Abstract

Many researchers challenge the possibility of using blockchain and smart contracts to disrupt the Internet of Things (IoT) architecture because of their security and decentralization guarantees. However, the state-of-the-art blockchain architecture is not scalable enough to satisfy the requirements of massive data traffics in the IoT environment. The main reason for this issue is one needs to choose the consensus trade-off between either coping with a high throughput or a high number of nodes. Consequently, this issue prevents the applicability of blockchain for IoT use cases. In this paper, we propose a scalable two-tiered hierarchical blockchain architecture for IoT. The first tier is a Core Engine, which is based on a Practical Byzantine Fault Tolerance (PBFT) consensus to cope with a high throughput, that supervises the underlying subordinate engines (sub-engines) as its second tier. This second tier comprises of the Payment, Compute, and Storage Engine, respectively. We can deploy multiple instances of these sub-engines as many as we need and as local as possible near to the IoT domains, where IoT devices reside, to cope with a high number of nodes. Furthermore, to further extend the scalability of the proposed architecture, we also provide additional scalability features on the Core Engine such as request aggregation, request prioritization, as well as sub-engine parallelism. We implement all of our engines and expose them to IoT applications through the Engine APIs. With these APIs, developers can build and run IoT applications in our architecture. Our evaluation results show that our proposed features on the Core Engine can indeed enhance the overall performance of our architecture. Moreover, based on our proof-of-concept IoT car rental application, we also show that the interoperability between sub-engines through the Core Engine is possible, even when the particular sub-engine is under sub-engine parallelism.

Highlights

  • In recent years, blockchain, the underlying technology behind the famous Bitcoin [1], gain tractions because of its ability to facilitate a working decentralized payment system without the need of a central third party

  • We enable parallelism in the Compute Engine such that only Notary 1 connects to the Ethereum Virtual Machine (EVM) in the Compute Engine 1

  • We begin by evaluating the Core Engine performance and assessing the integration of the sub-engines to the Core Engine by following the application logic of our Internet of Things (IoT) car rental application

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Summary

Introduction

Blockchain, the underlying technology behind the famous Bitcoin [1], gain tractions because of its ability to facilitate a working decentralized payment system without the need of a central third party. Adopters sometimes have to choose between one of those two extremes [5] Driven by these issues, we propose a scheme to scale the blockchain for IoT by combining multiple blockchain networks hierarchically. We propose a two-layer hierarchical multi-blockchain architecture to scale the blockchain implementations for IoT environments. We categorize the low-tiered blockchain networks by their respective IoT workflows, which are the Payment, the Compute, and the Storage Engine. We evaluate our architecture by conducting some experiments to measure the performance of the Core Engine, as well as measuring the latency across the sub-engines These experiments showcase the effectiveness of our request pool mechanism in increasing the throughput of the.

Blockchain Scalability Issues for IoT
Most of the IoT Devices Are Not Suitable to Run a Blockchain Node
Blockchain Design Cannot Process Transaction in Parallel
Blockchain Consensus Trade-Off
Proposed Architecture
Sub Engines
Payment Engine
Compute Engine
Storage Engine
Core Engine
Block Data Structure and Block Generation
Request Signaturing and Aggregation
Request Prioritization
Sub-Engine Parallelism
IoT Applications
Implementation
Evaluation
Static Request Pool Mechanism
Dynamic Request Pool Mechanism
Priority Mechanism
Cross Engines Evaluation
Related Work
Deployment Consideration
10. Conclusions
Full Text
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