Article
Environmental Sciences
Fatima Zahra Ainou, Mohsin Ali, Muhammad Sadiq
Summary: Morocco is an energy-deficient country that heavily relies on energy imports to support its growing economy. Energy consumption in Morocco is expected to increase significantly due to population growth, putting more pressure on the energy system. To address energy security concerns, Morocco launched the National Energy Strategy, aiming to increase the share of renewable energy in its generation mix. However, the country's energy security performance has declined in recent years, mainly due to increased energy imports and prices, as well as low energy efficiency.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Hardware & Architecture
Hao Yuan, Guoming Tang, Teng Liang, Deke Guo, Yi Wang
Summary: This article proposes a many-to-many power supply architecture for base stations, grouping multiple renewable energy generators into virtual cells to serve multiple stations and maximize renewable energy utilization. Software-defined techniques are used to control energy storage systems and eliminate power mismatches between supply and demand. Illustrative results from a case study show high renewable energy utilization with this proposed architecture and mechanisms.
Article
Green & Sustainable Science & Technology
Xiangdong Zhang, Gunasekaran Manogaran, BalaAnand Muthu
Summary: This article discusses the planning and evaluation methods for smart city energy systems, introducing the creation process of complex systems using diverse energy technologies network.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Energy & Fuels
Yongwang Zhang, Wanjiang Wang, Zhe Wang, Meng Gao, Litong Zhu, Junkang Song
Summary: This article discusses how to improve the quality of buildings and promote low energy consumption, green, ecological, and sustainable building development by developing green buildings and using renewable energy such as solar energy in light of global warming, environmental degradation, and energy resource shortage issues.
Article
Economics
Cong Wang
Summary: The COVID-19 pandemic has hindered energy transition and raised concerns about prioritizing green economic recovery. This study assesses the green economic development in Chinese urban areas, proposes a low-carbon energy transition plan for the post-pandemic age, and analyzes the interplay between energy transition and COVID-19 globally. Barriers to a smooth energy transition during the pandemic, such as governmental support, carbon fuel divestment, renewable generation capacity, global distribution chain, and energy poverty, are examined. The study also identifies windows of opportunity for energy transition created by the pandemic, considering cost-effectiveness, policy execution efficacy, and renewable energy.
ECONOMIC CHANGE AND RESTRUCTURING
(2023)
Article
Environmental Sciences
Mirza Huzaifa Asif, Tan Zhongfu, Azer Dilanchiev, Muhammad Irfan, Elchin Eyvazov, Bilal Ahmad
Summary: This research focuses on the adoption of renewable energy by Pakistani consumers using solar panels and finds that factors such as value orientation, utilitarian benefits, collectivism, reason for adoption, and attitude towards renewable energy significantly influence adoption intention. The study also reveals that customer attitudes towards renewable energy positively impact their intention to use it.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Qi-Cheng Yang, Mingbo Zheng, Chun-Ping Chang
Summary: This research examines the impact of renewable energy policies on renewable energy green innovation, using panel data from 102 countries. The study finds a positive correlation between green innovation and national renewable energy policies, but the influence is weaker in countries with lower innovation capacity.
Article
Environmental Sciences
Feina Fu, Sana Ullah
Summary: In recent times, the concept of green growth has emerged as a critical factor in controlling the environmental impact of economic activities. This study focuses on the asymmetric impact of green finance investment, technological progress, and renewable energy on green growth in China.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Energy & Fuels
Margot Deruyck, Silvia Bova, Greta Vallero, Michela Meo, Luc Martens, Wout Joseph
Summary: This paper investigates the use of renewable energy sources for wireless access networks and proposes an optimized algorithm to reduce costs. The study shows that wind energy is the most suitable option and the optimized multiple RES system performs the best.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Chemistry, Analytical
Sandrine Mukase, Kewen Xia, Abubakar Umar, Eunice Oluwabunmi Owoola
Summary: This paper investigates the charging process of a wireless energy transfer-based wireless sensor network and proposes a periodic charging scheme. By introducing minimum energy level and threshold energy level, efficient energy management can be achieved, resulting in reduced total energy consumption and distance traveled by the charging device.
Article
Green & Sustainable Science & Technology
Shuguang Wang, Luang Sun, Sajid Iqbal
Summary: The study highlights the importance of renewable energy dependence in facilitating energy transition in E7 settings. Factors such as renewable energy demand and supply ratio, energy consumption to GDP ratio are crucial in promoting renewable energy transition through green financing. The shift towards renewable energy in E7 economies is partly attributed to investments in renewable energy sources supported by green finance.
Article
Economics
Larissa Fait, Elke D. Groh, Heike Wetzel
Summary: This study investigates the choice of electricity contracts and finds that environmental and regional identity significantly influence the willingness to pay for regional and green electricity. Additionally, it is found that about 40% of individuals choose the greenest electricity mix when selecting an electricity contract. The use of decision heuristics based on regional contract characteristics is less frequent but increases when regional identity is salient.
