Blockchain for Managing Heterogeneous Internet of Things: A Perspective Architecture IoT has the potential to transform the way we think about information and communication technology. IoT has been studied extensively across many disciplines such as the networking, communication, security, business, and management communities. However, many unsolved challenges, especially in managing heterogeneous IoTs, remain to be discussed. Recent studies propose using blockchain, an emerging technology that enables decentralized coordination, to address inherent challenges in IoT. This article presents a preliminary study on an architecture that implements blockchain in managing heterogeneous IoT systems. We start by pointing out the limitations of prior IoT systems and the difficulties of integrating IoT and blockchain. Then we outline an architecture to manage a largescale heterogeneous IoT system. Our main goal is to stimulate further effort and crossdisciplinary collaboration by providing guidance and reference for future studies.

The Best of Both Worlds: A General Architecture for Data Management in Blockchainenabled InternetofThings The rapid proliferation of InternetofThings (IoT) devices has brought great challenges of data management, i.e., storing, retrieving and manipulating a large volume of IoT data. Conventional IoT systems rely on centralized architectures to manage IoT data, hence suffering from limited scalability, lack of transparency, and single point of failure issues. As such, we employ blockchain as a distributed ledger to support the decentralized approach of data management in IoT systems, where IoT data are stored in the deployed blockchain for further utilization, e.g., retrieve and audit. A general architecture combining blockchain and IoT systems is presented. Nevertheless, as the resource constraints of IoT devices may still exist during the process of data transmissions from IoT devices to the blockchain network, we propose a case study of a learningassisted resource allocation method to support intelligent data management. The numerical results show that the proposed scheme achieves superior performance compared with baseline solutions.