Hui Zhao

Bio: Hui Zhao is an academic researcher from Beijing University of Technology. The author has contributed to research in topics: Satellite & Resource allocation. The author has an hindex of 1, co-authored 3 publications receiving 1 citations.

A Blockchain-Enabled Energy-Efficient Data Collection System for UAV-Assisted IoT

Abstract: With the rapid development of Internet of Things (IoT), more and more applications focus on the detection of unmanned areas. With the assistance of unmanned aerial vehicle (UAV), IoT devices are able to access the network via aerial base stations. These UAV-assisted IoT applications still face security and energy challenges. The open environment of IoT applications makes the application easy to encounter external invasion. Limited energy of UAV results in the limited lifetime of network access. To address these challenges, researches on IoT security and energy efficiency are becoming hotspots. Nevertheless, in the UAV continuous coverage scenario, there is still an enormous potential to improve the security and efficiency of data collection in IoT applications. In this article, blockchain is introduced into the scene of UAV-assisted IoT, and a data collection system considering security and energy efficiency is proposed. In this system, UAV, as an edge data collection node, provides a long-term network access for IoT devices through regular cruises with recharging. By forwarding data and recording transactions, UAVs get charging coins as rewards. UAVs use charging coins to exchange charging time. UAV swarm builds distributed ledgers based on blockchain to resist the invasion of malicious UAV. In order to reduce energy consumption, this article designs an adaptive linear prediction algorithm. Through this algorithm, IoT devices upload prediction model instead of original data to greatly reduce in-network transmissions. Simulation results show that the proposed system can effectively improve the security and efficiency of data collection.

On the Aggregated Resource Management for Satellite Edge Computing

Abstract: Geosynchronous Earth Orbit (GEO) satellites, which can relay image data for Low Earth Orbit (LEO) satellites, play an important role in remote sensing. With the development of satellite technologies, the significantly improved computation capabilities of GEO satellites have enabled space service computing, through which GEO satellites can provide data processing services before forwarding to reduce the quantity of transmitted data. In the presence of multiple LEO satellites, how to make effective use of limited communication and computation resources in GEO satellites has become crucial. At present, the research on satellite resource management typically focuses on either communication or computation resources. Existing resource management algorithms are usually of slow convergence speed, which limits their applicability in real-time remote sensing scenarios. Therefore, we propose an aggregated resource management method for remote sensing applications. We first propose models for transmission tasks and processing tasks of remote sensing images. Then we formulate the aggregated resource management for satellite edge computing as a hybrid Stackelberg game and simplify the problem to speed up its convergence speed. Then we propose a distributed resource management algorithm to determine the optimal strategies. Simulation results show that the proposed method can quickly obtain the optimal resource allocation strategy and outperforms typical dynamic iterative algorithms in terms of service quantity and throughput.

Resource management of GEO relays for real-time remote sensing

Abstract: Remote sensing is one of the main applications of satellite communication. With limited communication time between low earth orbit (LEO) sensing satellites and the ground, geostationary orbit (GEO) satellite relaying has become an effective solution. In practical applications, one GEO communication satellite usually needs to provide data forwarding services for multiple satellites or even multiple satellite constellations. Therefore, communication resource management of GEO satellites has become crucial. Existing methods only focus on resource allocation without taking data forwarding task scheduling into consideration, which limits their applicability in real-time applications. In this paper, we propose a real-time resource management approach for GEO relaying, aiming to maximize network throughputs as well as to reduce transmission delays. In this approach, resource allocation is modeled as a Stackelberg game while task scheduling is modeled as a real-time queuing problem. Furthermore, we propose two real-time algorithms, including an adaptive gradient descent method to find optimal price for data forwarding services with low computational complexity, and a queue-jumping algorithm for data forwarding scheduling to minimize transmission delays. With comparison with existing methods, simulations verify the effectiveness of our proposed method with respect to convergence speed of the algorithm, network throughputs, and transmission delays.

