Qianqian Pan, Jun Wu, Ali Kashif Bashir, Jianhua Li · 6 authors
With the capability of establishing line-of-sight (LoS) links for devices, drones are generally utilized as aerial base stations to construct coexisting drone-terrestrial networks (CDTNs) for wireless communication. However, the established LoS links are easily blocked, thereby severely decreasing transmission performance. The intelligent reflecting surface (IRS) is a promising technology to improve data transmission in the CDTN by programming propagation channels. However, secure IRS reflection resource allocation is still an open issue. Existing IRS resource allocation methods are mainly based on a centralized third party and are vulnerable to the single point of failure. Furthermore, intelligent allocation of IRS reflection resources is also a key issue. To solve these problems, we propose a blockchain and artificial intelligence (AI) enabled configurable reflection resource allocation approach for the IRS-aided CDTN. First, we establish the IRS-aided communication framework for the CDTN, where a drone-mounted IRS is introduced to improve spatial freedom for data transmission. Second, the blockchain-based reflection resource management mechanism is proposed. In this mechanism, we design allocation transactions, the hierarchical blockchain structure, and smart-contract-enabled resource trading. Third, the AI-based reflection resource allocation mechanism is proposed, including the intelligent reflection elements assignment and deep-reinforcement-learning-driven reflection coefficient configuration. Furthermore, experimental results verify the effectiveness of our proposed approach. Finally, open issues and key challenges of the proposed approach are discussed.
On the Internet of Battlefield Things (IoBT), unmanned aerial vehicles (UAVs) provide significant operational advantages. However, the exploitation of the UAV by an untrustworthy entity might lead to security violations or possibly the destruction of crucial IoBT network functionality. The IoBT system has substantial issues related to data tampering and fabrication through illegal access. This paper proposes the use of an intelligent architecture called IoBT-Net, which is built on a convolution neural network (CNN) and connected with blockchain technology, to identify and trace illicit UAV in the IoBT system. Data storage on the blockchain ledger is protected from unauthorized access, data tampering, and invasions. Conveniently, this paper presents a low complexity and robustly performed CNN called LRCANet to estimate AOA for object localization. The proposed LRCANet is efficiently designed with two core modules, called GFPU and stacks, which are cleverly organized with regular and point convolution layers, a max pool layer, and a ReLU layer associated with residual connectivity. Furthermore, the effectiveness of LRCANET is evaluated by various network and array configurations, RMSE, and compared with the accuracy and complexity of the existing state-of-the-art. Additionally, the implementation of tailored drone-based consensus is evaluated in terms of three major classes and compared with the other existing consensus.
Abdullah Ayub Khan, Asif Ali Laghari, Muhammad Shafiq, Shafique Ahmed Awan · 5 authors
Due to globalization and advances in network technology, the Internet of Vehicles (IoV) with edge computing has gained increasingly more attention over the last few years. The technology provides a new paradigm to design interconnected distributed nodes in Unmanned Aerial Vehicle (UAV)-assisted vehicle networks for communications between vehicles in smart cities. The process hierarchy of the current UAV-assisted networks is also becoming more multifaceted as more vehicles are connected, requiring accessing and exchanging information, performing tasks, and updating information securely. This poses serious issues and limitations to centralized UAV-assisted vehicle networks, directly affecting computing-intensive tasks and data offloading. This paper bridges these gaps by providing a novel, transparent, and secure lifecycle for UAV-assisted distributed vehicle communication using blockchain hyperledger technology. A modular infrastructure for Vehicle-to-Everything (V2X) is designed and ‘B-UV2X’, a blockchain hyperledger fabric-enabled distributed permissioned network-based consortium structure, is proposed. The participating nodes of the vehicle are interconnected with others in the chain of smart cities and exchange different information such as movement, etc., preserving operational logs on the blockchain-enabled immutable ledger. This automates IoV transactions over the proposed UAV-assisted vehicle-enabled consortium network with doppler spread. Thus, for this purpose, there are four different chain codes that are designed and deployed for IoV registration, adding new transactions, updating the ledger, monitoring resource management, and customized multi-consensus of proof-of-work. For lightweight IoV authentication, B-UV2X uses a two-way verification method with the defined hyperledger fabric consensus mechanism. Transaction protection from acquisition to deliverance and storage uses the NuCypher threshold proxy re-encryption mechanism. Simulation results for the proposed B-UV2X show a reduction in network consumption by 12.17% compared to a centralized network system, an increase in security features of up to 9.76%, and a reduction of 7.93% in the computational load for computed log storage.
