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Blockchain for Edge of Things: Applications, Opportunities, and Challenges

Thippa Reddy Gadekallu, Quoc-Viet Pham, Dinh C. Nguyen, Praveen Kumar Reddy Maddikunta, N Deepa, Prabadevi B, Pubudu N. Pathirana, Jun Zhao, Won-Joo Hwang

arXiv:2110.05022v1cs.CRcs.DC

TL;DR

BEoT addresses security, privacy, and trust challenges arising when IoT data and computation move to the network edge. The paper surveys BEoT architectures, industrial applications, security services, and research challenges, finding broad opportunities while identifying unresolved issues including latency, computational cost, and limited intelligence.

  • Problem

    The paper addresses the missing comprehensive review of blockchain use in EoT and the security, privacy, and management challenges of distributed edge systems.

  • Method

    The paper conducts an extensive survey of BEoT architecture, industrial applications, security services, research challenges, and future directions.

  • Results

    The survey covers BEoT applications from smart transportation through smart grid and analyzes access authentication, data privacy preservation, attack detection, and trust management.

  • Takeaways & Limitations

    BEoT offers a broad framework for secure edge applications, but future work must address latency, communication and computation costs, and limited intelligence.

Abstract

from arXiv · show

In recent years, blockchain networks have attracted significant attention in many research areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by the combination of edge computing and the Internet of Things (IoT). In this context, blockchain networks enabled with unique features such as decentralization, immutability, and traceability, have the potential to reshape and transform the conventional EoT systems with higher security levels. Particularly, the convergence of blockchain and EoT leads to a new paradigm, called BEoT that has been regarded as a promising enabler for future services and applications. In this paper, we present a state-of-the-art review of recent developments in BEoT technology and discover its great opportunities in many application domains. We start our survey by providing an updated introduction to blockchain and EoT along with their recent advances. Subsequently, we discuss the use of BEoT in a wide range of industrial applications, from smart transportation, smart city, smart healthcare to smart home and smart grid. Security challenges in BEoT paradigm are also discussed and analyzed, with some key services such as access authentication, data privacy preservation, attack detection, and trust management. Finally, some key research challenges and future directions are also highlighted to instigate further research in this promising area.

I. INTRODUCTION

BEoT combines IoT, edge computing, and blockchain to address security and privacy challenges in distributed edge environments. Its architecture supports industrial applications and security services through decentralized data processing and blockchain mechanisms.

  • Security Motivation: Distributed EoT introduces security and privacy risks because edge-hosted computing, storage, and uploaded data can be exposed to attacks and breaches.Blockchain is presented as a potential response to these challenges.
  • BEoT Architecture: BEoT integrates IoT, edge computing, blockchain, industrial applications, and security services into one architecture.IoT devices generate data, edge servers process and store it, and blockchain interconnects devices, edge servers, and users without a central authority.
  • BEoT Architecture: Edge computing moves storage and computation closer to users, reducing transmission time for IoT data services.Edge servers support analytics, prediction, mining, and storage while potentially acting as blockchain miners.
  • BEoT Architecture: Blockchain provides decentralized coordination through data consensus, smart contracts, and shared ledgers.These mechanisms connect IoT devices, edge servers, and end users without requiring a central authority or third party.
  • Industrial Applications: BEoT supports applications spanning smart transportation, smart city, smart healthcare, smart home, and smart grid domains.The survey examines how blockchain-enabled edge services can support these industrial application areas.
  • Security Services: Blockchain-enabled EoT provides security services including access authentication, data privacy preservation, attack detection, and trust management.These services rely on decentralization, immutability, and traceability.

B. State of the Arts and Our Contributions

The paper addresses a missing comprehensive review of blockchain use in EoT by surveying its applications, architecture, security services, and research directions. It organizes the state of the art across multiple industrial domains and identifies open challenges.

  • Research Gap: Existing studies cover blockchain, IoT, and edge computing, but a comprehensive review of blockchain use in EoT remains missing.The paper is motivated by growing BEoT interest across academic and industrial application domains.
  • Contributions: The survey updates developments in blockchain and EoT and proposes and analyzes a high-level BEoT architecture.It also discusses motivations for combining the technologies.
  • Contributions: The paper reviews BEoT opportunities in smart transportation, smart city, smart healthcare, smart home, and smart grid applications.These domains constitute the central industrial-application scope of the survey.
  • Contributions: The survey analyzes blockchain-based security services for EoT, including access authentication, data privacy preservation, attack detection, and trust management.The paper presents these services as key security requirements of the BEoT paradigm.
  • Contributions: The paper identifies BEoT research challenges and highlights future directions based on its survey.The article is intended to support further research on BEoT applications and services.

