Shiva Kazemi Taskou, Mehdi Rasti, Pedro H. J. Nardelli
Network function virtualization (NFV) is a promising technology to make 5G networks flexible and agile. NFV decreases operators’ OPEX and CAPEX by decoupling the physical hardware from the functions they perform. In NFV, users’ service request can be viewed as a service function chain (SFC) consisting of several virtual network functions (VNFs) which are connected through virtual links. Resource allocation in NFV is done through a centralized authority called NFV Orchestrator (NFVO). This centralized authority suffers from some drawbacks such as single point of failure and security. Blockchain (BC) technology is able to address these problems by decentralizing resource allocation. The drawbacks of NFVO in NFV architecture and the exceptional BC characteristics to address these problems motivate us to focus on NFV resource allocation to users’ SFCs without the need for an NFVO. To this end, we assume there are two types of users: users who send SFC requests (SFC requesting users) and users who perform mining process (miner users). For SFC requesting users, we formulate NFV resource allocation (NFV-RA) problem as a multi-objective problem to minimize the energy consumption and utilized resource cost, simultaneously. To address this problem, we propose an Approximation-based Resource Allocation algorithm (ARA) using Majorization-Minimization approximation method to convexify NFV-RA problem. Furthermore, due to the high complexity of ARA algorithm, we propose a low complexity Hungarian-based Resource Allocation (HuRA) algorithm using Hungarian algorithm for server allocation. Through the simulation results, we show that our proposed ARA and HuRA algorithms achieve near-optimal performance with lower computational complexity. Also, ARA algorithm outperforms the existing algorithms in terms of number of active servers, energy consumption, and average latency. Moreover, the mining process is the foundation of BC technology. In wireless networks, mining is performed by resource-limited mobile users. Since the mining process requires high computational complexity, miner users cannot perform it alone. So, in this article, we assume that miner users can perform mining process with participating of other users. For mining process, the problem of minimizing the energy consumption and cost of users’ processing resources is formulated as a linear programming problem that can be optimally solved in polynomial time.
With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the grid to perform vertical transactions, e.g., feeding in extra solar energy to the grid and providing demand response service to alleviate the grid load. Smart homes can also interact with peer users to perform horizontal transactions, e.g., peer-to-peer energy trading. However, conventional transactive energy management method suffers from the drawbacks of low efficiency, privacy leakage, and single-point failure. To address these challenges, we develop a privacy-preserving distributed algorithm that enables users to optimally manage their energy usages in parallel via the smart contract on the blockchain. Further, we design an efficient blockchain system tailored for IoT devices and develop the smart contract to support the holistic transactive energy management system. Finally, we evaluate the feasibility and performance of the blockchain-based transactive energy management system through extensive simulations and experiments. The results show that the blockchain-based transactive energy management system is feasible on practical IoT devices and reduces the overall cost by 25%.
The adoption of blockchain for Transactive Energy has gained significant momentum as it allows mutually non-trusting agents to trade energy services in a trustless energy market. Research to date has assumed that the built-in Byzantine Fault Tolerance in recording transactions in a ledger is sufficient to ensure integrity. Such work must be extended to address security gaps including random bilateral transactions that do not guarantee reliable and efficient market operation, and market participants having incentives to cheat when reporting actual production/consumption figures. Work herein introduces the Electron Volt Exchange framework with the following characteristics: 1) a distributed protocol for pricing and scheduling prosumers' production/consumption while keeping constraints and bids private, and 2) a distributed algorithm to prevent theft that verifies prosumers' compliance to scheduled transactions using information from grid sensors (such as smart meters) and mitigates the impact of false data injection attacks. Flexibility and robustness of the approach are demonstrated through simulation and implementation using Hyperledger Fabric.
This conceptual paper overviews how blockchain technology is involving the operation of multi-robot collaboration for combating COVID-19 and future pandemics. Robots are a promising technology for providing many tasks such as spraying, disinfection, cleaning, treating, detecting high body temperature/mask absence, and delivering goods and medical supplies experiencing an epidemic COVID-19. For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area. Controlling and decentralizing multi-robot play a vital role in combating COVID-19 by reducing human interaction, monitoring, delivering goods. Blockchain technology can manage multi-robot collaboration in a decentralized fashion, improve the interaction among them to exchange information, share representation, share goals, and trust. We highlight the challenges and provide the tactical solutions enabled by integrating blockchain and multi-robot collaboration to combat COVID-19 pandemic. The framework of our conceptual proposed can increase the intelligence, decentralization, and autonomous operations of connected multi-robot collaboration in the blockchain network. We overview blockchain potential benefits to defining a framework of multi-robot collaboration applications to combat COVID-19 epidemics such as monitoring and outdoor and hospital End to End (E2E) delivery systems. Furthermore, we discuss the challenges and opportunities of integrated blockchain, multi-robot collaboration, and the Internet of Things (IoT) for combating COVID-19 and future pandemics.
