Distributed IoT systems
Decentralised IoT systems (Decentralised Internet of Things) are systems with a decentralised architecture as opposed to traditional centralised IoT systems, where IoT devices and sensors exchange and process data directly on the network, without depending on a central server. IoT.
The main features and benefits are as follows.
1. scalability: distributed IoT systems make it easier for the whole system to scale as nodes (devices) are added. As each device operates independently of a central server, performance can be maintained even in large networks.
2. fault-tolerance: as there is no central server, the entire system is not dependent on a single point of failure. This ensures that if one part of a node fails, the other nodes continue to function and the entire system remains healthy.
3. security: because the data is distributed, it is easier for the entire system to remain secure in the event of a single node or server being attacked, and security is enhanced through a combination of data encryption and distributed authentication mechanisms.
4. privacy: as data is processed on each device, personal and sensitive data is not centralised on a central server, making it easier to protect privacy.
5. real-time processing: by exchanging data directly between devices, data can be processed in real-time without having to go through a central server, enabling rapid reaction and control.
Specific implementation technologies include.
- Blockchain: uses distributed ledger technology to record transactions and data exchanges between IoT devices.
- Edge computing: processing data on devices or edge nodes to enable real-time processing without sending it to a central server.
- Distributed storage: data is distributed across multiple nodes to improve data resilience and redundancy.
Distributed IoT systems enable efficient and robust data management and are flexible enough to meet the requirements of different applications and systems.
Distributed Ledger Technology (DLT)
Distributed Ledger Technology (DLT: Distributed Ledger Technology) is a technology in which a digital ledger is stored across multiple computers (nodes) on a network, with each node holding a copy of the ledger and synchronised across all nodes. This technology is used to enhance data transparency, security and tamper-resistance.
A typical example of DLT is blockchain. A blockchain consists of transactional data in ‘blocks’, which are then linked together in chronological order to form a ‘chain’. Each block contains a hash value of the previous block, which ensures data integrity.
DLTs have been applied in a variety of areas, including the financial industry, supply chain management, digital identity and smart contracts, where the decentralised nature of the system makes it more robust and reliable than traditional centralised systems.
Benefits of combining distributed IOT systems and distributed ledger technology
The combination of such distributed IoT systems and distributed ledger technology (DLT) results in the following benefits.
1. data integrity and tamper-resistance:
– Tamper-proof: DLT, and in particular blockchain, is designed to prevent data tampering, as transactions are recorded on all nodes, making it very difficult to change data. This ensures the integrity of the data generated by IoT devices.
– Traceability: by tracking the history of the data, it is easy to see which device generated the data and how it was processed.
2. enhanced security:
– Distributed security: data is stored in a distributed ledger, eliminating a single point of failure, enhancing security and protecting against unauthorised access and data tampering through data encryption and digital signatures.
– Authentication and access control: DLT can be used to enforce authentication and access control between devices, ensuring that each device’s actions and data transmissions are recorded and reliable.
3. automation through smart contracts:
– Transaction automation: smart contracts can be used to ensure that processing and actions are performed automatically when data meets certain conditions. For example, an automatic alert can be sent out when a sensor exceeds a certain threshold.
– Efficient data exchange: the automation of data exchange and contract enforcement between IoT devices increases the efficiency of the overall system.
4. reliability and resilience:
– Advantages of distributed networks: the combination of DLT and distributed IoT systems improves overall fault tolerance, so that if one part of a node fails, the other nodes continue to function and the entire system remains stable.
– Distributed data storage: data is stored across multiple nodes, reducing the risk of data loss and improving overall system reliability.
5. transparency and auditability:
– Real-time auditing: DLT facilitates real-time auditing and verification as all transactions are transparently recorded. This makes it easier to verify the origin of data and the processing process.
– Provides an audit trail: a history of each device’s actions and data exchanges is stored, making auditing and troubleshooting easier.
Applications combining distributed IOT systems and distributed ledger technology
There are a wide range of applications that combine distributed IoT systems with distributed ledger technology (DLT). The following are specific examples of applications.
1. supply chain management:
– Data tracking and transparency: using DLT, products can be tracked all the way from manufacture to delivery and sale, with IoT sensors collecting data in real time and this data being recorded in the blockchain to ensure that product quality and handling history is known.