With the rapid technological development of robust and intelligent UAVs (Unmanned Aerial Vehicles), typically referred to as drones, much opportunities have emerged to provide DraaS (Drone-as-a-Service) to help industries such as agriculture, energy and utilities, GIS, package delivery, cinematography, industrial inspection and many more. The capability of drones to lift payload, acquire data with camera and sensors mounted on it make drones as a useful tool for various commercial applications. However, there exist great challenges for executing autonomous missions, operations, management, ensuring safety and secure communications. In this research paper, we review the latest research in the field of Artificial Intelligence and Blockchain applied for DraaS. Blockchain being a distributed ledger protects the shared data using cryptography techniques such as hash functions and public key encryption. It can also be used for assuring the truthfulness of the information stored and for improving the security and transparency of the UAVs. The integration of AI contributes more intelligence to the system enabling informed decision making and eventually converting drones into vehicles capable of executing autonomous missions in the real-world.
Sana Hafeez, Mahmoud A. Shawky, Mohammad Al-Quraan, Lina Mohjazi · 6 authors
Unmanned aerial vehicles (UAV), an emerging architecture that embodies flying ad-hoc networks, face critical privacy and security challenges, mainly when engaged in data-sensitive missions. Therefore, message authentication is a crucial security feature for drone communication. This paper presents a Blockchain-based Efficient, and Trusted Authentication scheme for UAV communication BETA-UAV, which exploits the inherent properties of blockchain technology concerning memorability and immutable to record communication sessions via transaction using a smart contract. The smart contract in BETA-UAV allows participants to publish and call transactions from the blockchain network. Furthermore, the transaction addresses are proof of freshness and trustworthiness for subsequent transmissions. Furthermore, we investigate the ability to resist active attacks, e.g., impersonation, replaying, and modification. In addition, we evaluate the gas costs associated with the smart contract's functions by implementing BETA-UAV on the Ethereum public blockchain. Comparing computation and communication over-heads shows that the proposed approach can save significant costs over traditional techniques.
In a space-air-ground integrated network (SAGIN), managing resources for the growing number of highly-dynamic and heterogeneous radios is a challenging task. Symbiotic communication (SC) is a novel paradigm, which leverages the analogy of the natural ecosystem in biology to create a radio ecosystem in wireless networks that achieves cooperative service exchange and resource sharing, i.e., service/resource trading, among numerous radios. As a result, the potential of symbiotic communication can be exploited to enhance resource management in SAGIN. Despite the fact that different radio resource bottlenecks can complement each other via symbiotic relationships, unreliable information sharing among heterogeneous radios and multi-dimensional resources managing under diverse service requests impose critical challenges on trusted trading and intelligent decision-making. In this article, we propose a secure and smart symbiotic SAGIN (S^4) framework by using blockchain for ensuring trusted trading among heterogeneous radios and machine learning (ML) for guiding complex service/resource trading. A case study demonstrates that our proposed S^4 framework provides better service with rational resource management when compared with existing schemes. Finally, we discuss several potential research directions for future symbiotic SAGIN.
