SCALABILITY ANALYSIS OF BLOCK CHAIN BASED SYSTEMS

Abstract

In recent years, block-chain technologies have gained massive momentum application domains. Block-chain is a decentralized data management technology which is speculated to be a disruptive technology that can have a drastic impact on people s lives as the Internet did. As different block-chain platforms are emerging rapidly, a firm understanding of the offerings by the adopted platform for the underlying technology along with its performance analysis is both important and challenging. Many organizations have shown interest in adopting the block-chain technology in their core systems, but scalability becomes a main concern in existing block-chain platforms. The block-chain application is stepping from its inception to full maturity and establishing itself as a part ofthe internet offuture (such as in the Internet ofThings), thus scalability of the technical challenges while having billions of devices installed worldwide with the passage over time. In this work, a comprehensive overview is presented ofa major and a popular block-chain platform, known as the Hyperledger-Fabric. The work proposes a prototype while using Docker containers as the experimental setup for deploying Hyperledger-Fabric nodes and chain-code. The work also evaluates performance ofthe Hyperledger-Fabric based block chain technologies in-terms of system scalability while considering different and scenarios. Performance evaluation can help in identifying system bottlenecks that can be further utilized to develop better solutions or optimize existing ones. A methodology is presented for evaluating performance of the block-chain platform. While using this methodology, performance analysis is done along with presenting the obtained results. The experimental results are based on varying numbers of transactions and number of nodes which reflects a detailed study of the Hyperledger-Fabric platform that may also help Hyperledger-Fabric foundation to further improve the performance oftheir platform. The experiments mainly consist oftwo cases. In Case#l, the transactions are performed by only a single node within the block-chain group ofnodes depicting a low load overthe block-chain network. In Case# I, nodes are varied from 3 to 25 nodes and the selected node performs up to 2000 transactions. Whereas in Case#2, we consider a worst scenario in which all the nodes are performing transactions on the network. For Case#2, nodes are varied from 3 to 13 nodes and transactions up to 1000. While evaluating performance, two performance parameters, namely Consensus Time and Ledger Size, mainly assessed while executing the experiments. For Case#l, over 25 nodes and while having 2000 transactions, it is observed that Ledger Size consumes a disk space of 5.3 MB and for that it takes 80.18 Minutes to complete the execution of all transactions. For Case#2, over 13 nodes and while having 1000 transactions, the Ledger Size consumes 57001.9 MB of disk space and takes 270.06 Minutes to complete the execution of all transaction.