The accelerating adoption of electric vehicles (EVs) has revealed a significant challenge: ensuring accessible, secure charging infrastructure in areas with limited internet connectivity. This study introduces EVMCSDLT, a novel payment framework that leverages Distributed Ledger Technology (DLT) to facilitate secure transactions between EV users and mobile charging stations in offline environments. Unlike conventional payment systems that require continuous Internet connectivity, EVMCSDLT employs a two-part blockchain security mechanism using QR code authentication and hashing techniques. This mechanism distributes security data across both the sender's & receiver's devices, enabling transactions to be validated & recorded locally before subsequent synchronization with the blockchain network. The system is implemented using React.js integrated with Web3, supporting both online & offline transaction processing via MetaMask wallet. It also features real time geospatial tracking of fixed and mobile charging stations through Google Maps, allowing users to locate nearby charging options efficiently. Experimental results demonstrate a reliable transaction range of up to 8.13 meters between devices, consistent QR code scanning with an average response time of 3.4 s under various lighting conditions, and strong resistance to cyber threats in simulated man-in-the-middle attacks. The EVMCSDLT framework marks a significant advancement in extending the accessibility of EV charging technology to underserved areas while ensuring transaction security and integrity regardless of the Internet connectivity status.
With the wide application of electric vehicles, smart robots and Internet of Things (IoT) devices, efficient scheduling of mobile charging systems has become an important research direction in smart energy management. However, the traditional cloud computing architecture is difficult to meet the requirements of low latency, high reliability and privacy protection, and the existing scheduling strategies still have challenges in terms of energy optimization, task balancing and dynamic adaptability. To this end, this paper proposes an intelligent mobile charging scheduling method that integrates edge computing and biomechanical modeling, constructs a biomechanical-based charging demand modeling and energy consumption analysis framework, and combines bionic optimization algorithms to achieve efficient path planning. Meanwhile, an edge computing architecture is adopted to optimize resource scheduling, and a federated learning mechanism is designed to enhance cross-domain data processing capability. To safeguard user privacy, a multi-level privacy protection mechanism is proposed, combining differential privacy, homomorphic encryption and zero-knowledge proof to ensure data security. Experimental results show that the method outperforms traditional methods in terms of task response time, energy consumption optimization, load balancing and privacy security, and can significantly improve the charging scheduling efficiency and provide effective technical support for large-scale distributed charging networks. The research results provide a theoretical basis and engineering practice reference for the application of smart charging networks, edge intelligent computing and privacy protection technology.
Forks in the Bitcoin network result from the natural competition in the blockchain's Proof-of-Work consensus protocol. Their frequency is a critical indicator for the efficiency of a distributed ledger as they can contribute to resource waste and network insecurity. We introduce a model for the estimation of natural fork rates in a network of heterogeneous miners as a function of their number, the distribution of hash rates and the block propagation time over the peer-to-peer infrastructure. Despite relatively simplistic assumptions, such as zero propagation delay within mining pools, the model predicts fork rates which are comparable with the empirical stale blocks rate. In the past decade, we observe a reduction in the number of mining pools approximately by a factor 3, and quantify its consequences for the fork rate, whilst showing the emergence of a truncated power-law distribution in hash rates, justified by a rich-get-richer effect constrained by global energy supply limits. We demonstrate, both empirically and with the aid of our quantitative model, that the ratio between the block propagation time and the mining time is a sufficiently accurate estimator of the fork rate, but also quantify its dependence on the heterogeneity of miner activities. We provide empirical and theoretical evidence that both hash rate concentration and lower block propagation time reduce fork rates in distributed ledgers. Our work introduces a robust mathematical setting for investigating power concentration and competition on a distributed network, for interpreting discrepancies in fork rates -- for example caused by selfish mining practices and asymmetric propagation times -- thus providing an effective tool for designing future and alternative scenarios for existing and new blockchain distributed mining systems.