Recently, the usage of blockchain on swarm UAV applications has gained popularity due to the simplicity and security of the designed frameworks. Applications of drones to precision architecture have also been a prominent research topic for years. However, architectures that use drones as a service (DAAS) for such applications are still lacking some detailed analysis. This paper addresses the known problems and challenges of swarm UAV networks, such as availability, route de-confliction, confidentiality and authenticity, and energy consumption. It presents a conceptual solution and architecture for blockchain and computer vision-assisted precision agriculture applications of swarm UAVs through a combination of early designs of agriculture-specific system components and methods adapted from proposed frameworks for other fields in the industry.
Several advanced features exist in fifth-generation (5G) correspondence than in fourth-generation (4G) correspondence. Centric cloud-computing architecture achieves resource sharing and effectively handles big data explosion. For data security problems, researchers had developed many methods to protect data against cyber-attacks. Only a few solutions are based on blockchain (BC), but are affected by expensive storage costs, network latency, confidence, and capacity. Things are represented in digital form in the virtual cyberspace which is the major responsibility of the communication model based on cybertwin. A novel cybertwin-based UAV 6G network architecture is proposed with new concepts such as cloud operators and cybertwin in UAV. Here, IoE applications have to be energy aware and provide scalability with less latency. A novel Compute first networking (CFN) framework named secure blockchain-based UAV communication (BC-UAV) is designed which offers network services such as computing, caching, and communication resources. The focus of the blockchain was to improve the security in the cloud using hashing technique. Edge clouds support core clouds to quickly respond to user requests.
Rapid advancements in the fifth generation (5G) communication technology and mobile edge computing (MEC) paradigm have led to the proliferation of unmanned aerial vehicles (UAV) in urban air mobility (UAM) networks, which provide intelligent services for diversified smart city scenarios. Meanwhile, the widely deployed Internet of drones (IoD) in smart cities has also brought up new concerns regarding performance, security, and privacy. The centralized framework adopted by conventional UAM networks is not adequate to handle high mobility and dynamicity. Moreover, it is necessary to ensure device authentication, data integrity, and privacy preservation in UAM networks. Thanks to its characteristics of decentralization, traceability, and unalterability, blockchain is recognized as a promising technology to enhance security and privacy for UAM networks. In this paper, we introduce LightMAN, a lightweight microchained fabric for data assurance and resilience-oriented UAM networks. LightMAN is tailored for small-scale permissioned UAV networks, in which a microchain acts as a lightweight distributed ledger for security guarantees. Thus, participants are enabled to authenticate drones and verify the genuineness of data that are sent to/from drones without relying on a third-party agency. In addition, a hybrid on-chain and off-chain storage strategy is adopted that not only improves performance (e.g., latency and throughput) but also ensures privacy preservation for sensitive information in UAM networks. A proof-of-concept prototype is implemented and tested on a micro-air–vehicle link (MAVLink) simulator. The experimental evaluation validates the feasibility and effectiveness of the proposed LightMAN solution.
Dena Mahmudnia, Mehrdad Arashpour, Yu Bai, Haibo Feng
Central management of fire stations and traditional optimization strategies are vulnerable to response time, a single point of failure, workload balancing, and cost problems. This is further intensified by the absence of modern communication systems and a comprehensive management framework for firefighting operations. These problems motivate the use of new technologies such as unmanned aerial vehicles (UAVs) with the capability to transport extinguishing materials and reach remote zones. Forest fire management in remote regions can also benefit from blockchain technology (BC) due to the facilitation of decentralization, tamper-proofing, immutability, and mission recording in distributed ledgers. This study proposed an integrated drone-based blockchain framework in which the network users or nodes include drones, drone controllers, firefighters, and managers. In this distributed network, all nodes can have access to data; therefore, the flow of data exchange is smooth and challenges on spatial distance are minimized. The research concluded with a discussion on constraints and opportunities in integrating blockchain with other new technologies to manage forest fires in remote regions.