– Quality assurance: conditions such as temperature and humidity are recorded, providing evidence of product quality retention and increasing confidence to consumers and suppliers.
2. smart grids:
– Energy management and distribution: the use of DLT to manage decentralised energy resources (e.g. household photovoltaic systems and electric vehicles) allows energy transactions and usage to be transparently recorded; IoT devices monitor energy generation and consumption, and smart contracts can distribution and payments are automated. See detail in “Electricity storage technology, smart grids and GNNs”
– Efficient distribution of energy: balancing supply and demand in real time to ensure efficient distribution of energy
3. health care and medicine:
– Patient data management: patient health data and diagnostic results are collected by IoT devices (e.g. wearable devices) and recorded in DLTs to enable access by healthcare organisations and researchers, while maintaining data integrity and privacy.
– Medicines tracking: tracking medicines from manufacture to distribution, helping to prevent counterfeit and fraudulent products, and enabling DLT to verify the authenticity of products.
4. smart cities:
– Manage public services: use distributed IoT systems to monitor urban infrastructure (e.g. traffic, lighting, waste management) and utilise DLT to record and manage data. This can improve service efficiency and better manage budgets and resources.
– Citizen participation: smart contracts can be used to provide a way for citizens to participate in the management of public services and to record their opinions and requests on the blockchain.
5. digital identity:
– Identity management: manage secure and privacy-preserving digital identities by collecting biometric and other authentication data on IoT devices and recording them in DLTs.
– Access management: use smart contracts to automatically manage user authentication and access rights.
6. traceability and compliance:
– Product traceability: use DLT to trace the manufacturing process and distribution channels of products such as food and chemicals to ensure compliance with regulations and standards.
– Enhanced compliance: recorded data can help verify compliance with regulations and industry standards.
Algorithms applied to the combination of distributed IOT systems and distributed ledger technology
The algorithms applied when combining distributed IoT systems and distributed ledger technology (DLT) include.
1. consensus building algorithms:
– Proof of Work (PoW):
– Description: an algorithm whereby a node solves a computational problem in order to add a transaction to a block, which is then added to the blockchain. Highly secure but energy intensive as it consumes computational resources.
– Applications: used to ensure the integrity of transactions, e.g. Bitcoin.
– Proof of Stake (PoS):
– Description: Algorithm where nodes are entitled to block generation based on the amount of cryptocurrency they hold. Energy efficient and improves scalability.
– Applications: used in e.g. Ethereum 2.0 and Cardano.
– Practical Byzantine Fault Tolerance (PBFT):
– Description: an algorithm for obtaining agreement between nodes, which assumes that if a certain number of nodes provide correct information, then overall agreement can be obtained. It has relatively low latency and is often used in commercial applications.
– Applications: e.g. Hyperledger Fabric and Zilliqa.
2. encryption algorithms:
– Hash functions (SHA-256, SHA-3, etc.):
– Description: algorithm that converts data into a fixed-length hash value. Used to maintain data integrity and security.
– Applications: SHA-256 is used in the Bitcoin blockchain.
– Digital signatures (e.g. ECDSA, RSA):
– Description: Signing a message or transaction ensures the authentication of the sender and the integrity of the data. Asymmetric cryptography is used.
– Applications: used for transaction signing in blockchain networks.
3. data integrity algorithms:
– Merkle Trees:
– Description: A tree structure for verifying data integrity, used to check the integrity of transactions within a block. When data changes occur, the entire tree is affected, facilitating verification.
– Applications: e.g. Bitcoin blockchain.
4. smart contract algorithms:
– Solidity:
– Description: programming language for smart contracts used in Ethereum, which encodes the logic of the contract and ensures that it is executed automatically.
– Applications: used to create smart contracts in the Ethereum network.
– Vyper:
– Description: alternative smart contract programming language to Solidity, with emphasis on security and conciseness.
– Applications: used for smart contract development.
5. distributed storage algorithms:
– InterPlanetary File System (IPFS):
– Description: A decentralised file system in which files are stored in a distributed manner across nodes and can be accessed efficiently. It uses a hash value of the file to identify its contents.
– Applications: used for data storage in distributed applications.
– BigchainDB:
– Description: A distributed database, providing high-throughput data processing while utilising blockchain characteristics. It has database query functionality, but is data tamper-proof.
– Applications: used in distributed applications requiring fast data transactions.
