Research Summary: SoK: Applying Blockchain Technology in Industrial Internet of Things

SoK: Applying Blockchain Technology in Industrial Internet of Things

Description:

Industrial Internet of Things (IIoT) platforms need to integrate blockchain technologies to overcome challenges such as poor interoperability, privacy, security, and resource constraints in addition to heterogeneous smart devices, networks, and data types.

TLDR

  • Traditional IIoT systems employ centralized cloud-based architectures that may be unsustainable for industries’ projected exponential growth.
  • The drawbacks of using a centralized architecture include having a single point of failure, massive data processing requirements, and lack user-access controls.
  • Decentralized architectures may address these shortcomings, however, integrating them requires addressing several challenges: standardization, interoperability, and scalability.
  • This study explores recent advances in tackling those shortcomings and examines several practical applications of blockchain architectures in IIoT platforms.
  • The author proposes three architectures for integration: IIoT-IIoT, IIoT-Blockchain, and Hybrid Approaches.

Core Research Question

What are the architectures that IIoT platforms need to integrate to sustain industrial advancement?

Citation

  • [1] G. Wang, “SoK: Applying Blockchain Technology in Industrial Internet of Things”, Cryptology ePrint Archive, 2021. [Online]. Available: https://eprint.iacr.org/2021/776.pdf. [Accessed Sept. 18, 2021]

Background

  • IIoT is a branch of the Internet of Things (IoT) that stems from the increasing prevalence of smart devices across industrial applications. At current rates of growth, there will be 75 billion IoT devices by 2025, with IIoT devices making up 17% of the total.
  • Since IIoT deals with massive amounts of data, the ubiquitous adoption of IoT devices will demand efficiency improvements. Current centralized solutions won’t be able to keep up with increasingly large and complex networks of IIoT devices.
  • Blockchain technologies may offset many of the traditional limitations of IIoT with decentralized mechanisms, immutability, and transparency.
  • Blockchain infrastructures can eliminate single points of failure and reduce overhead by distributing data processing [1].
  • Still, the scope of blockchain applications within the industrial sphere is relatively limited. Though integration presents considerable opportunities for advancement, no universal standards for integration currently exist.

Summary

Features and Challenges of IIoT

  • The primary function of IoT is connectivity. In industrial settings, IoT devices are Cyber-Physical Systems that link machines to control systems, interfacing physical operations with their cyber counterparts to reduce the need for human interference and allowing automation.
  • Most IIoT devices are lightweight nodes with resource constraints such as limited computing power, bandwidth, energy supply, memory, and storage.
  • IIoT devices often have unpredictable connections to one another due to device mobility, faulty wireless networks, and device standby settings.
  • Traditional IIoT platforms deploy centralized cloud-based infrastructures, which provide ample computing power and storage, yet when joined with IIoT technologies and devices they present significant drawbacks.
  • These include privacy and security vulnerabilities, access control issues, expenses and risks associated with third parties, and bottlenecking and scalability concerns.
  • IIoT platforms experience poor interoperability mainly due to their heterogeneous make-up. The uses of IIoT devices vary per application, as do network topologies and data types. Each industrial sector and organization may implement different protocols, making data and service sharing complex and inefficient.

Features, Benefits, and Challenges of Blockchain

  • Blockchain is a shared ledger that verifies and records transactions through decentralized technologies and distributed networks. All participating nodes within blockchain networks store identical copies of the ledger and maintain consistent timestamped records.
  • Data stored on the blockchain is immutable and tamper-resistant, as any alterations are reflected in successive blocks’ overturn. These qualities, coupled with blockchain’s transparency and traceability, make it a viable structure for business relations.
  • Blockchains generally apply asymmetric cryptography and digital signatures for security and privacy purposes.
  • Blockchain’s pseudo-anonymity provides a degree of user privacy, though privacy remains an open issue.
  • Blockchains are vulnerable to 51% attacks, partitioning attacks, and smart contract scripting exploits.
  • Scalability is an ongoing challenge. As the blockchain expands, performance diminishes and resource requirements increase.