Autonomous inspection and measurement have become an integral part of smart IoT ecosystem. Low cost mobile and static sensing devices have leveraged the concept of smart factory in different industries such as healthcare, manufacturing, transportation etc. However, in case of remote sensing where the sensing devices are at distant locations it becomes infeasible for the central data aggregator or control center to evaluate the integrity and authenticity of the sensing data. This situation becomes even worse in case of compromised sensing devices due to cyber-attacks such as forged identity, spoofing, false data injection etc. This work in progress paper proposes a novel idea for blockchain based distributed sensing data aggregation scheme for UAV swarms. This distributed system could detect the malicious actors (sensors) without the intervention of central authority and thus enhances the integrity of the sensing data. In order to eliminate the payloads on the on-board UAVs, we have leveraged the storage capacity of the network edge components for storing the blockchain ledger of the network. We also explored and developed different threat models for UAV information acquisition networks.
Mohtasin Golam, Rubina Akter, Esmot Ara Tuli, Dong‐Seong Kim · 5 authors
Unmanned aerial vehicles (UAVs) offer important strategic advantages in the Internet of Military Things (IoMT). On the other hand, the use of the UAV by an untrusted party may threaten security and perhaps endanger the vital operation of the IoMT network. The IoMT network additionally faces significant challenges from data falsification and manipulation through unauthorised access. For the purpose of addressing these challenges, this research presents a blockchain-based architecture and user authentication mechanism for the purpose of identifying and keeping track of unauthorized UAVs in the IoMT network. Blockchain technology not only stores data on the central control server but also forbids unauthorized access, data manipulation, and illegal intrusions. Additionally, a unique consensus model for UAV communication has been created. By streamlining the resource-constrained mining process, the created consensus can improve the efficiency of blockchain transactions between UAVs.
In recent years, with the continuous development of UAV technology, the application of the UAV swarm in the military has been a global focus of research. Although it can bring a series of benefits in autonomous cooperation, the traditional UAV management technology is prone to hacker attacks due to many security issues, such as a single point of failure brought by centralized management and the lack of reliable identity authentication. This paper studies the advantages and the recent advances of the blockchain in UAV swarm, proposes a blockchain-based UAV swarm identity management model (B-UIM-M), and establishes a distributed identity authentication scheme based on the distributed identity identifier (DID) under this model. Moreover, to ensure the safe transmission of UAV communication data, a secure communication architecture based on blockchain and a set of secure transmission protocols were designed, combined with cryptography. In the current military field, there is no similar application case of the UAV swarm identity management model and distributed identity authentication. The feasibility and security of the proposed scheme are proved through experiments and security analyses.
Drone-based systems supporting Search and Rescue (SAR) missions help expeditiously improve the possibility of discovering the missing victims. Nonetheless, the current drone-based systems have some limitations, such as the need for humans in control of large-scale drones, drone’s energy inefficiency, repercussion of quality of service (QoS) from abnormalities events, shortages of automaticity and real-time interactions, deficiency of swift decisions from artificial intelligence-based SAR, and underestimation of security issues in SAR systems. Therefore, developing a more advanced drone-based system is necessary to overcome these limitations. However, it is challenging to achieve the target due to trade-off relationships of technologies and strict requirements of time-critical SAR. This paper studies the feasibility of an Internet-of-Drones (IoD) system using blockchain and artificial intelligence at the edge to overcome limitations and improve SAR QoS. An advanced IoD system architecture from drones to a back-end system and end-users terminals has been proposed. Furthermore, advanced edge services and artificial intelligence at the edge have been presented for automatically searching for missing persons. In addition, computation offloading approaches have been provided to improve the energy efficiency of drones and reduce system latency. Last but not least, public and private blockchain, including Ethereum and Hyperledger Fabric, for providing secure and decentralized healthcare platform has been investigated and analyzed to enable real-time interaction between healthcare entities and improves healthcare services. The results show that the proposed system helps overcome the limitations and improve the SAR QoS. Besides, the proposed system satisfies the security requirements, including confidentiality, integrity, authentication, authorization, access control, privacy, trust, transparency, availability, automaticity, and tolerance.
