Advancing Scalability, Efficiency, and Storage Optimization in Blockchain for Mobile Internet of Things (mIoT) Applications

Abstract

The increasing adoption of blockchain technology in mobile Internet of Things (mIoT) networks requires the development of blockchain systems that are efficient, scalable, and optimized for resource utilization. While several studies have attempted to address these challenges, comprehensive solutions that adapt to the inherent mobility of mIoT systems are still lacking. This Ph.D. thesis investigates three innovative methods to advance the current blockchain model for mIoT systems. First, a novel k-dimensional spatiotemporal, multidimensional, graph-based blockchain structure is introduced to address network partitioning issues caused by the mobility of IoT devices. This unique structure effectively manages blockchain nodes as they move between cell areas, resulting in smaller independent peer-to-peer subnetworks, each with its own blockchain copy. Experimental results demonstrate improved scalability and efficiency, with logarithmic growth as the blockchain size increases. Furthermore, the longest chain length is reduced by over 99.99% compared to traditional chain-based structures, making blockchain operations such as block appending or management more efficient. Building upon the multidimensional blockchain foundation, the next stage of this research involves developing an efficient merging algorithm for graph-based or multidimensional blockchains in mIoT networks. This algorithm addresses the challenge of merging partitioned blockchains that contain similar or identical blocks, which often require significant time and computational resources during the merging process. By leveraging depth-first search and Merkle tree techniques, the merging algorithm minimizes the time and computational resources spent on identical blocks, resulting in a 72% reduction in merging time compared to algorithms that do not handle block similarity. Lastly, considering the limited storage capacity of mIoT systems, this thesis presents a novel Collective Signing-Based Blockchain Storage Optimization (CSBSO) model aimed at minimizing storage overhead in resource-constrained mIoT systems. The model utilizes the existing Collective Signing (CoSi) protocol to reduce storage requirements and leverages a multidimensional blockchain structure for efficient block management and retrieval. The storage optimization approach identifies and prunes the most irrelevant blocks based on the CoSi protocol. Evaluations using real-world datasets, such as the Ethereum Classic Blockchain and Facebook users datasets, demonstrate that the CSBSO model outperforms state-of-the-art storage optimization models, achieving approximately 92% storage space savings. These results underscore the potential of CoSi-based storage optimization in effectively reducing blockchain storage overhead in resource-limited applications.