## 4 Conclusions  
The Internet of Things is one of the important application areas of distributed ledger and blockchain technologies. Distributed ledger technologies can provide effective ways to solve the problems of traditional IoT applications. An important component of the reference architecture of distributed ledger technologies is the consensus layer. This layer manages the consensus between network nodes and ensures the agreement of the ledger state by all nodes, as well as ensures network security, accuracy, and security of the ledger. Consensus can significantly affect the performance and security of the blockchain system. To date, a wide range of consensus protocols with different concepts and properties have been developed, including for blockchain-based IoT networks. Therefore, choosing the most suitable consensus protocol for a particular distributed ledger system, in particular, for the IoT blockchain, is an important task. However, at the same time, it is a complex task, since the choice has to be made between conflicting requirements and there is a high degree of uncertainty. In this paper, the first steps were made in this direction with the aim of developing a system for the selection of optimal consensus protocols for blockchain-based IoT networks. This work was carried out to develop a conceptual model of the selection system, consisting of several successive stages:  
1. Formalization of the problem as a multi-criteria decision-making problem.
2. Formation of a set of alternatives (consensus protocols).
3. Formation of a set of evaluation criteria.
4. Selection of the optimal methods of multi-criteria decision analysis.
5. Software implementation of the selection system and testing.  
The proposed approach can serve as a basis for future research, and the next step is to move from the concept to practical implementation. To achieve this goal, it is intended to create a software implementation of the system for selecting optimal consensus protocols, and its subsequent testing in various use cases. It will then be necessary to explore ways to solve a number of problems and limitations in its further application. It should be taken into account that the developed system cannot completely replace expert analysis. It cannot exclude possible erroneous recommendations. This is due to the fact that the algorithms embedded in the system may not correspond to the analyzed problem. Or, the initial data of the system user may be initially erroneous. In addition, the system databases containing information on the protocols, criteria, and methods may become outdated over time. It is also necessary to take into account the increase in complexity with the increase in the number of alternatives and evaluation criteria considered. In the future, regular data updates, system maintenance, solving of the issues of scaling, and maintainability of the system are necessary.  
Conceptualization, R.O. and Y.S.; methodology, N.T. and D.S.; formal analysis, N.T. and D.S.; investigation, R.O. and Y.S.; resources, K.U. and B.Y.; data curation, N.T. and K.U.; writing--original draft preparation, R.O. and B.Y.; writing--review and editing, R.O. and B.Y.; visualization, R.O.; supervision, D.S.; project administration, Y.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant number AP23487259.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.