Transactive energy plays a key role in the operation and energy management of future power systems. However, the conventional operational mechanism, which follows a centralized design, is often less secure, vulnerable to malicious behaviors, and suffers from privacy leakage. In this work, we introduce blockchain technology in transactive energy to address these challenges. Specifically, we develop a novel blockchain-based transactive energy framework for prosumers and design a decentralized energy trading algorithm that matches the operation of the underlying blockchain system. We prove that the trading algorithm improves the individual benefit and guarantees the socially optimal performance, and thus incentivizes prosumers to join the transactive energy platform. Moreover, we evaluate the feasibility of the transactive energy platform throughout the implementation of a small-scale network of Internet of Things (IoT) devices and extensive simulations using real-world data. Our results show that this blockchain-based transactive energy platform is feasible in practice, and the decentralized trading algorithm reduces the user's individual cost by up to 77% and lowers the overall cost by 24%.
Prosumer consortium energy transactive models can be one of the solutions for energy costs, increasing performance and for providing reliable electricity utilizing distributed power generation, to a local group or community, like a university. This research study demonstrates the simulation of blockchain based power trading, supplemented by the solar power prediction using MLFF neural network training in two prosumer nodes. This study can be the initial step in the implementation of a power trading market model based on a decentralized blockchain system, with distributed generations in a university grid system. This system can balance the electricity demand and supply within the institute, enable secure and rapid transactions, and the local market system can be reinforced by forecasting solar generation. The performance of the MLFF training can predict almost 90% accuracy of the model as short term ahead forecasting. Because of it, the prosumer bodies can complete the decision making before trading to their benefit.
Keqi Wang, Wei Xie, Wencen Wu, Bo Wang · 7 authors
With the passage of the 2018 U.S. Farm Bill, Industrial Hemp production is moved from limited pilot programs to a regulated agriculture production system. However, Industrial Hemp Supply Chain (IHSC) faces critical challenges, including: high complexity and variability, very limited production knowledge, lack of data and information tracking. In this paper, we propose blockchain-enabled IHSC and develop a preliminary simulation-based digital twin for this distributed cyber-physical system (CPS) to support the process learning and risk management. Basically, we develop a two-layer blockchain with proof of authority smart contract, which can track the data and key information, improve the supply chain transparency, and leverage local authorities and state regulators to ensure the quality control verification. Then, we introduce a stochastic simulation-based digital twin for IHSC risk management, which can characterize the process spatial-temporal causal interdependencies and dynamic evolution to guide risk control and decision making. Our empirical study demonstrates the promising performance of proposed platform.
In this paper, we present a pricing mechanism that aligns incentives of agents who exchange resources on a decentralized ledger with the goal of maximizing transaction throughput. Subdividing a blockchain ledger into shards promises to greatly increase transaction throughput with minimal loss of security. However, the organization and type of the transactions also affects the ledger's efficiency, which is increased by wallet agents transacting in a single shard whenever possible while collectively distributing their transactions uniformly across the available shards. Since there is no central authority to enforce these properties, the only means of achieving them is to design the system such that it is in agents' interest to act in a way that benefits overall throughput. We show that our proposed pricing policy does exactly this by inducing a potential game for the agents, where the potential function relates directly to ledger throughput. Simulations demonstrate that this policy leads to near-optimal throughput under a variety of conditions.
Model-based Systems Engineering (MBSE) has been widely utilized to formalize system artifacts and facilitate their development throughout the entire lifecycle. During complex system development, MBSE models need to be frequently exchanged across stakeholders. Concerns about data security and tampering using traditional data exchange approaches obstruct the construction of a reliable marketplace for digital assets. The emerging Distributed Ledger Technology (DLT), represented by blockchain, provides a novel solution for this purpose owing to its unique advantages such as tamper-resistant and decentralization. In this paper, we integrate MBSE approaches with DLT aiming to create a decentralized marketplace to facilitate the exchange of digital engineering assets (DEAs). We first define DEAs from perspectives of digital engineering objects, development processes and system architectures. Based on this definition, the Graph-Object-Property-Point-Role-Relationship (GOPPRR) approach is used to formalize the DEAs. Then we propose a framework of a decentralized DEAs marketplace and specify the requirements, based on which we select a Directed Acyclic Graph (DAG) structured DLT solution. As a proof-of-concept, a prototype of the proposed DEAs marketplace is developed and a case study is conducted to verify its feasibility. The experiment results demonstrate that the proposed marketplace facilitates free DEAs exchange with a high level of security, efficiency and decentralization.
