Article
Computer Science, Theory & Methods
Pedro Cruz, Nadjib Achir, Aline Carneiro Viana
Summary: Multi-Access Edge Computing (MEC) attracts attention due to its implications in science, technology, and commerce. However, existing MEC initiatives are incomplete, and understanding experimental prototypes and implementations is crucial. This study discusses and surveys existing MEC projects, comparing strategies, limitations, and tools while addressing unresolved issues in practice.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Gabriele Morabito, Christian Sicari, Armando Ruggeri, Antonio Celesti, Lorenzo Carnevale
Summary: Nowadays, many Cloud companies adopt serverless computation based on the Function as a Service (FaaS) paradigm. Complex systems may now be viewed as a graph of serverless functions distributed over the Cloud and Edge layers. This work relies on Osmotic Computing principles to enhance the security and execution time of serverless applications.
INTERNET OF THINGS
(2023)
Review
Computer Science, Theory & Methods
Hans Jakob Damsgaard, Aleksandr Ometov, Jari Nurmi
Summary: With the increasing popularity of the Internet of Things and massive Machine Type Communication technologies, the number of connected devices is rising. However, bandwidth and latency constraints challenge Cloud processing of their associated data amounts. A promising solution to these challenges is the combination of Edge and approximate computing techniques that allows for data processing nearer to the user. This article aims to survey the potential benefits of these paradigms' intersection and provide insights on circuit-level and architecture-level hardware techniques, popular applications, and future research directions.
ACM COMPUTING SURVEYS
(2023)
Review
Chemistry, Physical
Zixuan Zhang, Xinmiao Liu, Hong Zhou, Siyu Xu, Chengkuo Lee
Summary: Machine-learning-enhanced nanosensors show great potential in the field of sensor technology due to their adaptive and predictive capabilities. This paper reviews the advancements in cloud computing, edge computing, and neuromorphic computing, and provides a perspective on the future of machine-learning-enhanced nanosensors.
Article
Computer Science, Hardware & Architecture
Mohammad Yahya Akhlaqi, Zurina Binti Mohd Hanapi
Summary: Many enterprise companies are migrating their services and applications to the cloud to take advantage of cloud computing benefits. However, the increasing number of connected devices and the massive amount of generated data using cloud services lead to congestion and delays in the centralized cloud architecture. Mobile Edge Computing (MEC) solves this problem by expanding cloud capabilities near the end devices, and new technologies like IoT, AV, 5G, and AR further enhance the potential of MEC. The offloading problem in MEC, which involves offloading delay-sensitive and computationally intensive tasks to nearby MEC nodes, is a widely studied issue but still an open problem.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Computer Science, Theory & Methods
Hao Zhou, Geng Yang, Yuxian Huang, Hua Dai, Yang Xiang
Summary: This paper proposes a privacy-preserving and verifiable federated learning (PVFL) method with low communication and computation overhead for edge computing. It is theoretically and experimentally demonstrated that PVFL has the properties of communication overhead independent of dropouts and parameter vector dimension, computation overhead independent of dropouts, and a negative correlation between the loss function value and the number of dropouts.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Bahareh Bahrami, Mohammad Reza Khayyambashi, Seyedali Mirjalili
Summary: MEC is a promising communication paradigm that utilizes edge servers near end users to enable IoT and 5G scenarios. These servers provide virtualized resources and host various MEC applications, allowing user equipment and IoT devices to offload tasks. Optimizing edge server placement can greatly enhance the performance of mobile applications.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Taejin Kim, Sandesh Dhawaskar Sathyanarayana, Siqi Chen, Youngbin Im, Xiaoxi Zhang, Sangtae Ha, Carlee Joe-Wong
Summary: Edge computing capabilities in 5G wireless networks can reduce latency for mobile users by offloading computing tasks from user devices to nearby edge servers. This paper introduces MoDEMS, a system model and architecture that addresses the challenges of handling long-term user mobility in offloading, aiming to minimize service provider cost and user latency. The authors propose alternative heuristic algorithms for solving the cost minimization problem and validate the results through various experiments, showing a 33% reduction in latency compared to previous migration approaches.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Volkan Gezer, Achim Wagner
Summary: This paper presents a novel software reference architecture for Edge Servers to overcome the QoS and latency issues caused by Cloud Computing, bringing computation power close to end devices for real-time applications. The architecture allows Edge Servers to collaborate, execute tasks on time, and address resource planning and task scheduling challenges in decentralized systems.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Computer Science, Information Systems
Firas Al-Doghman, Nour Moustafa, Ibrahim Khalil, Nasrin Sohrabi, Zahir Tari, Albert Y. Zomaya
Summary: The paradigm of edge computing has created new possibilities for the Internet of Things (IoT), expanding cloud services to the network edge. This allows for the design of distributed architectures and the enhancement of decision-making applications. Edge computing faces challenges related to security and privacy, but advancements in artificial intelligence and machine learning provide opportunities for precise models and intelligent applications at the network edge. This study presents a comprehensive survey on securing edge computing-based AI microservices, highlighting key requirements and proposing a secure edge computing framework.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
G. S. S. Chalapathi, Vinay Chamola, Wafa Johal, Jagannath Aryal, Rajkumar Buyya
Summary: This paper introduces the concepts of edge computing and Green Cloudlet Networks (GCNs) as well as the challenges they face. To address these challenges, a task assignment method called Ge-LATA is proposed, aiming to optimize latency and green energy consumption. Simulation experiments demonstrate the effectiveness of Ge-LATA compared to other task assignment schemes in reducing latency and energy consumption.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Computer Science, Information Systems
Quy Vu Khanh, Nam Vi Hoai, Anh Dang Van, Quy Nguyen Minh