The modular approach to ledger technology (MLT) offers a fresh viewpoint and method for putting distributed ledger systems into practice. Aiming to address the rigidity and limitations of traditional blockchains, MLT has a modular structure, in contrast to conventional blockchains, which are frequently thought of as monolithic. This makes it easier to modify the ledger to meet certain needs without having to completely overhaul the system. The intrinsic ability of MLT to evolve is one of its most notable advantages. Drawn from extensive literature reviews and various case studies, it's evident that as financial systems have grown increasingly complex, scalable and adaptable solutions are now essential more than ever. MLTs allow for the independent addition, removal, and modification of components. The usage of MLT to tackle new issues or adapt to shifts in the financial landscape is accentuated by their versatility. The capacity for interoperation is another significant benefit. The modern global financial system consists of numerous organizations and platforms that necessitate seamless communication. Because of its modular construction, MLTs may be able to incorporate components adhering to diverse standards or protocols, facilitating more efficient interactions between platforms. In conclusion, MLT not only offers a breakthrough approach to distributed ledgers but also signifies a transformative tool in addressing the modern challenges of the financial ecosystem.
Transport Layer Security (TLS) protocol is a cryptographic protocol designed to secure communication over the internet. The TLS protocol has become a fundamental in secure communication, most commonly used for securing web browsing sessions. In this work, we investigate the TLSNotary protocol, which aim to enable the Client to obtain proof of provenance for data from TLS session, while getting as much as possible from the TLS security properties. To achieve such proofs without any Server-side adjustments or permissions, the power of secure multi-party computation (MPC) together with zero knowledge proofs is used to extend the standard TLS Protocol. To make the compliacted landscape of MPC as comprehensible as possible we first introduce the cryptographic primitives required to understand the TLSNotary protocol and go through standard TLS protocol. Finally, we look at the TLSNotary protocol in detail.
Meeting the targets of Sustainable Development Goal (SDG) 7, which focuses on ensuring access to affordable, reliable, sustainable, and modern energy for all, poses significant challenges. Overcoming these hurdles requires innovative solutions that can bridge the gap between current capabilities and future needs. Swarm electrification emerges as a promising concept that could accelerate progress towards achieving SDG 7 goals by leveraging the collective power of decentralized energy resources. This paper presents a literature review on swarm electrification and related insights from case studies. The study delves into the concept of swarm electrification, placing it within the context of the prevailing trends in the power system sector: decentralization, decarbonization, and digitalization. It examines the role of digital technologies in enhancing swarm electrification and categorizes application areas according to the phases of swarm electrification. Particular attention is given to the technologies underpinning Deep Digitalization, such as distributed ledger technology, notably blockchain, and artificial intelligence, with a focus on machine learning. These technologies play pivotal roles in advancing swarm electrification. The review demonstrates how deep digitalization can facilitate the improvement of swarm electrification and ultimately support the integration of bottom-up initiatives with top-down grid expansion efforts over time.
Azana Hafizah Mohd Aman, Norazuwana Shaari, Zainab S. Attar Bashi, Saman Iftikhar · 7 authors
The Internet of Things (IoT) and Blockchain paradigms have offered significant benefits in recent technological innovations. Blockchain has been rated one of the top ten strategic technologies in a recent Gartner survey, and it is increasingly being employed in a range of industries. Blockchains provide transparent, tamper-proof, and secure platforms that, enables ground-breaking commercial solutions. Nonetheless, the use of blockchain technology for IoT Smart Residential energy systems looks to be relatively unexplored. In fact, most IoT devices are powered by a battery with a short life span. Generating and managing energy on an infinite scale is a much more ambitious goal than relying solely on battery power. Hence, this topic is addressed in this article, focusing on the IoT energy systems, renewable energy resources, and how energy is successfully stored. By thoroughly evaluating the literature and existing research cases, this article contributes to the state-of-the-art. Our study examines the opportunities, challenges, and constraints for the evolving peer-to-peer energy systems and blockchain-IoT applications. The study concludes with the hurdles that technology must overcome in order to move beyond the hype phase and into mainstream acceptance.