Drones’ Edge Intelligence Over Smart Environments in B5G: Blockchain and Federated Learning Synergy

Abstract: Edge Intelligence is an emerging technology which has attracted significant attention. It applies Artificial Intelligence (AI) closer to the network edge for supporting Beyond fifth Generation (B5G) needs. On the other hand, drones can be used as relay station (mobile drone edge intelligence) to gather data from smart environments. Federated Learning (FL) enables the drones to perform decentralized collaborative learning by developing local models, sharing the model parameters with neighbors and the centralized unit to improve global model accuracy in smart environments. However, drone edge intelligence faces challenges such as security and decentralization management, limiting its functions to support green smart environments. Blockchain is a promising technology that enables privacy-preserving data sharing in a distributed manner. There are several challenges that still need to be addressed in blockchain-based applications, such as scalability, energy efficiency, and transaction capacity. Motivated by the significance of FL and blockchain, this survey focuses on the synergy of FL and blockchain to enable drone edge intelligence for green sustainable environments. Moreover, we discuss the combination of FL and blockchain technological aspects, motivation, and framework for green smart environments. Finally, we discuss the challenges and opportunities, and future trends in this domain.

Internet of Things: Security and Solutions Survey

Abstract: The overwhelming acceptance and growing need for Internet of Things (IoT) products in each aspect of everyday living is creating a promising prospect for the involvement of humans, data, and procedures. The vast areas create opportunities from home to industry to make an automated lifecycle. Human life is involved in enormous applications such as intelligent transportation, intelligent healthcare, smart grid, smart city, etc. A thriving surface is created that can affect society, the economy, the environment, politics, and health through diverse security threats. Generally, IoT devices are susceptible to security breaches, and the development of industrial systems could pose devastating security vulnerabilities. To build a reliable security shield, the challenges encountered must be embraced. Therefore, this survey paper is primarily aimed to assist researchers by classifying attacks/vulnerabilities based on objects. The method of attacks and relevant countermeasures are provided for each kind of attack in this work. Case studies of the most important applications of the IoT are highlighted concerning security solutions. The survey of security solutions is not limited to traditional secret key-based cryptographic solutions, moreover physical unclonable functions (PUF)-based solutions and blockchain are illustrated. The pros and cons of each security solution are also discussed here. Furthermore, challenges and recommendations are presented in this work.

Blockchain-Empowered Space-Air-Ground Integrated Networks: Opportunities, Challenges, and Solutions

Abstract: The terrestrial networks face the challenges of severe cost inefficiency and low feasibility to provide seamless services anytime and anywhere, especially in the extreme or hotspot areas (e.g., disaster areas, mountains, and oceans) due to limited service coverage and capacity. The integration of multi-dimensional networks consisting of space, air, and ground layers is expected to provide solutions in delivering cost-effective and ubiquitous Internet of things (IoT) services for billions of users and interconnected smart devices. Autonomous data collection, exchange, and processing across different network segments with minimal human interventions in space-air-ground IoT (SAG-IoT) can bring great convenience to consumers, however, it also suffers new attacks from intruders. Severe privacy invasion, reliability issues, and security breaches of SAG-IoT can hinder its wide deployment. The emerging blockchain holds great potentials to address the security concerns in SAG-IoT, thanks to its prominent features of decentralization, transparency, immutability, traceability, and auditability. Despite of the benefits of blockchain-empowered SAG-IoT, there exist a series of fundamental challenges in terms of efficiency and regulation due to the intrinsic characteristics of SAG-IoT (e.g., heterogeneity, time-variability, and poor interoperability) and the limitations of existing blockchain approaches (e.g., capacity and scalability). This article presents a comprehensive survey of the integration of blockchain technologies for securing SAG-IoT applications. Specifically, we first discuss the architecture, characteristics, and security threats of SAG-IoT systems. Then, we concentrate on the promising blockchain-based solutions for SAG-IoT security. Next, we discuss the critical challenges when integrating blockchain in SAG-IoT security services and review the state-of-the-art solutions. We further investigate the opportunities of blockchain in artificial intelligence and beyond 5G networks and provide open research directions for building future blockchain-empowered SAG-IoT systems.