Abstract: The main focus of the article is on operating systems, cloud computing and command shells, which have been actively developing for several decades and are already part of the life of both an ordinary user and a computer technology professional. These objects are considered as separate components of information technology, as well as their relationship and the results of this relationship. Operating systems in cloud servers perform a managerial role. To be more precise, they manage the resources of physical servers. Operating systems or OS in this case define several parameters. These parameters include how operating systems can use and manage memory and storage for various virtual machines. Command shells, in turn, are represented by an application that provides the user with a command-line interface in which he enters commands both individually and runs scripts consisting of a list of commands. Research methods include theoretical (classification, comparative analysis, literature analysis) and practical (experiment, modeling) approaches. This allows for a comprehensive analysis of the functioning of operating systems and command shells in cloud computing. The scientific novelty of our research is the creation of scripts to perform a particular task in the field of cloud computing on a specific operating system using the above-described command shells. Thus, the authors provided theoretical data on operating systems and command shells. The authors provided examples of scripts for Bash and Bourne Shell (sh) command shells for the Linux operating system and scripts for Command Prompt command shells (cmd.exe ) and Windows PowerShell for the Microsoft Windows operating system. As a result of the analysis of the scripts, a table was compiled with the impact of the operating system and the command shell on cloud computing. The analysis of the table allowed the authors to characterize the objects of research of this scientific work and draw appropriate conclusions.

Keywords: Hyperfine, Bourne Shell, Bash, Microsoft Windows, Linux, cloud infrastructure, cloud platforms, cloud computing, command shells, operating systems

Abstract: The article examines the working principle of the Proof of Performance (PoP) model, based on a consensus algorithm that supports horizontal sharding functions. The PoP model introduces changes to the traditional block structure used in Proof of Stake algorithms and Tendermint-based networks. Horizontal sharding allows transactions to be distributed among multiple nodes (shards), significantly increasing the network's throughput. The main goal of the study is to explore ways to enhance the efficiency and scalability of blockchain networks through dynamic transaction distribution and adaptive node management. An important aspect is the definition of parameters and adjustable characteristics of nodes, such as performance and reliability, to ensure even and fair load distribution within the network. This provides the system with the ability to adapt to changing load conditions. The study employs analytical and formal methods to describe the block structure, transaction distribution mechanism, and the system of penalties and rewards for shards. The research represents an innovative approach to managing blockchain networks, focusing on node performance. The PoP model with horizontal sharding provides higher throughput and scalability compared to traditional consensus algorithms. A system of dynamic load distribution and adaptive weight adjustment of nodes based on their performance is proposed, which contributes to the improvement of the network's efficiency and reliability. The results of the study demonstrate that the Proof of Performance model significantly increases transaction processing speed and overall blockchain network performance. Application examples confirm the model's effectiveness in various types of networks, such as DeFi platforms, supply chain management systems, and IoT networks. The PoP model encourages nodes to maintain high performance, ensuring fair load distribution and enhancing the overall network resilience.

Keywords: Blockchain, Load distribution, Performance, Horizontal sharding, Proof of Stake, Proof of Performance, Block, Shard, Consensus algorithm, Consensus model