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Systems Engineering Methodologies and Applications
Najmeddine Dhieb, Hakim Ghazzai, Hichem Besbes, Yehia Massoud
Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. Due to their massive deployment and moderate security levels, those devices face a lot of security, management, and control challenges. Their classical centralized architecture is still cloaking vulnerabilities and anomalies that can be exploited by hackers for spying, eavesdropping, and taking control of the network. In this paper, we propose to improve the IoT architecture with additional security features using Artificial Intelligence (AI) and blockchain technology. We propose a novel architecture based on permissioned blockchain technology in order to build a scalable and decentralized end-to-end secure IoT system. Furthermore, we enhance the IoT system security with an AI-component at the gateway level to detect and classify suspected activities, malware, and cyber-attacks using machine learning techniques. Simulations and practical implementation show that the proposed architecture delivers high performance against cyber-attacks.
Yang Zhao, Jun Zhao, Wenchao Zhai, Sumei Sun · 6 authors
While fifth-generation (5G) communications are being rolled out around the world, sixth-generation (6G) communications have attracted much attention from both the industry and academia. Compared with 5G, 6G will have a wider frequency band, higher transmission rate, spectrum efficiency, greater connection capacity, shorter delay, wider coverage and stronger anti-interference capability, so as to meet the various network requirements for industries. In this paper, we present a survey of potential essential technologies in 6G. In particular, we will introduce artificial intelligence, intelligent surfaces, terahertz communications technologies in detail, while giving a brief introduction to other potential technologies, including visible light communications, Blockchain-enabled wireless network, advanced duplex and holographic radio.
Lam Duc Nguyen, Israel Leyva‐Mayorga, Petar Popovski
Distributed Ledger Technologies (DLTs) are playing a major role in building security and trust in Internet of Things (IoT) systems. However, IoT deployments with a large number of devices, such as in environment monitoring applications, generate and send massive amounts of data. This would generate vast number of transactions that must be processed within the distributed ledger. In this work, we first demonstrate that the Proof of Work (PoW) blockchain fails to scale in a sizable IoT connectivity infrastructure. To solve this problem, we present a lightweight distributed ledger scheme to integrate PoW blockchain into IoT. In our scheme, we classify transactions into two types: 1) global transactions, which must be processed by global blockchain nodes and 2) local transactions, which can be processed locally by entities called witnesses. Performance evaluation demonstrates that our proposed scheme improves the scalability of integrated blockchain and IoT monitoring systems by processing a fraction of the transactions, inversely proportional to the number of witnesses, locally. Hence, reducing the number of global transactions.
Holger Kinkelin, Richard von Seck, Christoph Rudolf, Georg Carle
The security of cryptographic communication protocols that use X.509 certificates depends on the correctness of those certificates. This paper proposes a system that helps to ensure the correct operation of an X.509 certification authority and its registration authorities. We achieve this goal by enforcing a policy-defined, multi-party validation and authorization workflow of certificate signing requests. Besides, our system offers full accountability for this workflow for forensic purposes. As a foundation for our implementation, we leverage the distributed ledger and smart contract framework Hyperledger Fabric. Our implementation inherits the strong tamper-resistance of Fabric which strengthens the integrity of the computer processes that enforce the validation and authorization of the certificate signing request, and of the metadata collected during certificate issuance.
Hao Xu, Paulo Valente Klaine, Oluwakayode Onireti, Bin Cao · 6 authors
The sixth-generation (6G) network must provide better performance than previous generations to meet the requirements of emerging services and applications, such as multi-gigabit transmission rate, higher reliability, and sub-1 ms latency and ubiquitous connection for the Internet of Everything (IoE). However, with the scarcity of spectrum resources, efficient resource management and sharing are crucial to achieving all these ambitious requirements. One possible technology to achieve all this is the blockchain. Because of its inherent properties, the blockchain has recently gained an important position, which is of great significance to the 6G network and other networks. In particular, the integration of the blockchain in 6G will enable the network to monitor and manage resource utilization and sharing efficiently. Hence, in this paper, we discuss the potentials of the blockchain for resource management and sharing in 6G using multiple application scenarios, namely, Internet of things, device-to-device communications, network slicing, and inter-domain blockchain ecosystems.