Article
Telecommunications
Turgay Pamuklu, Cem Ersoy
Summary: The article introduces a new model, GROVE, which integrates function splitting, Radio over Ethernet, and the use of renewable energy sources in C-RAN to maximize its benefits while maintaining economic feasibility. The quadratic routing decision constraints are linearized and solved with a mixed-integer linear programming (MILP) solver to minimize operational expenditure. Results show that combining routing, function splitting, and RES decisions is cost-effective and outperforms classical disjoint approaches. Network scalability analysis is also provided to determine the limits of the MILP solver for larger network topologies.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2021)
Review
Chemistry, Analytical
J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio, Andres Suarez-Gonzalez, Miguel Rodriguez-Perez, M. Estrella Sousa-Vieira
Summary: The article surveys the issue of energy balancing in Wireless Sensor Networks, focusing on three key areas: energy conservation techniques, energy-harvesting techniques, and energy transfer techniques. The main contributions in these areas and trending topics in recent research are identified. Discussion on future directions is also included.
Article
Environmental Sciences
Lianfeng Xia, Yujia Liu, Xu Yang
Summary: This research examines the impact of green finance, environmental regulations, income, urbanization, and waste management on renewable energy generation in 29 provinces in China from 2000 to 2020. The study finds that environmental taxes, green finance index, income, urbanization, and waste management positively influence renewable energy investment, and different measures of green finance also contribute to it.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Jingcai Guo, Song Guo, Shiheng Ma, Yuxia Sun, Yuanyuan Xu
Summary: This research focuses on the recognition of both known and unknown malware families, and proposes a new model that uses generative adversarial networks to synthesize malware instances to better train the classifier and improve recognition performance. Additionally, a large-scale malware dataset (MAL-100) is built to address the lack of existing benchmark datasets.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jing Li, Weifa Liang, Yuchen Li, Zichuan Xu, Xiaohua Jia, Song Guo
Summary: Mobile Edge Computing (MEC) is a promising paradigm that offloads compute-intensive tasks to MEC networks, providing high-performance processing for mobile applications. This study focuses on the acceleration of DNN inference in MEC networks through DNN partitioning and multi-thread execution parallelism. The research develops novel algorithms for maximizing the number of delay-aware DNN service requests admitted, both in offline and online scenarios. Experimental simulations demonstrate the promising performance of the proposed algorithms.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Chao Wang, Chunxiao Jiang, Jingjing Wang, Shigen Shen, Song Guo, Peiying Zhang
Summary: This article proposes a blockchain-enabled resource orchestration scheme for IoT using deep reinforcement learning. The scheme allows the IoT edge server and end user to reach a consensus on network resource allocation based on blockchain theory. By utilizing a policy network, the intelligent agent can perceive changes in the network's state and make dynamic resource allocation decisions. Simulation results demonstrate that the proposed scheme performs better than other security resource allocation algorithms, with average revenue, user request acceptance rate, and profitability increased by 8.5%, 1.8%, and 11.9%, respectively.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Jie Zhang, Song Guo, Jingcai Guo, Deze Zeng, Jingren Zhou, Albert Y. Zomaya
Summary: This paper proposes a novel training framework that achieves data-independent knowledge transfer by using distributed generative adversarial networks (GANs) in order to enable collaborative learning of models in federated learning. By deploying a lightweight and efficient distributed GAN between the server and clients, synthetic global feature representations can be automatically generated for model training and distillation.