Integration and Advantages of Blockchain and IIoT

  • As the number of IIoT devices on a network grows, the amount of data generated increases. Likewise, the demands on bandwidth and computational power also increase.
  • Consequently, centralized systems experience congestion and delay, resulting in expensive hardware solutions and steep maintenance overhead.
  • Using a blockchain’s decentralized structure as an overlay on existing IIoT frameworks can evenly distribute computational efforts among participants in a network.
  • Smart contracts stored on the blockchain serve as real-time auditors and may eliminate third-party actors in IIoT systems, thereby lowering expenses.
  • Blockchain’s composite layer acts as an interface that streamlines different data types and masks underlying heterogeneous layers. It connects the communication layer to industrial applications, bridging diverse mobile and industrial networks, enhancing interoperability, and facilitating reciprocal data exchange. Refer to Fig. 5.
  • Current industrial solutions employ lightweight IIoT devices to accelerate performance, yet this poses a growing risk to the industrial landscape. End-devices are subject to attacks since they cannot host robust security mechanisms and firmware updates are intermittent.
  • Integrating blockchain may enrich IIoT’s security systems through robust encryption primitives and multi-digital signature requirements. Moreover, blockchains are resistant to single points of failure attacks and provide a measure of fault tolerance.
  • Industrial applications typically employ consortium or private blockchains which enable smart contracts to regulate user access controls and data provenance. This improves privacy, security, and detection of unauthorized user access.
  • Omission of device authentication services potentially compromises IIoT operations.
  • Blockchain identification technologies can authenticate and monitor devices to assess and manage their integrity.

Challenges of Integration

  • IIoT devices have limited computing power, energy supply, and bandwidth capabilities. They cannot meet the requirements of blockchain mechanisms and sustain high levels of throughput.
  • The storage requirements of blockchain are too significant for lightweight nodes. However, devoid of the entire blockchain and its data, participating lightweight nodes cannot validate peer transactions.
  • Since industrial operations are time-sensitive, the latency introduced by consensus protocols may debilitate system performance and timestamping accuracy.

Method

The author employed a qualitative approach to explore architectures that IIoT platforms need to integrate to improve their current architectures. The researcher collected data through a comprehensive literature review consisting of 244 sources.

Results

While identifying integration challenges and potential solutions, the author provides some generalizations without necessarily connecting each problem to a solution and vice versa. Therefore, this summary only covers the issues and solutions that directly align.

Potential Solutions

  • The author proposes introducing structures similar to a blockchain that improve scalability and throughput and provide comparable services such as “decentralization and immutability” [1]. These include Directed Acyclic Graph, Tangle, and Greedy Heaviest-Observed Sub-Time.
  • On-chain storage may be reserved for critical data, whereas minute data may be stored off-chain and retrieved through distributed hash tables like Kademlia.
  • Latency can be improved by reducing transaction size and using powerful nodes such as edge devices to mitigate confirmation delays.

Discussion and Key Takeaways

Blockchain Storage and BaaS Platform

  • Blockchain communication requirements and massive data inhibit end-device performance and are too costly for on-chain storage solutions.
  • Decentralized blockchain storage run on cloud-based infrastructures can provide more efficient, secure, and cost-effective models for IIoT platforms as illustrated in Table IV.
  • Using Blockchain-as-a-Service (BaaS), industrial operations can integrate specific blockchain applications into existing cloud-based platforms with fewer complexities and investments. Essentially, this entails customizable blockchain capabilities to manage and store data with service providers that oversee blockchain operations. Table V. provides a list of various BaaS platforms.

Integration Approaches and Blockchain Selection

  • The author presents three models for blockchain integration: IIoT-IIoT, IIoT-Blockchain, and Hybrid Approaches. Table VII. provides a comparison of these approaches.
  • In the IIoT-IIoT model, blockchain has minimal interaction with IIoT and functions as an immutable archive, accounting for partial IIoT data and sustaining low latency levels, making it ideal for time-sensitive applications.
  • The IIoT-Blockchain model emphasizes the interconnectivity of blockchain and IIoT, recording all data via consensus mechanisms. This approach warrants more resources and values data as its greatest asset.
  • The Hybrid model secures partial data on the blockchain and requires a calculated design to capture critical data. Without heavy communication between IIoT and blockchain, it reduces burdens on constrained devices.

Implications and Follow-ups

Optimization on Performance

  • Industrial scenarios must sustain high levels of throughput for devices to function synchronously. However, existing solutions for blockchain integration increase throughput at the expense of scalability. Decreases in latency may also have adverse effects on scalability.
  • Most IIoT devices are resource-constrained, making direct integration impractical.
  • Integration solutions must accelerate scalability and throughput, lower latency, and accommodate the limitations of end-devices.

