the evolutionary game was applied to calculate the traffic amount among different regions in the network. The network clusters were further divided into subproblems. The work inherited the key characteristics of GT like distributed decision, dynamic network, and resource usage preferences. The area associated with each sender node was segmented into various subregions.