Six challenges facing blockchain and IoT convergence

Scale

The paramount technical challenge facing distributed ledger technology, or DLT, and IoT convergence is the ability to scale to meet service and security requirements across a dynamic network of devices. These requirements aren’t just precautions; they are foundational to running IoT in mission-critical, high-risk and high [data] volume (sometimes low-bandwidth) environments, such as healthcare, energy, transportation and beyond. This is rapidly pushing IoT data processing, management and analytics to the “edge,” where compute occurs locally, instead of relying on cloud connectivity.

A decentralized consensus mechanism may offer myriad benefits — information neutrality, authenticity, fault tolerance, security, etc. — but today that comes at the price of scalability, especially in an IoT context:

• It is simply untenable for vast networks of nodes to process every transaction
• Many (majority?) of “blockchain as a service” architectures are cloud-based
• Limited bandwidth to support real-time transaction processing
• Transaction and microtransaction fees can thwart project economics
• Traditional data storage structures are untenable using DLT
• Energy waste remains a massive barrier with environmental costs
• The costs and risks of potential downtime are too high

The silver lining of these constraints is that they are heavily influencing the architectural development and designs of blockchain today. What data are on versus off-chain; what type of consensus defines distributed verification; even a shift away from chains of blocks to other (still decentralized) record-keeping architectures (e.g., IOTA, Zilliqa and Lightning Network are all novel DLT approaches). DLT is not a solution for IoT’s scalability issues, but scalability will define when, how and in what scenarios IoT and DLT converge.

Security

While DLT architectures offer promising security benefits, security remains a significant challenge in the design and deployment of shared architectures. Businesses must not only protect data, contracts, files, devices and networks, but also maintain privacy, authenticate identity, prevent theft/spoofing, and develop governance for autonomous device coordination and settlement. Adding IoT into the equation merely extends these decisions across the topology of the network, whether a large-scale factory environment, a remote field with low bandwidth for connectivity, or within a smart home or retail context. DLT is not a silver bullet solution for IoT security, it merely introduces new design considerations across the stack.

Interoperability

The ability to securely and reliably interconnect multiple networks isn’t just a challenge in the IoT realm, but in the DLT space as well. Although blockchain is not a data integration tool per se, distributed ledgers are inherently designed to offer shared visibility of data. That said, interoperability takes on new complexities in the blockchain realm:

• Ability to integrate private and public blockchains
• Design of permissioning and data access across multiple “chains”
• Ability to integrate across multiple open source platforms
• Ensuring common standards for compliance adherence
• Ability to integrate with devices, existing data sets and incumbent systems

Requirements for customization can further fragment the technology’s ability to function harmoniously with other counterparties and architectures. Although a central objective of numerous consortia, including the International Standards Organization, and development activities, standardization is lacking at most layers of the stack, not to mention at the process level or across sectors or geographies.

Multiparty collaboration

While interoperability is typically viewed as a technical/standards hurdle — between data sets, devices, networks, etc. — it is also a deeply ingrained cultural hurdle. Traditional business instinct is competitive, proprietary and walled off, not open, interdependent or shared. This friction has challenged the current IoT market as traditional product-based business models are being forced to data-driven service-based business models, which inherently require an ecosystem to deliver.

The level of collaboration required for the successful and sustainable deployment of DLT is significant and will, in many instances, be entirely unprecedented. The range of intimate interactions between hitherto “strange bedfellows” is vast:

• Multiparty integration with incumbent systems
• Security and permissions testing across parties
• Designing and implementing shared operational and technical frameworks
• Encoding and implementing shared framework that adhere to regulatory compliance

Blockchain will not just require that estranged participants come together, but also demand multidisciplinary integration to define new laws, rules, liability frameworks, standards, processes, ontologies and definitions. Like IoT, the potential value of any DLT configuration is a function of the “network effect” — needing the network to prove the value of the network. If DLT can support greater control, granularity and trust to data and asset sharing, interoperability also represents a core catalyst for IoT business models involving broader ecosystems (note: registration required).

Regulation

Designing regulations and compliance into transaction execution is no simple feat. Enterprise-grade blockchain deployments will face numerous policy and legal questions — some such structures have precedents that are hundreds of years old, while others are all but entirely unchartered. Chief among these hurdles is the lack of clear monetary regulations and policy associated with digital or cryptocurrencies. Although certain countries and regulatory regimes are leaning into — or out of — the blockchain market, the IoT space is already foggy with legal uncertainties in data ownership, access, privacy and far beyond. DLT is not a replacement for governance, it merely introduces new ways to encode rules and process consensus.

Reputation and nascence

Both IoT and distributed ledger technologies are emerging. Blockchain is particularly nascent in its implementation — virtually all enterprise activity in the blockchain space is in proof-of-concept or pilot phase, and there are few, if any, at-scale deployments using private or permissioned blockchain configurations. While there are many examples of enterprise (particularly industrial) IoT deployed at scale, the simple fact that enterprise IT environments tend to evolve at a glacial pace means that both categories suffer from market dynamics that pose challenges to those exploring their convergence:

• Shady reputations (e.g., Bitcoin’s role in the dark web; IoT’s security vulnerabilities)
• Prone to media hype and hyperbole
• Fragmented marketplace (enterprise vendors and Sis versus startups; across public versus private DLT; growth in certain industries)

Finally, the nature of a technology in which many distributed parties share financial and operational stake is one where a wide range of constituencies influence its development. In addition to innovators small and large, governments and regulators, investors, financial institutions and merchants, consortia, miners, developers and engineers, and even consumers all play an untold role in development and reputation of blockchain. DLT is not a maturing vector for IoT per se, rather its own evolution will impact the architectural evolution of IoT.

While the intersection of DLT and IoT is a critical technological convergence to watch, and one that may provide an architecture for trust in autonomous products and services, businesses must take a sober approach. Blockchain is not a panacea or a solution to all IoT (nor IT) inefficiencies. Rather it is a series of modules and sub-technologies that companies must evaluate against current solutions and the needs and risks associated with integration. The challenges facing both IoT and DLT are vast, and in many cases unprecedented, but if past is prologue, such barriers have a way of pushing development forward.

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