Scalability

  • Poor scalability interferes with the adoption of blockchain in IIoT networks.
  • Unstable wireless connections also contribute to scalability issues.
  • Areas of research that may surface potential solutions include sharding and side-chaining.

Security and Privacy

  • Blockchain and IIoT are predisposed to different vulnerabilities.
  • Smart contract scripting lacks standardization, making discrepancies and oversights exploitable.
  • IIoT wireless networks are susceptible to eavesdropping and Denial of Service attacks.
  • Privacy preservation is an open issue for blockchain-IIoT platforms. The author proposes “decentralized record-keeping that is completely obfuscated and anonymous by design” [1].

Editable Blockchain

  • Conventionally in a blockchain, all records should be stored by all nodes. However, some industrial data eventually becomes useless and can be deleted or transferred to secondary storage. Also, fraudulent data should be nullified.
  • Editability allows modification and deletion of irrelevant, incorrect, and generally undesirable data stored on the blockchain. However, there must be a compromise between editability and security of the system.

Edge Computing

  • IIoT devices frequently cannot meet the requirements posed by IIoT applications when blockchain is applied, specifically in the context of computation and networking. Their storage is limited, and there are also limits on their interoperability and authentication standards.
  • In edge computing, edge devices are placed close to edge servers. Edge servers are less powerful than cloud servers but have closer proximity to edge devices which in an ideal situation allows for minimization of latency and transmission delay.
  • Powerful gateways can also act as consensus nodes in the blockchain to resolve the storage and computing problems of lightweight devices.
  • This paper proposes a potential research direction in which blockchain technology is implemented on the IIoT edge and minimizes networking and computational overhead.

Standardization on Blockchain-Based IIoT

  • Lack of or inconsistency in standardization results in the inability to reach service agreements for integration processes.
  • The Institute of Electrical and Electronics Engineers (IEEE) and the International Standards Organization (ISO) have made attempted standardization efforts.
  • Blockchain standardization will help to redefine future technologies and assist both users and developers of blockchain.

Applicability

Industry 4.0

  • Total industrial automation can be realized through the convergence of IoT, Cyber-Physical Systems, and blockchain.
  • With their immutable services, decentralized systems, particularly blockchain, can enable secure, trustworthy, and cost-effective interactions among autonomous agents.
  • Quality of Service monitoring on the blockchain can improve latency through its updating requirements and coupled with smart contracts, it may actualize chaining in real-time.

Smart Manufacturing

  • Smart manufacturing predominantly relies on centralized infrastructures and third-party auditors, which pose considerable disadvantages: poor interoperability, increased overhead, and security vulnerabilities.
  • Interoperability may be improved through blockchain’s ability to meld disjointed IIoT systems into a distributed network.
  • Overhead can be lowered with smart contracts as real-time auditors.
  • Smart contracts can provide automated firmware updates to leverage security.
  • Through blockchain-enabled IIoT platforms, smart manufacturing could achieve advances like machine self-monitoring, self-diagnosis, and automatic maintenance requests as outlined in the Blockchain Platform for Industrial Internet of Things.

Smart Grid

  • Centralized Energy Management Systems (EMS) have been shown to be less efficient and secure for peer-to-peer (P2P) energy trading.
  • Decentralized blockchain EMS has potential for more efficient and trustworthy P2P large-scale energy trading, especially with regards to the security and privacy of energy exchange and transmission.
  • Decentralized EMS applying bi-level algorithms indicate more practical operations for renewable energy source distributed generators in microgrids.

Supply Chain

  • Blockchain may be implemented as a form of quality control in the supply chain. Its identification technologies translate physical assets to digital identities associated with immutable timestamps, providing traceability and tamper-resistant proofs.
  • A product can be traced from its source to the shelf to uphold food safety standards in the food industry.
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Hi @rlj -

You mentioned that centralized systems experience congestion and delay, and blockchain’s decentralized structure is supposed to make it faster because it distributes computational to different participants.

How does this hold? Isn’t it commonly held that blockchain is computationally intensive and much slower than other data transmissions on the internet?

