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Hyungyeop Kim, Sungwook Lee, Seungmin Kim, Jinhyeok Lee · 5 authors
No abstract is available for this record.
V. Samuthira Pandi, D Shobana, J Lakshmi Priya, Ala’a Al-Shaikh · 6 authors
Power transfer is a promising new technology Wireless charging networks are being deployed for a RES array, which will be used in electric vehicles, industrial automation, and biomedical implants. Yet, due to power losses, electromagnetic interference, as well as the potential of unauthorized access or malicious attacks, guaranteeing the reliability and security of WPT systems is still a big challenge. Conventional monitoring and defect detection mechanisms need to be more efficient, reactive in real-time, and prone to data tampering. Implementation of the blockchain is a promising usable solution to solve these issues due to decentralized, tamper-proofed and transparent data management characteristics of the technology. At the same time, the research presents results on the implementation of one of the blockchain-oriented technologies in terms of constant control of normal operating conditions and detection of defects in wireless power transfer (WPT) networks, thus improving the efficiency of the operation while ensuring the security of the entire system. This study presents a novel data integrity assurance and autonomous fault detection framework for WPT systems by integrating blockchain with real-time sensor networks and artificial intelligence (AI)-based analytics. Automated Responses: Smart contracts allow automatic reactions when anomalies are detected, minimizing downtime and maintenance costs. Moreover, it enables secure and transparent records of power transactions using distributed ledger technology (DLT), preventing unauthorized access to energy and enhancing accountability of the system. Results of simulation and experimental validation show the gain in defect detection accuracy, reduced fault reporting latency, and improved cyber-attack resilience of blockchain-enabled WPT networks. This research proposes a pioneering model that can utilize blockchain-based monitoring solutions to enhance the design of WPT networks, providing an innovative proof of concept that can address the limitations of such systems. In the future, research directions that address challenges such as optimizing consensus mechanisms specifically for low-power IoT devices and investigate hybrid blockchain models could improve scalability and increase transaction speed to facilitate potential real-world applications of WPT in practical cases.
Neha Deshmukh, Vaishali Khairnar, Deepali Vora, Aleksandar Jovanović · 5 authors
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.
Yifan Zhang, Penghui Lei
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.
Paolo Barucca, Carlo Campajola, Jiahua Xu
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.
Sercan Koc
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.
Maciej Kalka, Marek Kirejczyk
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.
Ida Fuchs, Jayaprakash Rajasekharan, Ümit Cali
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.
Haoxiang Luo, Qianqian Zhang, Gang Sun, Hongfang Yu · 5 authors
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.
Karima Massmi, Khaled Hamouid, Kamel Adi
Electric vehicles (EVs) have gained significant attention due to their environmental and energy-efficient benefits. Dynamic Wireless Charging (DWC) has emerged as one of the most promising EV charging methods because it overcomes the challenges associated with traditional charging stations. However, as EVs keep moving while charging, this requires specific authentication and payment methods, enabling EV mobility privacy and ensuring fair billing. To address these concerns, we propose in this paper a smart contract based solution to deal with privacy and fair billing for EVs dynamic wireless charging. The proposed solution includes a lightweight authentication mechanism enabling a continuous authenticate-and-charge process when EV is moving on the road.
Aparna Kumari, Sudeep Tanwar
Electric Vehicles (EVs) have emerged in smart cities as one of the prominent solutions to improve environmental protection and reduce carbon gas emissions. However, with limited charging stations and battery life, EV owners are not inclined to cover long distances. So, Vehicle-to-Vehicle (V2V) has been introduced lately for energy sharing among EVs through the wireless power transfer (WPT) mechanism in the Internet of EVs (IoEV) environment. But the existing approaches suffered from security and privacy issues along with single-point-of-failure with energy trading between EVs. So, in this paper, we propose a blockchain-based V2V wireless energy sharing scheme, i.e., V2V-ES, to ensure secure transactions among EVs in the WPT process. First, the energy sharing is executed in a clustered IoEV environment, where block generation, validator selection, and PoA consensus processes are performed in every cluster. Next, the Bayesian game-based mechanism is adopted for optimal energy price in the IoEV environment. Here, a linear equilibrium strategy is obtained for optimal pricing that maximizes the utilities of both energy buyer and seller in the energy sharing process and increases social welfare. The game-based pricing is achieved through dedicated smart contracts (SCs) to guarantee trustworthiness, reliability, and security. Finally, the simulation results show the proposed V2V-ES scheme reduces the buyer's costs by 16% and increases the seller's utility by 19%. Moreover, the effectiveness of V2V-ES scheme is compared with benchmark approaches based on various parameters like network latency, system throughput, and optimal transaction price.
Oluleke Babayomi, Babatunde Olubayo, Iheanacho H. Denwigwe, Tobiloba Somefun · 8 authors
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.
Hany Habbak, Mohamed Baza, Mohamed Mahmoud, Khaled Metwally · 6 authors
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.