IEEE TRANSACTIONS ON COMPUTERS
(2023)
Article
Computer Science, Information Systems
Xiaojie Wang, Zhaolong Ning, Lei Guo, Song Guo, Xinbo Gao, Guoyin Wang
Summary: This paper investigates a practical scenario with multiple Service Providers (SPs) managing servers of different capacities and prices in the context of blockchain. It proposes a learning-based offloading algorithm that integrates Deep Reinforcement Learning (DRL) and Mean Field Theory (MFT) to maximize utilities of miners. Theoretical and performance results demonstrate the superiority of the proposed algorithm in terms of average miner utilities and algorithm convergence time compared to other representative algorithms.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Yuchen Li, Weifa Liang, Jing Li, Xiuzhen Cheng, Dongxiao Yu, Albert Y. Zomaya, Song Guo
Summary: The rise of deep learning brings new vitality to the future of intelligent IoT, and the emergence of edge intelligence enables real-time DNN inference services for mobile users. To ensure efficient and secure DNN model training in edge computing, federated learning is proposed as an ideal learning paradigm. This article focuses on energy-aware DNN model training in edge computing and proposes an algorithm to optimize the global loss of the training model while considering bandwidth and energy constraints.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Computer Science, Theory & Methods
Rongxin Han, Dezhi Chen, Song Guo, Jingyu Wang, Qi Qi, Lu Lu, Jianxin Liao
Summary: This article focuses on the parallel deployment of multi-service providers (SPs) in network slicing in the edge network. It proposes a multi-SP network slicing mechanism using multi-agent deep reinforcement learning to solve resource conflicts through network resource coordination. It demonstrates scalability and fast model convergence in dealing with dynamic edge networks.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Hao Dong, Cunqing Hua, Lingya Liu, Wenchao Xu, Song Guo, Rahim Tafazolli
Summary: This paper investigates the spectrum sharing problem in integrated terrestrial satellite networks and proposes an optimization framework that jointly considers terrestrial beamformer design and satellite user scheduling. The optimization problems are decomposed into three sub-problems and solved using deep clustering, second-order cone programming (SOCP), and linear programming. The proposed algorithm is demonstrated to be effective through simulation results.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Yue Zeng, Zhihao Qu, Song Guo, Bin Tang, Baoliu Ye, Jing Li, Jie Zhang
Summary: Network function virtualization is a crucial technology for 5G, enabling the abstraction of services into software-based service function chains (SFCs) for high-reliability mission-critical services. However, providing reliable SFCs in dynamic environments at a cost-effective manner is challenging due to delayed rewards, limited infrastructure resources, and hardware and software reliability heterogeneity. To address these challenges, this paper proposes a RuleDRL algorithm that combines deep reinforcement learning (DRL) to capture delayed rewards and rule-based schemes to explore high-quality solutions without violating constraints. Extensive simulations demonstrate the effectiveness of RuleDRL in cost savings and SFC acceptance ratio improvements compared to the state-of-the-art solution.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Enyuan Zhou, Zicong Hong, Yang Xiao, Dongxiao Zhao, Qingqi Pei, Song Guo, Rajendra Akerkar
Summary: The blockchain database MSTDB adopts a hybrid blockchain storage architecture, offloading the majority of blockchain storage to off-chain storage, and designs an index structure named Merkle Semantic Trie (MST) as a secure and semantic bridge between on- and off-chain. Based on MST, MSTDB provides a variety of semantic query functions, including multi-keyword query, range query, Top-K query, and cross-chain query. Extensive experiments demonstrate the effectiveness and efficiency of our blockchain database.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Information Systems
Zeyu Qin, Haipeng Yao, Tianle Mai, Di Wu, Ni Zhang, Song Guo
Summary: LEO satellite networks serve as a necessary supplement to terrestrial networks, especially in areas where the latter are limited. However, the increasing demand for computation-intensive IoT applications poses challenges in terms of efficient communication and computing capabilities. The combination of LEO networks and edge computing offers significant opportunities to address these problems.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Huawei Huang, Xiaowen Peng, Yue Lin, Miaoyong Xu, Guang Ye, Zibin Zheng, Song Guo
Summary: In a sharded blockchain, transactions are processed by parallel committees, boosting the transaction throughput. However, latency in committee formation and imbalanced consensus latency degrade the throughput. This paper proposes an algorithm to balance the tradeoff between throughput and cumulative age of transactions in a large-scale sharded blockchain, improving system utility, latency, and throughput performance.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Hardware & Architecture
Xiaolong Wang, Haipeng Yao, Tianle Mai, Song Guo, Yunjie Liu
Summary: With the rapid development of the Industrial Internet of Things (IIoT), the integration of time-sensitive networking (TSN) and fifth-generation (5G) wireless communication technology (TSN-5G networks) is considered the most promising solution to address the challenges posed by industrial networks. TSN can provide deterministic latency and reliability for real-time applications in wired networks, while 5G supports ultra-reliable and low-latency communications (uRLLC) in wireless networks. This paper focuses on the end-to-end traffic scheduling problem in TSN-5G networks and proposes a novel integrated TSN and 5G industrial network architecture, as well as a Double Q-learning based hierarchical particle swarm optimization algorithm (DQHPSO) to search for the optimal scheduling solution. Extensive simulations show that the DQHPSO algorithm improves the scheduling success ratio of time-triggered flows compared to other algorithms.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Information Systems
Tianle Mai, Haipeng Yao, Ni Zhang, Lexi Xu, Mohsen Guizani, Song Guo
Summary: The exponential growth of IoT devices and applications has brought both economic opportunities and challenges. The integration of IoT and blockchain technology is considered a promising solution to address privacy and security vulnerabilities. In this article, a cloud mining pool-aided BCoT architecture is proposed to overcome the computation and energy cost issue of blockchain. Furthermore, mining pool selection algorithms and a lightweight distributed reinforcement learning algorithm are introduced.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Fahao Chen, Peng Li, Deze Zeng, Song Guo
Summary: Short video apps like TikTok have gained popularity by providing users with fresh and short video contents that match their preferences. However, the growth of these apps poses technical challenges on the existing infrastructure. This article proposes an edge-assisted short video sharing framework that caches popular videos on edge servers for fast access through high-speed network connections.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