Yang Zhao, Jun Zhao, Jiawen Kang, Zehang Zhang · 7 authors
An increasing amount of users' sensitive information is now being collected for analytics purposes. To protect users' privacy, differential privacy has been widely studied in the literature. Specifically, a differentially private algorithm adds noise to the true answer of a query to generate a noisy response. As a result, the information about the dataset leaked by the noisy output is bounded by the privacy parameter. Oftentimes, a dataset needs to be used for answering multiple queries (e.g., for multiple analytics tasks), so the level of privacy protection may degrade as more queries are answered. Thus, it is crucial to keep track of the privacy spending which should not exceed the given privacy budget. Moreover, if a query has been answered before and is asked again on the same dataset, we may reuse the previous noisy response for the current query to save the privacy cost. In view of the above, we design and implement a blockchain-based system for tracking and saving differential-privacy cost. Blockchain provides a distributed immutable ledger that records each query's type, the noisy response used to answer each query, the associated noise level added to the true query result, and the remaining privacy budget in our system. Furthermore, since the blockchain records the noisy response used to answer each query, we also design an algorithm to reuse previous noisy response if the same query is asked repeatedly. Specifically, considering that different requests of the same query may have different privacy requirements, our algorithm (via a rigorous proof) is able to set the optimal reuse fraction of the old noisy response and add new noise (if necessary) to minimize the accumulated privacy cost. Experimental results show that the proposed algorithm can reduce the privacy cost significantly without compromising data accuracy.
Distributed consensus mechanisms have been widely researched and made popular with a number of blockchain-based token applications, such as Bitcoin, and Ethereum. Although these general-purpose platforms have matured for scale and security, they are designed for human incentive and continue to require currency reward and contract functions that are not requisite in machine communications. Redes Chain is a custom designed blockchain, built to support fully decentralized self-organization in wireless networks-without a cryptocurrency or contract dependency.
Muhammad Baqer Mollah, Jun Zhao, Dusit Niyato, Kwok‐Yan Lam · 8 authors
Due to the unique features and characteristics of blockchain technology, its applications have expanded across various sectors, including finance, banking, supply chains, and smart grids (SGs). Blockchain ensures security and trust in transactions without requiring a third party, making it particularly valuable in decentralized systems. This paper explores the integration of blockchain technology into SG systems. It begins with a comprehensive review of conventional and smart power grids, identifying the key challenges modern SGs face, particularly issues related to trust and fraud. An in-depth analysis of blockchain technology follows, highlighting its potential, advantages, and defining characteristics. The study then examines several blockchain-based SG applications and provides a comparative analysis of prior research. The findings of this review illuminate the critical role of blockchain in enhancing SG performance by addressing trust and fraud prevention challenges. Furthermore, this research has significant implications for the energy sector, as it underscores the potential of blockchain to revolutionize SGs through increased security, transparency, and efficiency. By providing a foundation for future studies, this paper aims to guide the development of unified blockchain frameworks that address scalability, privacy, and energy management, paving the way for a more secure and efficient decentralized energy system
Michela Moschella, Pietro Ferraro, Emanuele Crisostomi, Robert Shorten
In this article, we propose a stochastic decentralized algorithm to recommend the most convenient charging station (CS) to plug-in electric vehicles (PEVs) that need charging. In particular, we use different cost functions to describe the possibly different priorities of PEV drivers, such as the preference to minimize charging costs, charging times, or the distance between them and the CS. For this purpose, we leverage on an Internet of Things architecture based on a permissioned distributed ledger technology (DLT) to enforce compliance of drivers and reduces the occurrence of detrimental misbehaviors of drivers. Extensive simulations performed with the mobility simulator SUMO in realistic city-wide networks have been provided to illustrate how the proposed PEV assignment procedure works in practice, and to validate its performance.