The wireless blockchain network (WBN) concept, born from the blockchain deployed in wireless networks, has appealed to many network scenarios. Blockchain consensus mechanisms (CMs) are key to enabling nodes in a wireless network to achieve consistency without any trusted entity. However, consensus reliability will be seriously affected by the instability of communication links in wireless networks. Meanwhile, it is difficult for nodes in wireless scenarios to obtain a timely energy supply. Energy-intensive blockchain functions can quickly drain the power of nodes, thus degrading consensus performance. Fortunately, a symbiotic radio (SR) system enabled by cognitive backscatter communications can solve the above problems. In SR, the secondary transmitter (STx) transmits messages over the radio frequency (RF) signal emitted from a primary transmitter (PTx) with extremely low energy consumption, and the STx can provide multipath gain to the PTx in return. Such an approach is useful for almost all vote-based CMs, such as the Practical Byzantine Fault-tolerant (PBFT)-like and the RAFT-like CMs. This paper proposes symbiotic blockchain consensus (SBC) by transforming 6 PBFT-like and 4 RAFT-like state-of-the-art (SOTA) CMs to demonstrate universality. These new CMs will benefit from mutualistic transmission relationships in SR, making full use of the limited spectrum resources in WBN. Simulation results show that SBC can increase the consensus success rate of PBFT-like and RAFT- like by 54.1% and 5.8%, respectively, and reduce energy consumption by 9.2% and 23.7%, respectively.
Sub-Saharan Africa (SSA) is home to 75% of the world’s unelectrified population, and approximately 500 million of these live in rural areas. Off-grid mini-grids are being deployed on a large scale to address the region’s electrification inequalities. This study aims to provide a comprehensive review of the research on the off-grid renewable mini-grids in SSA. The study covers the current status of the level of deployment of off-grid mini-grids. It also reviews multi-criteria decision-making models for optimizing engineering, economics, and management interests in mini-grid siting and design in SSA. The statuses of financing, policy, and tariffs for mini-grids in SSA are also studied. Finally, the current status of energy justice research in respect of mini-grids in SSA is reviewed. The study shows the important role of decentralized renewable technologies in the electrification of SSA’s rural population. Within a decade since 2010, the rural electrification rate of SSA has increased from 17% to 28%, and 11 million mini-grid connections are currently operational. Despite these gains, the literature points to several injustices related to the present model by which SSA’s renewable mini-grids are funded, deployed, and operated. Hence, several recommendations are provided for the effective application of the energy justice framework (EJF) for just and equitable mini-grids in SSA.
With the rapid emergence of smart grids, charging coordination is considered the intrinsic actor that merges energy storage units (ESUs) into the grid in addition to its substantial role in boosting the resiliency and efficiency of the grid. However, it suffers from several challenges beginning with dependency on the energy service provider (ESP) as a single entity to manage the charging process, which makes the grid susceptible to several types of attacks such as a single point of failure or a denial-of-service attack (DoS). In addition, to schedule charging, the ESUs should submit charging requests including time to complete charging (TCC) and battery state of charge (SoC), which may disclose serious information relevant to the consumers. The analysis of this data could reveal the daily activities of those consumers. In this paper, we propose a privacy-preservation charging coordination scheme using a blockchain. The blockchain achieves decentralization and transparency to defeat the security issues related to centralized architectures. The privacy preservation will be fulfilled using a verifiable aggregation mechanism integrated with an aggregated signing technique to identify the untrusted aggregator and assure the data source and the identity of the sender. Security and performance evaluations are performed, including off-chain and on-chain experiments and simulations, to assess the security and efficiency of the scheme.