This is just speaking from my personal experience. Blockchain transactions take as long as half an hour to process. I would be concerned if any IoT device I own updates its data with that kind of latency, let alone the cost of computation.

Thanks!

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@rlj thank you for posting this terrific addition to our scaling category. When we talked about this summary one-on-one you mentioned that IIoT + blockchain technologies had tremendous potential, to the point that the author describes it as being able to ignite a fourth industrial revolution. How come? How might these networked things improve industrial processes?

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@Twan I echo your concern about the latency built into consensus mechanisms. See also:

And:

However, with IIoT specifically, there seems to be a resistance to the “shift of mindset” necessary to flip constraints into opportunities. Note this passage:

This captures the point: Of course edge servers are less powerful than cloud servers. But when designed to have “closer proximity to edge devices” they can help conquer problematic latency.

This leaves me thinking that working with the benefits of decentralized, P2P structures is a “mindset” that conventional thinking hasn’t yet embraced.

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Hi @Twan, thanks for your question. To clarify that matter, distributing computational efforts reduces expenses associated with “installation and maintenance in centralized infrastructures” and “networking equipment” [1]. That is not to imply it would reduce latency, though you raise a key issue in this research. Poor scalability largely interferes with blockchain-IIoT integration. Traditional IIoT platforms and blockchain both face this challenge. However, the latency introduced by blockchain’s decentralized mechanisms is unacceptable by industrial standards, which require massive amounts of data to be processed in a timely manner. As noted by the author, “solving scalability in blockchain will serve as a huge advance toward creating a practical decentralized infrastructure for IIoT applications” [1]. I would have to agree with the concerns you express. In its current state, blockchain comes at the expense of suboptimal industrial performance and with considerable computational and networking overhead.

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On the bright side, innovations in blockchain computation efficiency come out gradually. It’s not standing still. Researchers and engineers are working hard to reduce energy consumption. Ethereum even promised to reduce energy consumption by 99 percent on Ethereum 2.0.
If it’s going faster every day, maybe we can get lucky, and see blockchain overcome this barricade in the future.

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Hi @rlj: Thanks for an excellent summary of a paper which reveals many of the contradictions presented by the history of IIoT, as well as the possibility of mitigating those contradictions with blockchain—if industry can bring itself to adopt the necessary new “mindset” around the issues at hand.

Here are a few key points that leapt out at me:

This highlights a key failing across most industries and OEMs: Attempting to achieve customer “lock-in” with core proprietary protocols and technologies rather than adopting common-sense standards and then differentiating products on top of those standards.

The assumption that all data is equally valuable, to be preserved forever, is simply in error. A huge percentage of industrial data can be collected and processed at the edge, acted upon appropriately, and then discarded.

The paper characterizes “edge” devices correctly…

…but it doesn’t say that if we adopted a fully networked, P2P, decentralized state of mind, the limited computing power, storage, etc. of IIoT devices might be seen as an opportunity not a constraint.

For example, the paper notes:

But then it goes on to say:

Why can’t these “robust encryption primitives” be implemented on edge devices themselves?

Finally, the paper makes an intriguing point:

This is a fascinating area. Can you say a little more about it?

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@GanouTeikun welcome to the forum! With a mechanical engineering background, I was thinking that this post may interest you.

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@Gearlad how does this overlap with some of the work you and @Sean1992076 have been working on? @rlombreglia mentions embedding primitives in IoT devices, can you talk about some of the work your lab has done with turning IoT into lightweight ETH nodes and routers – would that be a solution ot some of the issues he’s brought up?

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Having worked in this field, I had an experience that using blockchain for storing all the data is quite a terrible idea (from an implementational perspective). Instead signed Hash Tables can be the preferred way since we had like more than 50 GBs of data only from one industrial site per day. Imagine storing it as multiple copies stored on all participating nodes that too through consensus!

And for immutability of data (partial?), as long as at least one party can provide full copy of data along with the corresponding signed hash table from blockchain, we are good :slight_smile:

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@kanad really good to have you on the forum again! Can you tell us a little more about the challenges of combining IoT and the blockchain – do you agree with the article’s basic premises about the increasing complexity of the networks requiring some kind of decentralized structure? Or are there other solutions that might work temporarily (especially in an industrial environment)?

