Decentralized Finance (DeFi) has become a transformative force in the financial sector, using blockchain technology to create open, permissionless financial services. Its total value locked (TVL) grew from $675 million in 2020 to $180 billion in 2021, before stabilizing at $40-50 billion in 2023. This research examines DeFi infrastructure, applications, and governance mechanisms; analyzes challenges limiting adoption; and identifies trends shaping its evolution. Through analysis of literature, reports, and market data, this study examines DeFi’s technical foundations, application scenarios, governance structures, and development challenges. Results indicate DeFi has established robust foundations supporting diverse ecosystems but faces barriers in technical (scalability, security), regulatory (compliance, legal uncertainty), and market dimensions. Future evolution may be characterized by four trends: integration with traditional finance, cross-chain interoperability, balancing privacy with regulatory compliance, and institutionalization with maturing financial engineering. These findings contribute to literature on blockchain-based financial systems and provide guidance for practitioners, regulators, and researchers.
Nikola Todorović, Marko Vještica, Nenad Todorović, Vladimir Dimitrieski · 5 authors
Due to strong competition and rapidly shifting market conditions, it is becoming harder for Small and Medium-sized Enterprises (SMEs) to achieve business success. To deal with rising challenges, SMEs form Virtual Organizations (VOs) and seize business opportunities jointly. In this paper, we present an outline of a novel methodological approach that promotes trustworthy collaborative production execution within a non-hierarchical VO. Furthermore, we propose using Distributed Ledger Technology (DLT) platforms and smart contracts to facilitate VO integration. The approach is based on the MultiProLan Domain-Specific Modeling Language (DSML) extended with concepts required to allow process designers to (i) model collaborative production processes while preserving the confidentiality of private enterprise data and (ii) configure what data should be shared between participants during the collaborative production execution. Designed process models are used to automatically generate smart contracts by following the Model-Driven (MD) principles. Finally, generated smart contracts are stored in a DLT network and used to distribute production data between VO participants and monitor production execution in near real-time. The application of our methodological approach is demonstrated by showcasing the use of the Collaborative Extension of MultiProLan (CE-MultiProLan) modeling language and its concepts for modeling collaborative production processes.
In the emerging world of IoT applications, machines are going to be at the endpoints of the Internet engaging in complex Machine to Machine (M2M) communications. Be it a personal assistant (softbot)making an appointment with a doctor or an autonomous car filling fuel or charging at a refueling station, in the future, it is going to be M2M communications without human intervention. In such a scenario, robust and secure technology is essential to record every M2M transactions. This paper makes use of blockchain, a distributed ledger technology for intelligent transportation systems. It is proposed that blockchain networks such as Ethereum have the foundations to record and satisfy the transaction that has happened between the machines. A permissioned Ethereum blockchain – the smart contract –is used for recording each every transaction that come off between the car and electric station. An algorithm is proposed to recharge the autonomous electric vehicles as a case study.