II. BLOCKCHAIN AND EOT: STATE OF THE ART

The paper introduces blockchain and EoT as complementary technologies: blockchain provides decentralized transaction management, while edge computing brings IoT processing closer to users. Their combination offers security and responsiveness but faces energy, latency, throughput, and privacy constraints.

  • Blockchain: Blockchain is a decentralized distributed ledger in which linked blocks store transaction information and cryptographic hashes.Each block links to its predecessor through a hash label, supporting the integrity of the stored chain.
  • Blockchain: Consensus protocols replace a central authority by having participating blockchain nodes agree on the current ledger state.New blocks require consensus before they are accepted into the blockchain.
  • Blockchain: Smart contracts encode predefined terms and conditions so blockchain transactions can be verified and decisions made quickly.They reduce time spent on manual transaction verification.
  • Blockchain Properties: Decentralization distributes information across nodes, while immutability follows from consensus algorithms.These properties address single points of failure and support reliable storage across distributed systems.
  • Blockchain Limitations: Blockchain adoption in EoT is constrained by energy consumption, network latency, limited throughput, and security and privacy concerns.The paper notes Bitcoin at up to 4 transactions/second, Ethereum at about 20 transactions/second, and Visa at up to 1667 transactions/second.
  • EoT: EoT integrates edge computing with IoT so sensor data can be stored and analyzed at edge nodes for real-time services.The approach addresses cloud-related latency and processing challenges by placing computation nearer to users.

C. Motivations of the use of Blockchain in EoT

Blockchain is motivated in EoT by the need to secure sensitive edge data while retaining low-latency, distributed processing. Its properties support privacy, transaction reliability, trust, transparency, and industrial responsiveness.

  • Security Motivation: Edge nodes support real-time analytics but expose sensitive data to privacy, confidentiality, integrity, and attack risks.Applications using multi-access edge computing include healthcare, connected vehicles, smart homes, smart grids, and Industry 4.0.
  • BEoT Benefits: Blockchain can provide safe, transparent, immutable, decentralized applications with reduced latency and real-time analytics or recommendations.These capabilities are presented as motivations for combining blockchain with EoT.
  • Motivations: EoT’s distributed architecture provides a setting for storing and verifying blockchain transactions.The edge distribution is identified as a foundation for blockchain-enabled transaction handling.
  • Motivations: Blockchain is intended to preserve data privacy and security in blockchain-enabled EoT applications.This motivation applies to sensitive industrial data handled at the edge.
  • Motivations: Immutability and traceability can support transaction reliability in smart grids, transportation, healthcare, and government services.The paper links these blockchain properties to reliability in industrial transactions.
  • Motivations: Blockchain consensus is presented as a mechanism for maintaining trustworthiness and transparency of information transferred over BEoT networks.Consensus allows participating nodes to agree on transferred information.
  • Motivations: Applying blockchain in EoT is intended to support low-latency responses needed by many industrial applications.Low-latency response is identified as increasingly important for industrial services.

III. INDUSTRIAL APPLICATIONS FROM BEOT PARADIGM

BEoT applies blockchain and edge computing across industrial domains to support secure, decentralized, interoperable, and lower-latency services. The surveyed applications span smart transportation, smart cities, healthcare, homes, and smart grids.

  • Application scope: BEoT modernizes industrial networks by combining blockchain with EoT across transportation, smart grid, smart city, healthcare, and smart home applications.The paper presents these domains as major application areas for the paradigm.
  • Smart Transportation: Smart transportation uses decentralized blockchain networks and edge nodes to manage vehicular data, secure transactions, and support reliable vehicle operations.Vehicle networks can form sub-blockchain networks, while consortium blockchain supports secure data management in vehicular edge environments.
  • Smart Transportation: Blockchain-enabled platoon driving uses smart contracts for payments and was reported to perform well for individual vehicle models with respect to fuel consumption.The model targets congestion, accidents, pollution, and malicious payment transactions in urban heavy traffic.
  • Smart Transportation: A BEoT intersection-management system supports vehicle-to-infrastructure and infrastructure-to-vehicle communication while reducing vehicle waiting and crossing time.Blockchain provides decentralization and protection against malicious attacks, while EoT improves network performance and reduces latency.
  • Smart Grid: Smart grids face centralized-structure, security, interoperability, stability, restoration, pricing, and energy-management challenges that blockchain and edge computing are used to address.The surveyed approaches include edge-based V2G trading, lightweight consortium blockchains, smart contracts, and privacy-preserving data aggregation.
  • Cross-domain benefits: BEoT supports interoperable, secure, privacy-preserving industrial data processing, with edge services providing low-latency processing by reducing reliance on cloud access.Blockchain handles transactions among heterogeneous devices, while edge services process data closer to users.

C. Smart City

BEoT applications in smart cities combine blockchain, edge computing, IoT, and cognitive systems for secure data sharing, privacy preservation, monitoring, and automated decision-making. The surveyed architectures address surveillance, sharing-economy transactions, and structural-health monitoring.