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First of all, I admit that I’m still a newbie in blockchain and I’m still familiarizing myself with IoT and blockchain and their implications in Industry 4.0.
I was having an interesting discussion with @Gearlad in my lab in the Mechanical Engineering department at National Taiwan University. Industry 4.0 is all about leveraging IIoT technologies to allow for cities to become smart cities and for factories to become smart factories. Let’s just say this: our lab plans to become a smart lab.

We collect all kinds of experimental data including temperature, pressure, size of material, ratio of different elements in an alloy, current (Ampere) density of materials, performance as an electrocatalyst for C02 reduction, so on and so forth. Currently, not all of the data that we collect is done with the help of machines, and some of it is based on human observation. Moreover, for the data we do collect, we store it on two mediums: Google drive and an external hard disk. An external drive is safer than Google drive in terms of privacy but nonetheless is still prone to damage and is less accessible than cloud storage. Unfortunately, Google is planning to shut down its unlimited storage plan for institutions and enterprises. What we need is a new form of data storage that is both secure and easily accessible, and blockchain is promising in overcoming these limitations.

Currently our lab has more traditional equipment that is not yet connected to the Internet. However, we have begun modernizing the lab with the application of AI and IoT. The purpose of this is to autonomously sort all of the data that we collect and to find different trends in this data. By using these trends we can predict the change in parameters such as size of ligaments, morphology structure, and electro-catalytic performance in porous metals. We use a Scanning Electron Microscope (SEM) to observe the morphology of porous metals; however, due to the limitation of the equipment, we need to adjust the focus of the images manually. Anothing thing worth mentioning is the facility is unable to generate mappings of elements on the porous metal, unless a better SEM machine is purchased (very expensive!). By applying IIoT, we have been planning to further upgrade our lab’s furnace so that it can monitor and control fluctuations in temperature more efficiently. In addition, automation can also increase safety as we’ve been relying on human observations to stop the furnace when the overshoot of the temperature in the furnace rises too high. Also, since we heat up materials in vacuum chambers, IoT may warn when the pressure of the chamber rises above the acceptable level. The examples above are also connected to the Industrial Control System (ICS) since we are aiming to create a system where all devices are able to do feedback control when some abnormalities arise.

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Thank you so much for this contribution! In the summary, it is mentioned that edge devices may be utilized to consolidate transactions so a node can validate without having to be onboard each IIoT device. I am not sure if the author made any suggestions how to get to this point of standardization without regulation or industry cooperation? There seems to be an assumption of a common goal driving the theoretical IIoT blockchain layer; but in reality, what would compel a private organization to join a non-government regulated public network as a means of monitoring their devices if they did not have at least SOME influence over that network layer?

While the proposed IIoT layer does sound useful in theory, has there been any indication that any private organizations have a desire to add a non-proprietary edge layer to their IoT devices, or has that notion mainly been coming out of the blockchain theoretical space?

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Great post, really enjoyed reading it.
I thought @rlombreglia replies were quite interesting about embracing constrains as opportunities.

Decentralized disjointed layers can help organize data for some type of central processing. First, you would have to characterize your industry/orgnization into nodes/layers and have extreme understand of how they communicate with one another. Local nodes can have set data standardization among the locale to improve scalability. Only using the distilled data from the points you reduce bottlenecks.

The ground level of one organization will most likely never look like another- so why even try to solve that problem? Differences are what makes organizations/sectors special; the overarching overlaps are where leaps and bounds will happen: getting product from A to B is ubiquitous. Though, I do not think a solution will make itself present until tested.

Showing decentralizing your business to align with the blockchain structure is where improvement using blockchain starts being obvious.

It makes sense to me if the benefit of the blockchain is to be decentralized, so why not decentralize your industry? This will probably be backwards for a lot of current industries but newer ones for example with AI- helping managing datasets as smaller pieces of a whole could possibly improve transparency.

An example that shows this is mentioned in the Smart Grid section about how centralized energy management systems (EMS) are less efficient than decentralized blockchain EMS.

The more decentralized the system the better a decentralized technology like blockchain benefits it.

I would like to learn more about this topic as it has huge implications, thanks for writing it!

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This was an exciting read which shines a light on the Industrial Internet of Things as one of the key components of Industry 4.0. I really love how this summary highlighted some of the issues and challenges of IIOT and this includes the heterogeneous nature of IIoT, the complexity of the network, the poor interoperability system, the massive data management, and the risk of being vulnerable to a single point of failure. There seems to be an assumption that the application of blockchain technology could help improve the efficiency of IIoT. I am not sure if the author answered the question on how Blockchain technology will solve the challenges of IIoT and thus, drive Industry 4.0.