Distributed ledger technology is becoming popular these days because of its high confidentiality, decentralization, and nontampering. It is suitable for replacing centralized security disadvantaged point transfer systems. Low‐power wide area network (LPWAN) is capable for long‐range communication with low‐power consumption. The iconic features like wide area coverage and long battery‐powered duration make it best to combine with large‐scale IoT application deployment. In both industry and academic field, such combination of LPWAN and point transfer system is highly attended. However, the ledger management system generates too much data that low‐bandwidth network such as LPWAN can hardly handle; meanwhile, the processing power’s requirement for small IoT devices is challenging. Towards addressing these issues, we design a packet transmission optimizing mechanism for a ledger‐based point transfer system (LPTS) in LPWAN to reduce overall data traffic and build a simulator to evaluate its performance. Moreover, we have implemented the system and evaluated in field experiment.
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan · 5 authors
With advancements in renewable energy technologies, consumers are becoming prosumers, and renewable energy resources are being used in distributed networks. In an isolated distributed system, peer-to-peer (P2P) energy trading is one of the most promising energy management solutions. In this paper, we propose a P2P energy trading method for micro-grids using open resources and technology. The proposed setup comprises an Internet of Things (IoT) server to transfer energy amongst the peers without human intervention, and an Ethereum based private blockchain is suggested for money transfer in the form of cryptocurrency. The IoT server enables the peers to control and monitor self-produced energy. Arduino UNO, ACS 712 hall-effect current sensor, and a relay are the main components used in the hardware setup. The current sensor data is sent in real- time to Arduino for onward communication to the IoT server. A user-friendly interface has been developed on the server to perform various energy trading tasks. Peers have the choice to access the server remotely to perform energy trading tasks. The energy trading events can be shared amongst peers through e-mail notifications. For financial transactions, we utilized Ganache graphical user interface (GUI) a private Ethereum blockchain eliminating the need for financial institutions. The proposed peer-to-peer energy trading model has been successfully tested for energy trading between two peers. This paper provides details of the proposed hardware and software setup and explains how low-cost P2P energy trading can be achieved.
In this article, we address the problem of prolonging the battery life of Internet of Things (IoT) nodes by introducing a smart energy harvesting framework for IoT networks supported by femtocell access points (FAPs) based on the principles of Contract Theory and Reinforcement Learning. Initially, the IoT nodes' social and physical characteristics are identified and captured through the concept of IoT node types. Then, Contract Theory is adopted to capture the interactions among the FAPs, who provide personalized rewards, i.e., charging power, to the IoT nodes to incentivize them to invest their effort, i.e., transmission power, to report their data to the FAPs. The IoT nodes' and FAPs' contract-theoretic utility functions are formulated, following the network economic concept of the involved entities' personalized profit. A contract-theoretic optimization problem is introduced to determine the optimal personalized contracts among each IoT node connected to a FAP, i.e., a pair of transmission and charging power, aiming to jointly guarantee the optimal satisfaction of all the involved entities in the examined IoT system. An artificial intelligent framework based on reinforcement learning is introduced to support the IoT nodes' autonomous association to the most beneficial FAP in terms of long-term gained rewards. Finally, a detailed simulation and comparative results are presented to show the pure operation performance of the proposed framework, as well as its drawbacks and benefits, compared to other approaches. Our findings show that the personalized contracts offered to the IoT nodes outperform by a factor of four compared to an agnostic type approach in terms of the achieved IoT system's social welfare.
Onel L. Alcaraz López, Hirley Alves, Richard Demo Souza, Samuel Montejo‐Sánchez · 6 authors
Recent advances on wireless energy transfer (WET) make it a promising solution for powering future Internet-of-Things (IoT) devices enabled by the upcoming sixth-generation (6G) era. The main architectures, challenges and techniques for efficient and scalable wireless powering are overviewed in this article. Candidates enablers, such as energy beamforming (EB), distributed antenna systems (DASs), advances on devices' hardware and programmable medium, new spectrum opportunities, resource scheduling, and distributed ledger technology are outlined. Special emphasis is placed on discussing the suitability of channel state information (CSI)-limited/free strategies when powering simultaneously a massive number of devices. The benefits from combining DAS and EB, and from using average CSI whenever available, are numerically illustrated. The pros and cons of the state-of-the-art CSI-free WET techniques in ultralow power setups are thoroughly revised, and some possible future enhancements are outlined. Finally, key research directions toward realizing WET-enabled massive IoT networks in the 6G era are identified and discussed in detail.