  • Smart City: Smart cities use IoT to control, monitor, and track large volumes of sensor data while providing essential services.The paper frames smart-city systems as responses to diverse service requirements from growing populations.
  • Surveillance: Blockchain-based microservice architecture was proposed for scalable smart-city surveillance involving face, motion, license-plate, and threat detection.The cited passage contrasts this with conventional monolithic surveillance architecture.
  • Sharing Economy: Blockchain architectures support spatio-temporal smart contracts and cognitive engines for automated, third-party-free sharing-economy transactions.Cognitive engines use edge-node data and machine-learning capabilities for pattern recognition, language processing, analytics, and decision-making.
  • Security and Privacy: Edge networks reduce bandwidth and latency, while Argon2-based processing is introduced to improve security and privacy and prevent information leakage.The cited architecture records credentials and access rules and uses the key-derivation function in a distributed smart-city network.
  • Data Sharing: A channelized blockchain framework separates IoT data by type, with certified organizations, smart-contract access control, and encryption protecting each channel.The framework targets decentralization, security, interoperability, and privacy-preserving data sharing across smart-city applications.
  • Structural Health Monitoring: In secured structural-health monitoring, heterogeneous sensors provide building data to cloud services retrievable through cognitive edge nodes.The use case includes fibre-optic, temperature, inclinometer, accelerometer, strain, vibration, acoustic, smoke, and displacement-related sensors.
  • Surveillance: Edge video hubs process, analyze, and predict information from diverse surveillance systems, with blockchain-based smart contracts supporting secure transactions.The systems include road, commercial, residential, health-gadget, and other surveillance sources used for real-time decisions.

D. Smart Healthcare

BEoT supports smart healthcare through blockchain-secured medical data, edge processing, access control, and decentralized sharing. The surveyed systems cover UAV-based health records, therapy management, EHR protection, and dyslexia screening.

  • Smart Healthcare: IoT, AI, 5G, mobile Internet, big data, and cloud computing are transforming traditional medical systems into smart healthcare systems.The paper identifies healthcare as a major domain affected by these technologies.
  • Health Data Security: The BHealth scheme uses UAVs, MEC servers, blockchain, smart contracts, encryption, and user verification to collect and secure medical data.User information is stored on the blockchain, while blockchain synchronizes and protects health data and authorizes storage.
  • Therapy Management: A blockchain-MEC therapy framework provides decentralization, security, low-latency response, and data sharing for therapeutic data.Patients can share therapy data, while the mobile edge network processes multimedia information and avoids high-bandwidth limitations.
  • Electronic Health Records: Hybrid blockchain-edge architectures protect EHR access by verifying and recording access events through a mutual-agreement mechanism before blockchain inclusion.The architecture addresses security and privacy for patient data collected from sensors, wearables, and other sources.
  • Screening: A blockchain-based mobile-edge framework stores and shares dyslexia-testing data while applying automatic grading to predict symptoms.The final results are stored in the blockchain, providing a decentralized repository for multimedia test data used in medical research and analysis.

E. Smart Home

BEoT smart-home applications combine edge or fog processing with blockchain to support secure device access, real-time monitoring, and protected healthcare-data sharing. Reported benefits include attack prevention, event classification, and improved security, while ChainSDI increases communication and computation costs.

  • Secure smart-home access: Blockchain-based gateway architectures register and authenticate smart-home devices, restricting data transactions to approved devices and addressing gateway attacks.The framework uses SHA2 encryption and edge computing can offload blockchain computation overhead.
  • Secure smart-home access: Secure authentication combines blockchain, group signatures, and message authentication codes for reliable transactions, device authentication, and gateway authentication.The system also traces intruder misbehavior footprints.
  • Healthcare monitoring: Fog-assisted monitoring processes patient data near the network edge, providing real-time event notifications with minimum latency.The model uses a three-layer architecture with notification mechanisms at the gateway.
  • Healthcare monitoring: Behavior-based patient-event classification is performed accurately in the smart home using Bayesian belief networks with temporal mining.
  • Healthcare data sharing: ChainSDI supports secure sharing and computation of smart-home patient data, but increases communication and computation costs.It also addresses interoperability and regulatory issues in healthcare software-defined infrastructures.

IV. SECURITY REQUIREMENTS FROM BEOT PARADIGM

BEoT security requirements arise from growing device connectivity, data-intensive edge applications, and increasingly sophisticated cyberattacks. The reviewed approaches address authentication, privacy, trust, and attack protection, while reported limitations include latency, computing cost, and real-time constraints.