Reading the article [1], the author opines that the decentralized nature of blockchain could eliminate a single point of failure, save operational costs, and enhance trustworthiness, and the immutability nature of Blockchain could make the data of IIOT difficult to be tampered with. However, we all know that Blockchain technology has a scalability issue, and also, the Storage issue, which is interconnected with the scalability issue because as the size of the chain grows, nodes require more and more resources, thus decreasing the system’s capacity scale. Is the trade off with integrating blockchain technology to IIoT really worth it?

I know there is a Current Use of Blockchain, the hyperledger Fabric, in the supply chain industry. for instance, Walmart used Hyperledger fabric to trace a batch of mangoes in 2.2 seconds, something that typically takes 7 days to do [2]. My last Question is thus, if Walmart were able to improve its supply chain efficiency with Blockchain, how, then, is latency a challenge blockchain needs to improve upon?

  • [1] G. Wang, “SoK: Applying Blockchain Technology in Industrial Internet of Things”, Cryptology ePrint Archive, 2021. [Online]. Available: https://eprint.iacr.org/2021/776.pdf . [Accessed Sept. 18, 2021]

  • [2] Tan B., Yan J., Chen S., Liu X. (2018) “The Impact of Blockchain on Food Supply Chain: The Case of Walmart”. In: Qiu M. (eds) Smart Blockchain. SmartBlock 2018. Lecture Notes in Computer Science, vol 11373. Springer, Cham. https://doi.org/10.1007/978-3-030-05764-0_18

3 Likes

This was an interesting read which gives a take on the core implications and potential of Blockchain as a service being the cornerstone to large-scale automative architectures. I really love how this summary gives me further perspective on the scaling trilemma of scalability, maintainability, and ease of use problem that Blockchain is facing! This may be a recurring theme of blockchain and the core hurdle for integration and adoption of blockchain for conventional commercial activity.

Ensuring decentralization over a vast perimeter of automation may hinder scalability and may introduce further layers of abstraction that make such automation unnecessarily difficult to operate. Ensuring Scalability inevitably makes tradeoffs of blockchains decentralization and makes maintenance of said blockchain possibly irreconcilable. This goes the same for ensuring ease of use. Conveniences and an emphasis on good user experiences may as well make the entire application architecture so simple that blockchain may be the last technology any developer would want to use in their application.

In terms of the scalability issue of data management, would you think the concept of a “blockchain database” be appropriate to facilitate further development of Blockchain as a service oriented automative applications?

Blockquote El-Hindi et al. introduced the concept of Blockchain DB with the aim of coming up with a shared database on blockchains [2]. Blockchain DB introduces a database layer on top of the existing blockchain framework that extends the blockchains by classical data management techniques. The aim of blockchain DB is to increase the performance and scalability of blockchains for data sharing but also decrease complexities for organizations intending to use blockchains as DB.

An overview of blockchain scalability, interoperability and sustainability
2. El-Hindi et al. (2019). “BlockchainDB - Towards a Shared Database on Blockchains.”

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Thanks for your comment @jmcgirk.

Industry 4.0

The fourth Industrial Revolution (Industry 4.0) is driven by the goal of complete industrial automation with minimal third-party interference. Industry 4.0 has emerged through the convergence of Cyber-Physical Systems, the Internet of Things (IoT), and the digital technologies outlined in Fig. 1. In this paper, the author emphasizes that blockchain will have a profound impact on Industry 4.0, which may be attributed to underlying principles like better efficiency and trustworthiness. Blockchain-enabled Industrial Internet of Things (IIoT) platforms may enhance the main features of Industry 4.0 illustrated in Fig. 1. This is discussed with more depth as follows:

Decentralization

As a decentralized ledger technology, blockchain enables self-regulating capabilities and eliminates reliance on centralized authorities. In blockchain networks, smart contracts are real-time auditors that perform self-executing functions once specific conditions are met. Integrating blockchain networks with IIoT platforms may advance the autonomy of smart machines in industrial manufacturing by securing machine-to-machine communication. Further, removing third-party actors reduces overhead costs and risks associated with intermediaries and centralization, such as single-points-of-failure attacks. Considering that Industry 4.0 seeks to achieve full industrial automation, implementing a decentralized system may support its intent. This makes blockchain infrastructure and its autonomous capacities an appealing prospect for Industry 4.0.