Unmanned Aerial Vehicle (UAV) is a promising technology that can serve as aerial base stations to assist Internet of Things (IoT) networks, solving various problems such as extending network coverage, enhancing network performance, transferring energy to IoT devices (IoTDs), and perform computationally-intensive tasks of IoTDs. Heterogeneous IoTDs connected to IoT networks have limited processing capability, so they cannot perform resource-intensive activities for extended periods. Additionally, IoT network is vulnerable to security threats and natural calamities, limiting the execution of real-time applications. Although there have been many attempts to solve resource scarcity through computational offloading with Energy Harvesting (EH), the emergency and vulnerability issues have still been under-explored so far. This paper proposes a blockchain and multi-agent deep reinforcement learning (MADRL) integrated framework for computation offloading with EH in a multi-UAV-assisted IoT network, where IoTDs obtain computing and energy resources from UAVs. We first formulate the optimization problem as the joint optimization problem of computation offloading and EH problems while considering the optimal resource price. And then, we model the optimization problem as a Stackelberg game to investigate the interaction between IoTDs and UAVs by allowing them to continuously adjust their resource demands and pricing strategies. In particular, the formulated problem can be addressed indirectly by a stochastic game model to minimize computation costs for IoTDs while maximizing the utility of UAVs. The MADRL algorithm solves the defined problem due to its dynamic and large-dimensional properties. Finally, extensive simulation results demonstrate the superiority of our proposed framework compared to the state-of-the-art.
In the future era of intelligent networks, communication technology and network architecture need to be further developed to provide users with high-quality services. The Space-Air-Ground Integrated Networks (SAGIN) is seen as a potential architecture to provide ubiquitous communication and drive the era of the intelligent global network. The space and air segments in SAGIN can assist in offloading traffic from the ground segment. However, in a highly dynamic and heterogeneous network like SAGIN, offloading decisions are easily affected by the incorporated/malicious nodes. How to ensure security and improve network performance becomes a critical problem. In this paper, we address the above problem by jointly using blockchain and federated reinforcement learning (FRL). Firstly, we propose a blockchain-based secure federated learning framework that combines topology information chain and model chain to assist traffic offloading. Then, we propose a node security evaluation and an enhanced practical byzantine fault tolerance (EPBFT) algorithm to secure the traffic offloading process. Furthermore, we describe the traffic offloading problem as a Markov decision problem (MDP) and employ the Blockchain-based Federated Asynchronous Advantage Actor-Critic (BFA3C) algorithm to solve this problem. Finally, the simulation results show that the BFA3C-based algorithm used in SAGIN with/without malicious nodes achieves superior performance in terms of latency and security.
Underwater drones have found a place in oceanography, oceanic research, bathymetric surveys, military, surveillance, monitoring, undersea exploration, mining, commercial diving, photography and several other activities. Drones housed with several sensors and complex propulsion systems help oceanographic scientists and undersea explorers to map the seabed, study waves, view dead zones, analyze fish counts, predict tidal wave behaviors, aid in finding shipwrecks, building windfarms, examine oil platforms located in deep seas and inspect nuclear reactors in the ship vessels. While drones can be explicitly programmed for specific missions, data security and privacy are crucial issues of serious concern. Blockchain has emerged as a key enabling technology, amongst other disruptive technological enablers, to address security, data sharing, storage, process tracking, collaboration and resource management. This study presents a comprehensive review on the utilization of Blockchain in different underwater applications, discussing use cases and detailing benefits. Potential challenges of underwater applications addressed by Blockchain have been detailed. This work identifies knowledge gaps between theoretical research and real-time Blockchain integration in realistic underwater drone applications. The key limitations for effective integration of Blockchain in real-time integration in UUD applications, along with directions for future research have been presented.
