## 1 Introduction
Danish company Maersk, a specialist in maritime freight and port terminal services, uses the TradeLens blockchain platform to improve transparency and interoperability in its logistics operations. The world's largest consumer goods company Unilever is using blockchain to provide traceability for raw materials such as palm oil. Amazon is combining its managed blockchain with IoT devices to track shipments in real time. Walmart is using blockchain technology to provide traceability for food products. This is only a partial list of examples. The reference architecture for distributed ledger technologies includes the consensus layer. This layer manages the consensus between nodes in the network and ensures that the ledger state is agreed upon by all nodes. It includes consensus protocols that are used to establish and maintain consensus and ensure network security, accuracy, and tamperproofing of the ledger. Consensus can significantly affect the performance and security of a blockchain system. To date, a wide range of consensus protocols with different concepts and properties have been developed, including for blockchain-based IoT networks [4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16]. However, at the same time, designing and developing optimized consensus protocols for specific scenarios and use cases is usually a labor-intensive and error-prone task, since choices must be made between conflicting requirements and there is a high degree of uncertainty. Most new protocols are variations of existing well-known consensus protocols. At the same time, existing implementations often cannot be reused for their implementation. And, there is a need for their complete reimplementation. This leads to potential new errors and difficulties in applying existing verification results. In this regard, in practical applications and scenarios, such as for blockchain-based IoT networks, developing a new suitable optimal consensus protocol or choosing one from a variety of existing ones is an important task. A promising modern approach for developing new protocols is the design of modular and composable consensuses. For example, in [17], [PERSON] et al. (2024) presented a flexible framework that allows for the detailed analysis and redesign of existing BFT protocols, and the fairly easy generation of new BFT protocols. The structure of the framework is hierarchical and consists of three levels. All three levels are extensible and allow for innovation. Any level can be modified or expanded to theoretically cover all BFT protocols, known and unknown. In [PERSON] et al. (2025) proposed a new programming model for implementing consensus protocols using replicated data types (RDT). The composability of PRDTs allows for the design of consensus protocols by composing basic consensus blocks and/or simpler protocols, facilitating the construction and verification of consensus protocols. The core components of consensus protocols can be designed as independent PRDTs. These components can then be combined to create complete consensus protocols. Individual components can be modified to adapt existing protocols. To select optimal consensus protocols from a variety of existing protocols, a suitable approach is to use multi-criteria decision making (MCDM) methods. There are works devoted to the application of such methods in the field of distributed ledger and blockchain technologies, mainly for choosing a blockchain platform, but also for choosing a consensus protocol [6; 19; 20; 21]. To date, many studies have been conducted on the integration of distributed ledger technologies and the Internet of Things, as well as the application of MCDM methods to problems associated with their joint use. These studies provide a solid basis for the development of practical tools aimed at supporting researchers and practitioners. However, such developments have not yet been undertaken to date. This paper initiates research in this direction with the aim of developing a system for selecting optimal consensus protocols for IoT networks.