Trustworthiness

The use of blockchain may enhance data transparency and increase trustworthiness in Industry 4.0. In this paper, the author emphasizes that having autonomous agents communicate directly provides several key advantages: greater efficiency, lower expenses, and fewer risks involved. However, in centralized industrial systems, the trustworthiness of the agents is an open issue [1]. Blockchain can address this concern. With all data on a blockchain stored in an immutable and transparent manner, participating entities can monitor and verify transactions across multiple industrial sectors and organizations. Additionally, consensus mechanisms ensure that all participating agents within a network share the same account of the truth while smart contracts running on blockchain regulate data provenance, ownership, and user access controls. Since data stored on the blockchain is visible to the authorized users of a network, it is resistant to manipulation, and tampering is more readily detected. With more reliable data, the technologies deployed in Industry 4.0 are better equipped to “extract value” to improve learning patterns and autonomy within smart factories.

Digitization

As “​​the backbone of any industrial sector”, the supply chain plays a critical role within industrial processes. Blockchain technologies can be implemented for quality control and more efficient supply chain management. One example of this may be found within the aerospace industry, where blockchain will potentially increase revenue by up to $40 billion. With a single aircraft consisting of up to millions of individual parts, blockchain technologies can assign each one a digital identity and retain its “digital twin”—a complete record that includes its provenance, service maintenance history, configuration, etc. This record is continually updated and available in real-time, making problems easier to diagnose and thereby reducing the frequency of manual testing and inspection. For instance, Airbus was able to take a preemptive maintenance approach by embedding sensors into its machinery. Blockchain’s utility within the aerospace industry can generally be applied to industrial ecosystems. Industrial assets like smart devices and machinery may be digitized and tracked. With parts originating from many different suppliers, traditional systems face challenges with counterfeits, communication barriers, and manual record-keeping. In Industry 4.0, blockchain can help to overcome drawbacks such as these by providing a secure digital accounting system that allows for greater traceability and tracking.

Conclusion

The topics discussed here only touch on a very small portion of blockchain’s utility within Industry 4.0. Anyone interested in further exploring blockchain’s applicability in Industry 4.0 should read “Blockchain technology applications for Industry 4.0: A literature-based review.” With regards to this response, the key takeaways of blockchain within Industry 4.0 are: decentralization that allows for greater automation of industrial processes, trust through transparency and immutability of industrial data, and digitization that allows for traceability and tracking of industrial components.

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@Twan, I’m interested to learn how Ethereum 2.0 will reduce energy consumption by 99%. What measures are being taken to achieve this level of efficiency?

@kanad Thanks for sharing. The author of this paper mentions that the use of hash tables is a possible storage solution for resource-constrained IIoT devices. Can you elaborate more on how distributed hash tables are beneficial for industrial applications and end devices based on your experience? Also, I’m curious to hear your thoughts on whether you think one of the author’s proposed models of integration or BaaS is appropriate for industrial uses at this point in time.

@GanouTeikun Thanks for your comment. As the lab integrates more technologies that introduce connectivity to traditional equipment, what do you see as possible challenges or risks posed by this scenario? How might blockchain advance automation in the lab? What are some potential drawbacks that blockchain may present? Lastly, can you provide some insight on the uses of blockchain and AI convergence in the lab?

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@rlombreglia Thank you for your thoughtful additions to this conversation. While this paper has limited discussion on edge computing, it most certainly is an area that deserves attention given its tremendous growth, relevance to time-sensitive applications, and potential to accelerate industrial performance.

Edge computing processes and transmits local data, meaning that the bandwidth requirements are lower in comparison to dispatching all data to a centralized data center. Edge computing can reduce cloud storage requirements by filtering out “excess data”, and sending the essential data to the cloud. Limiting the data processed by the cloud mitigates latency, making edge computing an emerging solution for the timing requirements of industrial operations. Gartner estimates that around 75% of “enterprise-generated data” will be “created and processed outside a traditional centralized data center or cloud” by 2025. As industrial applications continue to incorporate more smart devices into their networks, finding an efficient and secure means to manage the massive data that they generate is increasingly imperative. Edge computing shows promise in addressing scalability challenges and lowering operational overhead in Industrial Internet of Things (IIoT) platforms, yet the inherent risks of centralized systems prevail.