Shivam Saxena, Hany E. Z. Farag, Aidan Brookson, Hjalmar Turesson · 5 authors
This paper proposes a peer to peer (P2P), blockchain based energy trading market platform for residential communities with the objective of reducing overall community peak demand and household electricity bills. Smart homes within the community place energy bids for its available distributed energy resources (DERs) for each discrete trading period during a day, and a double auction mechanism is used to clear the market and compute the market clearing price (MCP). The marketplace is implemented on a permissioned blockchain infrastructure, where bids are stored to the immutable ledger and smart contracts are used to implement the MCP calculation and award service contracts to all winning bids. Utilizing the blockchain obviates the need for a trusted, centralized auctioneer, and eliminates vulnerability to a single point of failure. Simulation results show that the platform enables a community peak demand reduction of 46%, as well as a weekly savings of 6%. The platform is also tested at a real-world Canadian microgrid using the Hyperledger Fabric blockchain framework, to show the end to end connectivity of smart home DERs to the platform.
The automotive industry has seen an increased need for connectivity, both as a result of the advent of autonomous driving and the rise of connected cars and truck fleets. This shift has led to issues such as trusted coordination and a wider attack surface have come to light, leading to higher costs and bureaucratic interventions. Due to the increasing adoption of connected vehicles, as well as other connected infrastructure, trustless peer to peer systems including blockchain are being explored as potential solution to this efficiency problem. All the while, scalability is still a significant concern for industry players. Current blockchain based systems have difficulty scaling: Bitcoin can only process seven transactions per second (tx/s) whereas Ethereum's fifteen tx/s is not a major improvement. Combined with the high cost of consensus and low throughput, such platforms are unusable with the mobility sector. This paper will address the latest advances in the field that aim to resolve parts of this problem as well as inform its readers about the scalability technologies that could push blockchain automotive infrastructure into the mainstream. This paper will also introduce the theoretical tools and advancements that, if implemented, could bring the mobility industry closer toward adopting efficient, scalable, and cost effective decentralized solutions.
Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan · 8 authors
Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data. Then, manufacturers can predict customers' requirements and consumption behaviors in the future. The working flow of the system includes two stages: in the first stage, customers train the initial model provided by the manufacturer using both the mobile phone and the mobile edge computing (MEC) server. Customers collect data from various home appliances using phones, and then they download and train the initial model with their local data. After deriving local models, customers sign on their models and send them to the blockchain. In case customers or manufacturers are malicious, we use the blockchain to replace the centralized aggregator in the traditional FL system. Since records on the blockchain are untampered, malicious customers or manufacturers' activities are traceable. In the second stage, manufacturers select customers or organizations as miners for calculating the averaged model using received models from customers. By the end of the crowdsourcing task, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. To protect customers' privacy and improve the test accuracy, we enforce differential privacy on the extracted features and propose a new normalization technique. We experimentally demonstrate that our normalization technique outperforms batch normalization when features are under differential privacy protection. In addition, to attract more customers to participate in the crowdsourcing FL task, we design an incentive mechanism to award participants.
This paper deals with the design of the secure network in an Enhanced Internet of Vehicles by using the Blockchain Governance Game (BGG). The BGG is a system model of a stochastic game to find best strategies towards preparation of preventing a network malfunction by an attacker and the paper applies this game model into the connected vehicle security. Analytically tractable results for decision-making parameters enable to predict the moment for safety operations and to deliver the optimal combination of the number of reserved nodes with the acceptance probability of backup nodes to protect a connected car. This research helps for whom considers the enhanced secure IoV architecture with the BGG within a decentralized network.
While direct allocation of spectrum and evolved medium access protocols provide a base for ubiquitous wireless connectivity, the existing TCP/IP and OSI models were designed for wired networks and do not address open interconnection of air interfaces. Without an interconnection model for the air interface, existing network designs continue to tie wireless medium access to that of the backhaul provider for ownership of access and identity trust, resulting in limitations on functionality and coverage. In this paper, we propose a novel solution to access ownership and identity trust by extending the TCP network standard, under a new model we propose, named TCP-Air which integrates distributed ledger technologies directly at the air interface. Further, we present two use cases of the TCP-Air model, demonstrating applications not feasible under existing permissioned-access network designs.
Andrew Cullen, Pietro Ferraro, Christopher King, Robert Shorten
Recently, Directed Acyclic Graph (DAG) based Distributed Ledgers have been proposed for various applications in the smart mobility domain [1]. While many application studies have been described in the literature, an open problem in the DLT community concerns the lack of mathematical models describing their behaviour, and their validation. Building on a previous work in [1], we present, in this paper, a fluid based approximation for the IOTA Foundation's DAG-based DLT that incorporates varying transaction delays. This extension, namely the inclusion of varying delays, is important for feedback control applications (such as transactive control [2]). Extensive simulations are presented to illustrate the efficacy of our approach.