The Internet of Drones (IoD) ecosystem consists of many interlinked commercial services provided by a network of drones. The advent of 6G networks plays a crucial role in increasing the feasibility of the IoD ecosystem. This ecosystem's sheer size and low computational efficiency create challenges in maintaining compliance and control. The 6G IoD ecosystem can incorporate a blockchain-based multi layered compliance and control system to solve the significant trust and authentication issues. Implementing authentication mechanisms and UAV-user identity data in the blockchain layer can preserve the integrity of these authentication mechanisms. This paper proposes a novel Multi Layered Blockchain assisted 6G Internet of Drones (MLB-IoD) ecosystem that augments the IoD ecosystem with secure control and compliance mechanisms. The MLB-IoD ecosystem consists of the novel Global Compliance System (GCoS) and the Swarm Security (SSe) system as its constituents. The GCoS assures drone takeoff compliance and optimally permissible route planning, while the SSe system provides intelligent swarm access control mechanisms. The analysis of the proposed MLB-IoD ecosystem reveals it to be highly secure against authentication based and cryptological attacks. Further, the simulation results show that the location-compliance based path planning module in the GCoS reduces the average flight time for UAVs by 18.37%.
Yu Han, Xiaolei Wang, Yi Zhang, Gang Yang · 5 authors
In the context of the development of UAVs towards clustering, intelligence, and autonomy, it is necessary to ensure that multiple UAVs and ground control stations can communicate and share information securely in real-time so that UAV swarms can make real-time and effective decisions and collaborations. These factors pose challenges to the security, robustness, and operational efficiency of UAV swarm communication networks. This paper combines blockchain technology with a UAV swarm communication network, proposes a new UAV swarm communication network architecture based on consortium blockchain, and describes the network structure and transaction process in detail. The performance analysis shows that the security mechanism of the architecture can meet the security requirements of the UAV swarm communication network. And this solution is superior to existing solutions based on blockchain technology such as Ethereum in performance and is a technical solution with both security and usability.
Sana Javed, Muhammad Asghar Khan, Ako Muhammad Abdullah, Amjad Alsirhani · 7 authors
The Internet of Drones (IoD) has recently gained popularity in several military, commercial, and civilian applications due to its unique characteristics, such as high mobility, three-dimensional (3D) movement, and ease of deployment. Drones, on the other hand, communicate over an unencrypted wireless link and have little computational capability in a typical IoD environment, making them exposed to a wide range of cyber-attacks. Security vulnerabilities in IoD systems include man-in-the-middle attacks, impersonation, credential leaking, GPS spoofing, and drone hijacking. To avoid the occurrence of such attacks in IoD networks, we need an extremely powerful security protocol. To address these concerns, we propose a blockchain-based authentication scheme employing Hyperelliptic Curve Cryptography (HECC). The concepts of a blockchain as a Certificate Authority (CA) and a transaction as a certificate discussed in this article are meant to facilitate the use of a blockchain without CAs or a Trusted Third Party (TTP). We offer a security analysis of the proposed scheme, which demonstrates its resistance to known and unknown attacks. The proposed scheme resists replay, man-in-the-middle, device impersonation, malicious device deployment, Denial-of-Service (DoS), and De-synchronization attacks, among others. The security and performance of the proposed scheme are compared to relevant existing schemes, and their performance is shown to be better in terms of security attributes as well as computation and communication costs than existing competitive schemes. The total computation cost of the proposed scheme is 40.479 ms, which is 37.49% and 49.79% of the two comparable schemes. This shows that the proposed scheme is better suited to the IoD environment than existing competitive schemes.