H. Martins, H. Farias, G. Fenner, Camilo Albeto Sepulveda Rangel · 6 authors
This paper presents a comprehensive model for electric vehicle chargers (EVC) focused on scheduling loads in electric vehicle charging stations (EVCS). It also applies practical information from data gathered by Open Charge Point Protocol (OCPP) for validation of results. The scheduling strategy applies an evolutionary particle swarm optimization (EPSO) metaheuristic to set the hours for charge of the EV. The battery charging model combines the Kinetic Battery Model (KiBaM) and a Voltage Model (VM). A practical validation for the battery model accuracy is made with real data gathered by OCPP. The results showed a good operation for the framework in the EVCS in terms of economic cost and grid impact.. The results also showed a good performance for the battery model. Finally, the OCPP confirmed the results of the model with low errors in terms of performance.
Xin Qi, Keping Yu, Toshio Sato, Kouichi Shibata · 13 authors
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.
Xin Qi, Keping Yu, Toshio Sato, Kouichi Shibata · 13 authors
Low Power Wide Area Network (LPWAN) is an Internet of things (IoT) network layer technology that has emerged in recent years for long-range and low-power communication needs in IoT. Its low-bandwidth, low-power, long-range and mass-connected IoT application features can be well applied to the points transfer system. However, the traditional centralized points transfer system faces many problems such as centralization, high computational requirement of nodes, and low robustness which are difficult to be widely used. In order to solve these problems, we propose a distributed ledger-based points transfer system in LPWAN and analyze the system robustness from the disaster management aspect. The simulation results show that our proposed system can still have strong robustness under extreme disaster situations and ensure the safe and efficient operation of the whole system.
Mahmoud Abouyoussef, Muhammad Ismail
Dynamic wireless charging of electric vehicles (EVs) enables the exchange of power between a mobile EV and the electricity grid via a set of charging pads (CPs) deployed along the road. Accordingly, dynamic charging coordination can be introduced for a group of mobile EVs to specify where each EV can charge (i.e., from which CPs). This coordination mechanism maximizes the satisfied charging requests given the limited available energy supply. Upon specifying the optimal set of pads for a given EV, a fast authentication mechanism is required between the EV and the CPs to start the charging process. However, both the coordination and authentication mechanisms require exchanging private information, e.g., EV identities and locations. Hence, there is a need for a strategy that enables privacy-preservation in dynamic charging via supporting: (i) user anonymity and (ii) data unlinkability. In this paper, we propose a decentralized and scalable networking strategy based on a specially designed private blockchain that can support the privacy requirements of dynamic charging coordination, authentication, and billing. The proposed networking strategy relies on group signature and distributed random number generators to support the desirable features. Simulation results demonstrate the efficiency and low complexity of the proposed blockchain-based networking strategy.
Fisayo Sangoleye, Nafis Irtija, Eirini Eleni Tsiropoulou
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.
Ahmed Barnawi, Shubhani Aggarwal, Neeraj Kumar, Daniyal Alghazzawi · 6 authors
Vehicle-to-grid (V2G) technology is used in the modern eco-friendly environment for demand response management. It helps in reducing the carbon footprints in the environment. However, security and privacy of the information exchange between different entities are significant concerns keeping in view of the information exchange via an open channel, i.e., Internet among different entities such as plug-in hybrid electric vehicles (PHEVs), charging stations (CSs), and controllers in V2G environment. With an exponential rise in Electric vehicles (EVs) usage across the globe, there is a requirement of developing a seamless charging infrastructure for charging and billing. Moreover, secure information flow needs to be maintained at different levels in such an environment. Hence, this paper proposes a blockchain-based demand response management for efficient energy trading between EVs and CSs. In this proposal, miner nodes and block verifiers are selected using their power consumption and processing power. These nodes are responsible for the authentication of various transactions in the proposal. We also proposed a game theory-based solution to support energy management and peak load control off-peak and peak conditions. The proposed scheme has been evaluated using various performance evaluation metrics where its performance is found superior in comparison to the existing solutions in the literature.
Hsin‐Hung Cho, Hsin‐Te Wu, Chin‐Feng Lai, Timothy K. Shih · 5 authors
A wireless rechargeable sensor network was proposed to extend the lifetime of the wireless sensor network. In this article, a charger is combined together with a self-propelled vehicle to provide a more flexible result of charger deployment. The dynamic chargers path selection problem is defined and mapped into the traveling salesman problem. Four metaheuristic algorithms for Internet-of-Things (IoT) applications are designed, and the higher fitness value between the charging path and the number of dead IoT devices is achieved. However, metaheuristic approaches may spend more time on searching solutions so that many IoT devices overuse limited power and fail to be charged for a long time, leading to power exhaustion. In this article, the edge computing technique is applied to accelerate the obtainment of charging paths with the well-defined edge/centralized unit switching. Moreover, to assure the calculated path trustworthy and will not be tampered with, the blockchain technology is adopted. The proposed architecture maintains high-level information credibility while transmitting the information of charging paths within the cloud and edge. The simulation results showed that the proposed method is capable of achieving better charging efficiency and less deployment cost.
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.