Examples of implementations combining distributed IOT systems and distributed ledger technology
Examples of implementations combining distributed IoT systems and distributed ledger technology (DLT) include.
1. smart supply chains:
Description: a system that combines IoT sensors and DLT to manage the entire supply chain of a product.
Example implementations:
– IoT sensors: sensors attached to products in distribution or storage collect real-time data on temperature, humidity, location, etc.
– DLT: using blockchain, the collected data is recorded in an unalterable ledger. This allows transparent tracking of the distribution history and storage status of products.
– Smart contracts: actions (e.g. sending out alerts, processing returns, etc.) are automatically performed when certain conditions are met.
Benefits:
– Improves product tracking and traceability
– Provides evidence of quality retention
– Enhances transparency throughout the supply chain
2. smart grid systems:
Description: energy management system combining DLT and IoT for the management of decentralised energy resources.
Example implementations:.
– IoT devices: devices that collect energy generation and consumption data from household photovoltaic systems and electric vehicles.
– DLT: uses blockchain to record energy transactions and usage and stores them in a distributed ledger, where transaction history and consumption data are transparently recorded.
– Smart contracts: automatically manage energy transactions and payments, with transactions being processed automatically when the conditions are met.
Benefits:
– Provides transparency in energy transactions.
– Automated settlement and transaction management
– Efficient management of decentralised energy resources
3. medical data management systems:
Description: system combining IoT and DLT for the management and sharing of medical data.
Example implementations:
– IoT devices: real-time collection of health data from wearable devices and medical equipment.
– DLT: record patient health data and diagnostic results in a blockchain to maintain data integrity and privacy.
– Smart contracts: manage data access rights and sharing rules, automatically controlling access to data based on conditions.
Benefits:
– Enhanced patient data integrity and security.
– Efficient sharing and access management of healthcare data
– Real-time monitoring of health data
4. smart city management systems:
Description: system combining DLT and IoT for the management of urban infrastructure.
Example implementations:
– IoT devices: traffic sensors, lighting controllers, waste collection sensors, etc. within the city collect data in real time.
– DLT: the collected data is recorded in a blockchain to transparently track the status and usage of urban infrastructure.
– Smart contracts: automate infrastructure management rules and service conditions, e.g. to control traffic signals or optimise public services.
Benefits:
– Efficient management and optimisation of urban infrastructure
– Data transparency and real-time monitoring
– 4. automation and improvement of citizen services
5. digital identity management:
Description: combined IoT and DLT systems for managing individual digital identities.
Example implementations:
– IoT devices: biometric devices and smart cards collect personal identity information.
– DLT: digital identity information is recorded on a blockchain to make the data secure and tamper-proof.
– Smart contracts: automate access rights and authentication rules to control access based on specific conditions.
Benefits:
– Enhanced security and privacy of digital identities
– Automates and streamlines the authentication process
– Data tampering protection and integrity assurance
Challenges in combining distributed IOT systems with distributed ledger technology and how to address them
Several challenges exist when combining distributed IoT systems with distributed ledger technology (DLT). Each of these challenges and measures to address them are described below.
1. scalability:
Challenges:
– Processing power limitations: DLT, particularly blockchain technology, has limitations in transaction processing speed and throughput, and blockchain performance can become a bottleneck when IoT devices generate large amounts of data.
Solution:
– Layer 2 solutions: there are ways to improve scalability by processing and collecting data off-chain and reducing the amount of transactions recorded on-chain. Examples include Lightning Networks and Plasma.
– Distributed databases: use distributed databases (e.g. BigchainDB, IPFS) instead of distributed ledgers to improve data scalability.
2. data privacy and security:
Challenges:
– Protecting privacy: data recorded in DLTs is often publicly available and the privacy of personal and sensitive information collected from IoT devices needs to be protected.
Solution:
– Data encryption: privacy can be protected by encrypting data before it is recorded on the blockchain, using public key cryptography and hash functions.
– Private blockchains: privacy is protected by using private blockchains, which can only be accessed by certain authorised nodes, instead of public blockchains where all transactions are publicly visible
3. data integrity and reliability:
Challenge:
– Data authenticity: it can be difficult to ensure the quality and authenticity of the data provided by IoT devices, and if the data is inaccurate or tampered with, the information on the DLT will also be inaccurate.