The vast majority of 5G users are in eMBB content which requires high bandwidth and moderate latency under a few milliseconds. Today's applications are irregular and not predictable and current fixed wireless access cannot meet these requirements of eMBB traffic. This leads to the use of unmanned aerial vehicles (UAVs) as mobile base stations to increase the capacity of physical infrastructure. However; due to serving eMBB users, the replacement of UAVs for recharging becomes frequent. There are many studies proposing to increase the serving time without any replacement in the literature. Due to the economic limitations of service providers, they prefer partial recovery on the topology. All of these leads use UAV as a service between multi-providers by hiring it from infrastructure on-demand. On the other hand, security is an urgent requirement of 5G while integrating multi-providers. Therefore, this paper proposes blockchain-assisted UAV as a service to handle the smart contracts between providers and UAVs in exchange for UAV-Coin. Thanks to that, multi-providers can hire a UAV on-demand to enhance network capacity without any full recovery on the physical topology. This is implemented by using edge servers that execute UAV, Content, and Database manager modules, respectively. The proof algorithm for blockchain-assisted UAVaaS is proposed. Here, the Proof of Stake (PoS) is preferred for the validation of transactions and adding them into a blockchain in order to meet the latency requirement of eMBB content. According to performance evaluation, the blockchain can be used by up to 10 service providers while considering the processing delay. Moreover, the service providers can earn much more UAV-Coin by being selected as a winner more than once for validation in proof of algorithm.
Mohamed Torky, M. A. El-Dosuky, Essam Goda, Václav Snåšel · 5 authors
Unmanned aerial vehicles (UAVs) have emerged as a powerful technology for introducing untraditional solutions to many challenges in non-military fields and industrial applications in the next few years. However, the limitations of a drone’s battery and the available optimal charging techniques represent a significant challenge in using UAVs on a large scale. This problem means UAVs are unable to fly for a long time; hence, drones’ services fail dramatically. Due to this challenge, optimizing the scheduling of drone charging may be an unusual solution to drones’ battery problems. Moreover, authenticating drones and verifying their charging transactions with charging stations is an essential associated problem. This paper proposes a scheduling and secure drone charging system in response to these challenges. The proposed system was simulated on a generated dataset consisting of 300 drones and 50 charging station points to evaluate its performance. The optimization of the proposed scheduling methodology was based on the particle swarm optimization (PSO) algorithm and game theory-based auction model. In addition, authenticating and verifying drone charging transactions were executed using a proposed blockchain protocol. The optimization and scheduling results showed the PSO algorithm’s efficiency in optimizing drone routes and preventing drone collisions during charging flights with low error rates with an MAE = 0.0017 and an MSE = 0.0159. Moreover, the investigation to authenticate and verify the drone charging transactions showed the efficiency of the proposed blockchain protocol while simulating the proposed system on the Ethereum platform. The obtained results clarified the efficiency of the proposed blockchain protocol in executing drone charging transactions within a short time and low latency within an average of 0.34 s based on blockchain performance metrics. Moreover, the proposed scheduling methodology achieved a 96.8% success rate of drone charging cases, while only 3.2% of drones failed to charge after three scheduling rounds.
Internet of Things (IoT)-inspired drone environment is having a greater influence on daily lives in the form of drone-based smart electricity monitoring, traffic routing, and personal healthcare. However, communication between drones and ground control systems must be protected to avoid potential vulnerabilities and improve coordination among scattered UAVs in the IoT context. In the current paper, a distributed UAV scheme is proposed that uses blockchain technology and a network topology similar to the IoT and cloud server to secure communications during data collection and transmission and reduce the likelihood of attack by maliciously manipulated UAVs. As an alternative to relying on a traditional blockchain approach, a unique, safe, and lightweight blockchain architecture is proposed that reduces computing and storage requirements while keeping privacy and security advantages. In addition, a unique reputation-based consensus protocol is built to assure the dependability of the decentralized network. Numerous types of transactions are established to characterize diverse data access. To validate the presented blockchain-based distributed system, performance evaluations are conducted to estimate the statistical effectiveness in the form of temporal delay, packet flow efficacy, precision, specificity, sensitivity, and security efficiency.
Paola Torrico Morón, Salma Salimi, Jorge Peña Queralta, Tomi Westerlund
Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in ad-hoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. With larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.