  • Security motivation: Growing numbers of connected devices create additional vulnerabilities, making it harder for systems to identify, protect, and respond to sophisticated attacks.The risks include theft, business disruption, and damage to the physical world.
  • Security requirements: Blockchain supports secure data exchange through digital identities, encryption, timestamps, hash functions, and distributed ledgers.These mechanisms are discussed as protections for IoT data and transactions.
  • Authentication and performance: The proposed model reduces delay rate by 6%-12% and increases hit rate by 8%-14% compared with existing models.
  • Authentication and performance: Authenticated blockchain and key-agreement approaches target secure, low-latency smart-grid edge systems, but computing cost and authentication-rate issues remain.One approach suggests maintaining edge-server cache nodes to reduce computing cost, while another reports that smart meters may fail authenticity checks.
  • Authentication and performance: A vehicular-edge blockchain model seeks low communication overhead, but does not achieve better latency and overhead for 256-bit data messages.

B. Data Privacy for Edge of Things

BEoT data-privacy approaches use blockchain, edge processing, and attack-detection mechanisms to protect sensitive IoT data and improve trusted exchange. Reported systems track messages, filter malicious participants, and reduce communication overheads, while trust-based transactions also support pricing and latency reduction.

  • Privacy protection: Blockchain privacy mechanisms use encryption, timestamps, hash functions, and distributed ledgers to protect data transmitted across distributed sites.
  • Privacy protection: A blockchain model deployed on edge servers processes New York taxi IoT data to protect sensed-data privacy.
  • Attack detection: An edge-cloud-SDN blockchain architecture pre-processes sensor data, dynamically manages network traffic, and detects malicious attacks.
  • Attack detection: Blockchain at edge nodes tracks messages, protects them from impersonation, DDoS, and masquerade attacks, and reduces communication overheads.
  • Trust management: BlockTDM uses trust management to exclude malicious distributors, while game-theoretic pricing supports transactions between suppliers and distributors.

E. Summary

BEoT security analysis identifies blockchain as a source of services including authentication, privacy preservation, attack detection, and trust management, while highlighting unresolved scalability, interoperability, and resource constraints.

  • BEoT security opportunities include access authentication, data privacy preservation, attack detection, and trust management.
  • BEoT must address challenges before adoption, including usability, cybersecurity, memory management, access control, real-time delivery, and prediction.
  • Blockchain records and tracks digital-resource transactions through a shared, secured, immutable, decentralized ledger without centralized authority.
  • Resource-constrained edge servers require lightweight authentication and trust management because conventional cryptographic techniques are difficult to accommodate.
  • Blockchain interoperability is obstructed by differences in digital-token and cryptocurrency representations.

3) Resource management in BEoT:

BEoT resource management is constrained by heterogeneous device capabilities, blockchain bandwidth and storage demands, and the need for scalable, device-specific designs and intelligent processing.

  • Blockchain can reduce data-processing latency through distributed resource use, but its bandwidth consumption conflicts with restricted IoT bandwidth.
  • Blockchain storage overhead can be reduced by separating metadata from streams or using sidechains, but lightweight designs may lose scalability as nodes increase.
  • Scalability requires device-specific blockchains tailored to IoT resource capabilities, including suitable security algorithms, mining processes, and metadata segregation.
  • BEoT still lacks intelligence for predictive analytics such as disease, demand, traffic, resource, and appliance-maintenance prediction.
  • Research directions include trust-enabled security frameworks, standards for privacy and interoperability, and query or resource-management methods that reduce processing and storage overhead.

2) Other Future Directions and Enabling Technologies:

Future BEoT directions emphasize compatibility, cybersecurity, scalable processing, AI-enabled prediction, cognitive edge computing, and integration with 5G networks.

  • Future BEoT work should address usability, cybersecurity, memory management, access control, real-time streams, and prediction of future trends.
  • Blockchain performance is limited by storage burden, energy and bandwidth consumption, throughput reduction, and scalability problems as IoT devices proliferate.
  • AI is proposed to provide the predictive intelligence missing from BEoT smart applications and to support real-time problem solving through learning.
  • Edge AI approaches use deep reinforcement learning for caching and federated learning for resource management, while blockchain integration remains subject to heterogeneous-node load distribution.
  • Cognitive-edge designs use blockchain subchains and machine learning for knowledge aggregation, extraction, management, and trading.
  • BEoT-5G integration faces throughput, scalability, smart-contract conversion, regulatory, privacy, infrastructure-cost, and trusted-registration challenges.
  • Intelligent transportation research combines 5G-VANET, software-defined networking, blockchain ledgers, and centralized authentication for traffic-system security.

VI. CONCLUSION

The paper surveys blockchain applications in EoT, proposes a generic BEoT architecture, reviews industrial and security uses, and identifies research challenges and BEoT-5G directions.

  • The survey covers BEoT architecture, industrial applications, and security services including authentication, privacy preservation, attack detection, and trust management.
  • The paper outlines research challenges and open directions toward BEoT-5G networks.
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