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Article
Computer Science, Information Systems
Ernando Batista et al.
Summary: The Internet of Things enables the coordination and orchestration of numerous physical and virtual objects connected to the Internet. This paper proposes a solution for load balancing in IoT applications using Software-Defined Networks. It addresses the challenges posed by unstable network infrastructure and processing overload on IoT devices.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Dina Shehada et al.
Summary: The Internet of Things (IoT) allows for connectivity between smart devices, but it also brings challenges in terms of security and performance. This paper proposes a Fog computing based trust and reputation system to address these challenges, by evaluating trust among IoT devices and protecting the system from malicious devices. The proposed solution outperforms previous works in terms of suitability to IoT systems and security.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Mainak Adhikari et al.
Summary: This article introduces a new cybertwin-driven edge framework using 6G technology with an intelligent service provisioning strategy, distributing tasks from IoE applications using deep reinforcement learning and applying SVM classifier model at the edge network to analyze data and achieve high accuracy. Simulation results over real-time financial datasets demonstrate the effectiveness of the proposed strategy in reducing energy consumption by 15% and increasing prediction accuracy by 12% over baseline algorithms.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Jungyeon Baek et al.
Summary: This article explores the joint task offloading and resource allocation control for heterogeneous service tasks in multifog nodes systems using a deep recurrent network approach. Experimental results demonstrate that the proposed algorithm achieves a higher average success rate and lower average overflow compared to baseline methods.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Poria Pirozmand et al.
Summary: This study aims to identify the importance of each feature according to user's opinion in every feedback stage through weighted feature vector, rough theory and fuzzy logic, in order to achieve higher accuracy in image quality retrieval.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xianwei Li et al.
Summary: With the advancement in IoT technology, Mobile Edge Computing (MEC) emerges as a new method to address the limited computation capacity of IoT devices. The proposed system cooperatively allocates computation and communication resources to minimize the overhead of IoT devices, as well as reduce latency and energy consumption. Results show that the system provides significant improvements compared to traditional models.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Abegaz Mohammed Seid et al.
Summary: This paper deploys a clustered multi-UAV system to provide computing task offloading and resource allocation services to IoT devices. A multi-agent deep reinforcement learning (MADRL)-based approach is proposed to minimize the overall network computation cost while ensuring the quality of service (QoS) requirements of IoT devices or UEs in the IoT network.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Shuaiqi Shen et al.
Summary: The emerging technology of cybertwin is expected to bring revolutionary benefits to the 6G network, especially in terms of resource allocation and digital asset management. The current service architecture utilizing AI algorithms with universal configurations causes difficulties in customizing the complexity of AI algorithms, so we propose an adaptive AI framework that can adjust the complexity of AI models based on available computing resources.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Tiago Koketsu Rodrigues et al.
Summary: This article explores a Cybertwin-based system in multiaccess edge computing, proposing a mathematical model and conducting performance analysis through algorithms. Research shows that in specific scenarios, Cybertwin offers faster overall service compared to virtual machine schemes.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Wenjing Hou et al.
Summary: This article proposes a hierarchical task offloading strategy that integrates edge computing and artificial intelligence to ensure user QoE, low latency, and ultrareliable services in IoT. By utilizing multiagent deep deterministic policy gradient, the novel scheme achieves faster task processing and dynamic real-time allocation with lower overhead. Federated learning is used to train the model, leading to improved system processing efficiency and task completion ratio compared to benchmark schemes.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Hui Liang et al.
Summary: In this article, a combinatorial auction resource trading mechanism based on PAUSE is proposed to efficiently and securely allocate resources to meet the personalized service needs of mobile users and protect their privacy. Through this mechanism, cost savings can be achieved as well as transparent allocation of resources.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Miaojiang Chen et al.
Summary: This paper proposes a learning-based mobile fog scheme with deep deterministic policy gradient algorithm to improve the fog resource provisioning performance of mobile devices. The scheme models offloading computing as Markov Decision Processes, realizing offloading among different network states without knowing the transition probabilities, and uses the DDPG algorithm to address the state spaces explosion issue and learn an optimal offloading policy on distributed mobile fog computing. Simulation results show significant improvement in performance compared to traditional methods.
COMPUTER COMMUNICATIONS
(2021)
Article
Engineering, Civil
Yanlong Zhai et al.
Summary: The Internet of Vehicles (IoV) is an important application scenario in the development of the Internet of things, and SDN and fog computing can effectively improve the IoV network dynamics. This paper proposes an energy-aware dynamic offloading scheme for IoV systems based on SDN and fog computing, which aims to prolong the running time of the system by leveraging available battery power to execute more applications.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xuezhu Li
Summary: This paper proposes a computing offloading resource allocation strategy based on deep reinforcement learning in Internet of Vehicles, aiming to improve system delay performance and achieve optimal resource allocation and system security through redefining weighting factors and using Q-learning for optimization.
JOURNAL OF GRID COMPUTING
(2021)
Review
Chemistry, Multidisciplinary
Lorenzo Canese et al.
Summary: This review presents an analysis of the most commonly used multi-agent reinforcement learning algorithms, starting from single-agent algorithms and extending to multi-agent scenarios. The algorithms are grouped based on their features and a detailed taxonomy of main approaches proposed in literature is provided, focusing on mathematical models. Each algorithm is described in terms of possible application fields, pros and cons, and compared based on important characteristics such as nonstationarity, scalability, and observability. Benchmark environments used to evaluate the methods' performances are also discussed.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Taj-Aldeen Naser Abdali et al.
Summary: The Internet of Things (IoT) is rapidly growing in our world, and Fog Computing (FC) technology acts as a middleware between the Cloud and IoT to handle data transmission issues and improve performance by processing data locally at the edge of the network. This study provides a deep analysis of FC, covering its concept, architecture, applications, advantages, and optimization methods to address existing challenges and optimize services.
Article
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Dadmehr Rahbari et al.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2020)
Article
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Mahdi Abbasi et al.
COMPUTER COMMUNICATIONS
(2020)
Article
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Hua Wei et al.
Article
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Davood Akbari Bengar et al.
Article
Computer Science, Software Engineering
Kimia Rezaei Kalantari et al.
Article
Computer Science, Information Systems
Zhihan Lv et al.
COMPUTER COMMUNICATIONS
(2020)
Article
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Huilin Li et al.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Computer Science, Information Systems
Dohyun Kwon et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Hardware & Architecture
Quan Yu et al.
IEEE WIRELESS COMMUNICATIONS
(2019)
Article
Computer Science, Artificial Intelligence
Hamidreza Alrezaamiri et al.
Article
Engineering, Electrical & Electronic
Tao Ouyang et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2018)
Article
Telecommunications
Feng Wei et al.
CHINA COMMUNICATIONS
(2018)
Article
Engineering, Electrical & Electronic
Kai Arulkumaran et al.
IEEE SIGNAL PROCESSING MAGAZINE
(2017)