Xi Lin, Jun Wu, Ali Kashif Bashir, Jianhua Li · 6 authors
Recently, edge artificial intelligence techniques (e.g., federated edge learning) are emerged to unleash the potential of big data from Internet of Things (IoT). By learning knowledge on local devices, data privacy preserving and Quality of Service (QoS) are guaranteed. Nevertheless, the dilemma between the limited on-device battery capacities and the high energy demands in learning is not resolved. When the on-device battery is exhausted, the edge learning process will have to be interrupted. In this article, we propose a novel wirelessly powered edge intelligence (WPEG) framework, which aims to achieve a stable, robust, and sustainable edge intelligence by energy harvesting (EH) methods. First, we build a permissioned edge blockchain to secure the peer-to-peer (P2P) energy and knowledge sharing in our framework. To maximize edge intelligence efficiency, we then investigate the wirelessly powered multiagent edge learning model and design the optimal edge learning strategy. Moreover, by constructing a two-stage Stackelberg game, the underlying energy-knowledge trading incentive mechanisms are also proposed with the optimal economic incentives and power transmission strategies. Finally, simulation results show that our incentive strategies could optimize the utilities of both parties compared with classic schemes, and our optimal learning design could realize the optimal learning efficiency.
Onel L. Alcaraz López, Hirley Alves, Richard Demo Souza, Samuel Montejo‐Sánchez · 6 authors
Recent advances on wireless energy transfer (WET) make it a promising\nsolution for powering future Internet of Things (IoT) devices enabled by the\nupcoming sixth generation (6G) era. The main architectures, challenges and\ntechniques for efficient and scalable wireless powering are overviewed in this\npaper. Candidates enablers such as energy beamforming (EB), distributed antenna\nsystems (DAS), advances on devices' hardware and programmable medium, new\nspectrum opportunities, resource scheduling and distributed ledger technology\nare outlined. Special emphasis is placed on discussing the suitability of\nchannel state information (CSI)-limited/free strategies when powering\nsimultaneously a massive number of devices. The benefits from combining DAS and\nEB, and from using average CSI whenever available, are numerically illustrated.\nThe pros and cons of the state-of-the-art CSI-free WET techniques in ultra-low\npower setups are thoroughly revised, and some possible future enhancements are\noutlined. Finally, key research directions towards realizing WET-enabled\nmassive IoT networks in the 6G era are identified and discussed in detail.\n
Áron Lászka, Abhishek Dubey, Michael Walker, Douglas C. Schmidt
Power grids are undergoing major changes due to rapid growth in renewable\nenergy resources and improvements in battery technology. While these changes\nenhance sustainability and efficiency, they also create significant management\nchallenges as the complexity of power systems increases. To tackle these\nchallenges, decentralized Internet-of-Things (IoT) solutions are emerging,\nwhich arrange local communities into transactive microgrids. Within a\ntransactive microgrid, "prosumers" (i.e., consumers with energy generation and\nstorage capabilities) can trade energy with each other, thereby smoothing the\nload on the main grid using local supply. It is hard, however, to provide\nsecurity, safety, and privacy in a decentralized and transactive energy system.\nOn the one hand, prosumers' personal information must be protected from their\ntrade partners and the system operator. On the other hand, the system must be\nprotected from careless or malicious trading, which could destabilize the\nentire grid. This paper describes Privacy-preserving Energy Transactions\n(PETra), which is a secure and safe solution for transactive microgrids that\nenables consumers to trade energy without sacrificing their privacy. PETra\nbuilds on distributed ledgers, such as blockchains, and provides anonymity for\ncommunication, bidding, and trading.\n