Solution:
– Data verification mechanisms: it is important to incorporate verification mechanisms in the data collection process to ensure data quality, e.g. only record data in the DLT if they meet certain quality criteria.
– Selection of consensus algorithms: improve data reliability by selecting reliable consensus algorithms (e.g. PBFT) and ensuring that only data for which consensus has been reached between nodes is recorded.
4. interfaces and compatibility:
Challenges:
– Compatibility between systems: it is sometimes difficult to ensure compatibility between IoT devices and different DLT systems, as there are different protocols and standards, making it difficult to achieve uniformity.
Solution:
– Standardisation and APIs: use standardised protocols and APIs to ensure compatibility between IoT devices and DLT systems and adopt standard formats and interfaces for data exchange to maintain uniformity between different systems.
– Bridge solutions: build bridge solutions or gateways to bridge data between different DLT networks and IoT platforms.
5. costs and resources:
Challenges:
– Increased costs: deploying and operating DLT can be costly, especially for large IoT systems, where costs related to resource consumption and maintenance can be high.
Solution:
– Efficient resource management: introduce technologies that increase the efficiency of resource use (e.g. lightweight blockchain protocols or cloud-based resource management) in order to optimise costs.
– Performance optimisation: optimise performance based on data volume and transaction frequency to ensure efficient operations while keeping costs down.
6. regulation and compliance:
Challenges:
– Regulatory compliance: compliance with data protection and industry regulations is required, but distributed systems make regulatory compliance difficult.
Solution:
– Understand and apply the legal framework: fully understand the current regulations and legislation and design your system to comply with them. Also ensure that the system is flexible enough to respond to regulatory changes.
– Implement compliance tools: implement tools and services that automate compliance checks and manage regulatory compliance effectively.
Reference Information and Reference Books
For information on WoT, see “About WoT (Web of Things) Technology. For information on IoT in general, see “Sensor Data & IOT Technologies“; for information on stream data processing, see “Machine Learning and System Architecture for Data Streams.
For reference books, see
“Managing the Web of Things: Linking the Real World to the Web“
“Building the Web of Things: With examples in Node.js and Raspberry Pi“
“Smart Innovation of Web of Things (Internet of Everything“
Key English References for Decentralized IoT with DLT and Mesh Networks
1. Blockchain for the Internet of Things: Architectures, Security, and Applications
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Editors: Debasis Giri, Joel J. P. C. Rodrigues
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Publisher: Springer, 2020
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Overview: A comprehensive guide to integrating blockchain (DLT) with IoT systems. Covers architectures, security mechanisms, use cases, and emerging applications in decentralized IoT environments.
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Best for: Understanding how blockchain enhances trust, security, and decentralization in IoT.
2. Internet of Things: Architectures, Protocols and Standards
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Authors: Simone Cirani, Gianluigi Ferrari, Marco Picone
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Publisher: Wiley, 2018
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Overview: Thorough explanation of IoT architectures and protocols, including detailed coverage of wireless technologies such as ZigBee, Thread, Bluetooth Mesh, and other mesh networking standards.
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Best for: Technical insights into mesh networking protocols for IoT deployment.
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Author: Imran Bashir
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Publisher: Packt, 4th Edition, 2023
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Overview: Comprehensive reference for understanding blockchain technology, including permissioned and permissionless DLTs, smart contracts, and IoT integration. Covers IOTA, Hyperledger, and real-world IoT use cases.
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Best for: Practitioners building secure, scalable, and decentralized IoT applications with DLT.
Key Topics & Search Terms
| Domain | Recommended Search Terms |
|---|---|
| Distributed Ledger | IOTA, Tangle, Hyperledger, Ethereum IoT, DAG-based Ledgers |
| Mesh Networking | ZigBee Mesh, Bluetooth Mesh, Thread, Wi-Fi Mesh, Decentralized Routing |
| IoT Security | Blockchain IoT Security, Distributed Trust Models, Peer-to-Peer Authentication |
| Edge/Fog Computing | Decentralized IoT, Edge Intelligence, Fog Computing for IoT |
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IOTA Foundation – Official Documentation
➔ DAG-based DLT for IoT applications -
IEEE IoT Journal
➔ Cutting-edge research on decentralized IoT, DLT, and mesh networking -
GitHub Practical Repositories
➔ Search"IoT Mesh Network Blockchain site:github.com"for code examples and frameworks
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