# Proof of Optimum (PoO): Consensus Model Based on Fairness and Efficiency in Blockchain
## 8 Conclusions and Future Work  
As a result, it can be said that while PoW-based blockchain systems follow a consensus mechanism based on hardware power, they are useful in terms of security. However, they are very disadvantageous in terms of efficiency and decentralization. Moreover, they are not very healthy in terms of energy consumption. Mining operations with expensive ASIC mining devices are making the work of other low-level hardware participants in the blockchain system increasingly difficult. This negatively affects decentralization. PoO has been proposed as a solution to the efficiency and decentralization problems described here [4; 22; 24]. PoO offers several unique advantages over traditional PoW algorithms. The use of genetic algorithms and optimization techniques to provide efficiency and energy savings shows that PoO makes data processing processes faster and more effective. In this way, blockchain networks can transact faster and use resources more efficiently. PoW-based blockchain systems execute their transactions in the system at the expense of wasting large quantities of computer resources. As the calculation techniques of optimization algorithms have a more stable structure than PoW, a model that can produce more efficient results in terms of block creation time and decentralization is proposed. Experiments confirm that the PoO algorithm can create blocks in a decentralized way. It can be observed that artificial intelligence-supported blockchain networks will meet demands as they continue to progress in the future. In future studies, it is planned that different optimization approaches can help blockchain studies by diversifying the proposed PoO via optimization algorithms. As optimization and blockchain networks powered by artificial intelligence will continue to grow in the foreseeable future, the proposed PoO consensus mechanism could help reduce the need for more powerful hardware for mining [11; 24]. The future potential of PoO is quite broad. This model can be used to solve more complex problems by integrating with different optimization algorithms. For example, more creative and effective solutions can be obtained by combining artificial intelligence techniques or complex mathematical models with PoO other than genetic algorithms. This indicates that PoO has great potential, especially in areas such as large-scale data analysis or predictive models. Additionally, applications of PoO in different industries should be evaluated. PoO's optimization capabilities can be used to achieve better results in areas such as finance, healthcare and supply chain management. In this way, it can be shown that PoO can be used not only to speed up data processing but also to improve workflows in different industries. The Proof of Optimization (PoO) algorithm has given promising results in experiments on numerical data. In the experiments, it has been observed that the PoO algorithm provides faster block generation than the Proof of Work (PoW) and Proof of Stake (PoS) algorithms. In addition, it has been determined that the PoO algorithm is more resistant to the factors that cause imbalance in the number of block proposals and provides a fair block distribution. The test results show that the block generation time of the PoO consensus model varies between 2 s according to the dataset solution with the least cities (ulysses22) and 60 s according to the dataset solution with the most cities (gr666). Additionally, as a result of experimental analyses, it was determined that decentralization, which is the percentage of block creation among miners in the blockchain, reached a more stable value and the fairness index rose above 0.90 on average  
In future studies, by using other optimization algorithms and optimization problems, various evaluations can be made to experimentally study their effects on consensus models. The study can be considered as a method of distributed optimization. Solutions can be diversified by changing the optimization problem or algorithm.