Open Access

ARTICLE

A Lightweight Blockchain for IoT in Smart City (IoT-SmartChain)

Zakariae Dlimi^*, Abdellah Ezzati, Saïd Ben Alla

Hassan First University of Settat, Faculté Sciences et Technique, LAVETE, Settat, 26000, Morocco

* Corresponding Author: Zakariae Dlimi. Email:

(This article belongs to the Special Issue: Advances of AI and Blockchain technologies for Future Smart City)

Computers, Materials & Continua 2021, 69(2), 2687-2703. https://doi.org/10.32604/cmc.2021.018942

Received 27 March 2021; Accepted 27 April 2021; Issue published 21 July 2021

Abstract

The smart city is a technological framework that connects the city’s different components to create new opportunities. This connection is possible with the help of the Internet of Things (IoT), which provides a digital personality to physical objects. Some studies have proposed integrating Blockchain technology with IoT in different use cases as access, orchestration, or replicated storage layer. The majority of connected objects’ capacity limitation makes the use of Blockchain inadequate due to its redundancy and its conventional processing-intensive consensus like PoW. This paper addresses these challenges by proposing a NOVEL model of a lightweight Blockchain framework (IoT-SmartChain), with a lightweight consensus and a lightweight structure. The framework architecture presents a role hierarchy of connected objects according to their computational and storage capacity. This organization allows all things to be linked even indirectly via different interfaces and to benefit from the power of high-capacity objects such as Fog and Edge computing nodes. Data is validated and added to the blockchain ledger by running a lightweight consensus called Proof of Random Participation (PoRP), which reduces the blockchain nodes’ high computing power requirement. The TOPIC subscription-based data storage strategy called Assisted Selected Relevant Data in Local Ledger (ASRDLL) reduces the data size of a node’s local ledger and the entire network’s data size. This strategy is assisted by a centralized algorithm that optimizes the overall network size by adjusting the choice of TOPICS. The storage capacity, computational power, and energy consumption have been evaluated by a proof of concept implementation under NodeJS.

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