An Efficient Approach for Merging Multidimensional Blockchains in Mobile IoT

Graph-based or multidimensional blockchains have been proposed to improve the scalability and efficiency of existing blockchain applications. However, when implemented in mobile Internet of Things (mIoT) networks, these blockchain systems can frequently split and merge and cause the merging algorithm to process a large number of similar blocks (a block is similar or identical when it exists once in multiple blockchains). The presence of similar blocks hinders the merging process, as it consumes time and computational resources to scan, validate, and potentially merge similar blocks. This paper presents an efficient approach for merging graph-based or multidimensional blockchains in mIoT networks by avoiding similar blocks and effectively detecting and merging new blocks that were created after the split. Our proposed merging algorithm employs depth-first search and Merkle tree techniques to minimize the time and computational resources spent on identical blocks. Finally, we evaluate the performance of our method in highly mobile networks and demonstrate that it can execute the merge with a more than 72% reduction in time in comparison to merging algorithms without block similarity handling.