MapChain-D: A Distributed Blockchain for IIoT Data Storage and Communications

With the rapid growth of Industrial Internet of Things (IIoT) devices, managing an extensive volume of IIoT data becomes a significant challenge. While the conventional cloud storage approaches with centralized data centers suffer from high latency for large-scale IIoT data storage due to increased communication and latency overheads, distributed storage frameworks, such as blockchains, have become promising solutions. In this article, we design and analyze a dual-blockchain framework for secure and scalable distributed data management in large-scale IIoT networks. The proposed framework, named MapChain-D, consists of a data chain that is mapped to an index chain to provide efficient data storage and lookup. MapChain-D is designed for practical IIoT applications with storage, latency, and communication constraints. Detailed data exchange protocols are presented for data insertion and retrieval operations in MapChain-D. Based on these, theoretical analyses are provided on the space, time, and communication complexities of MapChain-D compared with conventional single-chain frameworks with local and distributed data storage. We implement our MapChain-D prototype using open-source LoRaWAN communications with multiple Raspberry Pi and Arduino devices, Kademlia-based distributed hash table, and Ethereum-based blockchain with proof-of-authority consensus. Experimental results from our prototype show that MapChain-D is more suitable to be deployed on resource-constrained IIoT devices. We also highlight the scalability and flexibility of MapChain-D with different number of edge nodes in the system.

I. Introduction

The efficient storage and secure management of Industrial Internet of Things (IIoT) data is a significant challenge due to the explosive growth in wireless devices and large-scale low-latency communication networks [1]. The conventional approach is to store data in centralized cloud data centers, which may be located far away from the wireless devices resulting in increased latency and communication overheads [2]. An attractive solution to reduce latency is to design distributed data management frameworks that move communications, computations, and storage requirements closer to wireless devices at the network edge [1]. Blockchains are one of the most promising distributed data structures for secure data management in large-scale networks with edge computing systems [3], [4], [5], such as vehicular networks [6], [7], [8], social media networks [9], energy trading networks [10], health-care networks [11], and logistics networks [12]. This is because blockchains can provide secure tamper-proof data management with a decentralized structure that does not require a trusted central controller [4], [13]. Furthermore, activities such as retrieving and modifying blockchain data stored in edge nodes are traceable and accountable using smart contracts to maximize data security and integrity [13].