Blockchain technology may be implemented on the IIoT edge to secure communication and minimize networking and computational overhead. This is observed in the following use cases:

  • Guo et. al tested a “distributed and trusted authentication” model that deployed a Practical Byzantine Fault Tolerance consensus algorithm to record and authenticate data on a consortium blockchain. In the experiment, edge authentication services were provided via smart contracts, an asymmetric cryptographic framework was applied to secure the edge nodes and terminals, and an edge-based caching scheme was used to accelerate the hit ratio. The results suggested that the proposed model outperformed current edge computing models by reducing delay, improving hit ratio, and providing a more cost-efficient communication and computational mechanism.

  • Jangirala et. al developed a simulation that used blockchain identification technologies to verify the identity of reader tags within supply chains. By applying a “lightweight blockchain-enabled RFID-based authentication protocol” within a “5G mobile edge computing environment” with bitwise rotation, bitwise exclusive-or, and linear cryptographic hashes, the researchers observed enhanced security and improved communication and computational overhead compared to existing models.

  • Nkenyereye et. al proposed a private blockchain-based “lightweight multi-receiver signcryption scheme” for emergency driven messages (EDM) in 5G vehicular edge computing. By implementing blockchain into edge nodes, EDMs were securely transmitted to edge servers within close proximity to reduce response time. The findings of the study indicate that the edge nodes were shielded from various attacks and that the model reduced communication overhead.

To reiterate the material discussed in the summary, blockchain removes centralized solutions used to increase throughput, i.e. resorting to expensive networking equipment, and it eliminates fees associated with third parties. Though the author of the original article does not specify as to why blockchain may lower these overhead expenses, generally it seems that incorporating blockchain into edge nodes, adopting lightweight protocols, and using blockchain as an overlay for heterogeneous devices may allow for communication to become more efficient, secure, and cost-effective.

At the edge layer, poorly-secured edge devices are an entry point for attackers. Moreover, resource-constrained edge-IoT devices in centralized systems face challenges with implementing “fine-grained access controls” and “encryption-based data protection.” Integrating blockchain into the Edge of Things (EoT) networks enables security services such as “access authentication, data privacy preservation, attack detection, and trust management”. The convergence of blockchain, edge computing, and the internet of things creates the novel paradigm coined the blockchain edge of things (BEoT). In the BEoT, data may be secured through encryption algorithms, yet one thing that remains unclear to me is if the “robust encryption primitives” are actually integrated into the edge devices themselves. From what I gather, encryption mechanisms are carried out in the network layer after the blockchain authenticates the devices.

Per conversations with @Gearlad, Francis has experience with edge computing. @fmendoz7, is there any insight that you can provide on this topic?

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Hi @rlj, thank you for the thoughtful response. Our lab lacks personnel with a strong IT background. In addition, it’s a fairly new lab and we are still in the process of acquiring new resources.

Our research is more related to material science; we’ve just started getting into applying automation and AI technologies to our research recently. Some of the softwares we use include OriginPro, Jade (for XRD), CHI6273D electrochemical analyzer, AutoLab, etc. There are many cases where the application of AI is beneficial to all parties involved, and there are ways that it could optimize the softwares we use. With that being said, there is always an inherent risk with using AI and taking humans out of the equation.

Risks involved with humans operating the lab

  • Human error in measurements
  • Human safety hazards: burns (acids, bases, fires, etc.), toxic gas, cuts (especially when using drills or cutters)
  • Causing damage to equipment
  • Incorrect operational procedures

Risks involved with automation of lab processes

  • Variables not programmed to be factored in by AI - these cases need human intervention
    • Dulling of blade, malfunctioning parts, etc.
    • Introducing machine to dynamic or rapidly changing environment
  • As you mentioned in your summary, end devices can be attacked or hacked as they lack sufficient security mechanisms.

Blockchain can be used for material sciences in the context of supply chain management. Quality assurance and ensuring that data is tamperproof is something that the blockchain can provide; blockchain has the potential of tracing the usage of materials from source (manufacturers, miners - of metals, not of hash values, etc.) to consumer (researchers and different industries).

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