Dynamic NFT exchanges in a blockchain environment using graph algorithms

Abstract

This thesis introduces Barterplace, a decentralized non-fungible token (NFT) barter system that integrates graph theory and blockchain technology to enable trustless, multi-party swaps. Unlike traditional NFT marketplaces that focus on direct buying and selling, Barterplace represents trade intents as a directed graph and employs Depth-First Search (DFS) for cycle detection, ensuring seamless and automated trade execution. The system is implemented on the Ethereum blockchain, leveraging smart contracts for security and transparency, while the InterPlanetary File System (IPFS) provides decentralized storage for NFT metadata. By facilitating swap cycles, Barterplace enhances NFT liquidity, increasing the likelihood of asset exchanges while eliminating intermediaries, reducing fees, and ensuring fair transactions. To improve efficiency and scalability, future optimizations such as off-chain computation and gas-efficient smart contract design are proposed. Experimental evaluations confirm the feasibility of this approach, demonstrating Barterplace’s potential to redefine digital asset trading in the Web3 ecosystem.