Summary: History has shown that healthcare and medical systems are crucial for the advancement of science and technology. In the past decades, there has been an explosive growth of ehealth applications, with cloud computing dominating e-healthcare systems and various domains. However, the high response time of cloud-based e-health systems presents a primary barrier.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Jin Wang, Zhaobo Lu, Mingjia Fu, Jianping Wang, Kejie Lu, Admela Jukan
Summary: This article discusses the potential, issues, and solutions of coded edge computing. By designing a general and efficient Decode-and-Compare Verification (DCV) scheme, computation results can be verified for correctness and faulty edge servers can be identified. Experimental results show that the DCV scheme outperforms other potential schemes in terms of computation time and accuracy.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Shagufta Henna, Alan Davy
Summary: Ubiquitous computing has the potential to harness the flexibility of distributed computing systems, including cloud, edge, and Internet of Things devices. This article proposes a novel collaborative distributed deep learning approach that utilizes the topological dependencies of the edge to enhance edge intelligence. Performance evaluation shows that both schemes outperform cloud-based deep learning inference.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Sheuli Chakraborty, Kaushik Mazumdar
Summary: This study proposes a scheme that dynamically selects edge cloud for offloading tasks and checks task dependencies, achieving good performance in sensor mobile edge computing.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Zuobin Xiong, Zhipeng Cai, Daniel Takabi, Wei Li
Summary: This article explores innovative approaches to privacy protection in federated learning with non-i.i.d. data. A novel algorithm, 2DP-FL, is designed to achieve differential privacy by adding noise during training local models and when distributing global model. The results of theoretical analysis and real-data experiments validate the advantages of 2DP-FL in privacy protection, learning convergence, and model accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Hardware & Architecture
Tongxin Zhu, Xiuzhen Cheng, Wei Cheng, Zhi Tian, Yingshu Li
Summary: The Internet of Things enabled Cyber-Physical System is a promising technology applied in various fields. This paper investigates PCA based data compression to maximize compression ratio while maintaining a bounded reconstruction error in IoT enabled CPSs. The proposed algorithms are verified through extensive simulations.
MICROPROCESSORS AND MICROSYSTEMS
(2022)
Article
Computer Science, Information Systems
Honghui Xu, Zhipeng Cai, Daniel Takabi, Wei Li
Summary: The demand for sharing video streaming has increased significantly due to the proliferation of IoT devices, while the development of AI detection techniques has made visual privacy protection more urgent and difficult. In this article, a cycle vector-quantized variational autoencoder (cycle-VQ-VAE) framework is proposed to encode and decode videos with extracted audio, enabling effective privacy protection. The framework includes two models, F2F and V2V, which utilize frame relations to improve privacy protection, video compression, and video reconstruction. Experimental results demonstrate the superiority of the proposed models in visual privacy protection, visual quality preservation, and video transmission efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Tongxin Zhu, Jianzhong Li, Hong Gao, Yingshu Li
Summary: A novel network called battery-free wireless sensor network (BF-WSN) is proposed to overcome the limitations of battery-powered wireless sensor networks. In BF-WSNs, battery-free sensor nodes harvest energy from the environment instead of relying on batteries, allowing them to have unlimited energy consumption. However, they still face challenges in terms of energy harvesting rates and capacities. This paper focuses on the Minimum-Latency Aggregation Scheduling problem in BF-WSNs, which is proved to be NP-hard. A Data Aggregation Scheduling algorithm is proposed to address the problem, and theoretical analysis and extensive simulations are conducted to evaluate its performance.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Cybernetics
Dongxiao Yu, Na Wang, Qi Luo, Feng Li, Jiguo Yu, Xiuzhen Cheng, Zhipeng Cai
Summary: This article investigates the core maintenance problem in dynamic graphs and proposes a method for processing multiple edges concurrently, significantly improving efficiency. The algorithms proposed show a significant speedup in processing time and support parallel implementations.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
Article
Computer Science, Cybernetics
Fuxing Li, Yingjie Wang, Yang Gao, Xiangrong Tong, Nan Jiang, Zhipeng Cai
Summary: This article focuses on the conflicts of interest among task requester, platform, and crowd workers in mobile crowdsourcing. A three-party evolutionary game model, considering collusion between crowd workers and the platform, is constructed. The replication dynamics method is used to analyze the evolutionary stability strategy. Rewards and penalties are proposed to address free-riding and false-reporting problems. Simulation experiments verify the stability of the equilibrium point in the three-party game system and effective methods to motivate players to choose a trusted strategy.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
Article
Automation & Control Systems
Tongxin Zhu, Zhipeng Cai, Xiaolin Fang, Junzhou Luo, Ming Yang
Summary: Edge-enabled Industrial Internet of Things (E-IIoT) has greatly improved the computation capacity and efficiency of IIoT networks. The correlation aware scheduling (CAS) algorithm proposed in this article effectively reduces latency by wisely scheduling computation resources.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Quan Chen, Zhipeng Cai, Lianglun Cheng, Hong Gao
Summary: With advancements in wireless power transfer techniques, battery-free wireless sensor networks (BF-WSNs) have gained increasing attention for supporting long-term applications. However, the minimum latency aggregation scheduling (MLAS) problem in BF-WSNs has not been well studied. This paper investigates the general MLAS problem in BF-WSNs, targeting any subset of nodes and arbitrary number of aggregation queries. The proposed algorithms demonstrate high performance in terms of latency and energy efficiency.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Information Systems
Quan Chen, Zhipeng Cai, Lianglun Cheng, Hong Gao, Jianzhong Li
Summary: This paper investigates the problem of Minimum Latency Broadcast Scheduling (MLBS) in duty-cycled wireless sensor networks. It proposes a two-step scheduling algorithm to construct the broadcast tree and compute a collision-free schedule simultaneously, and introduces concurrent broadcasting transmission mode. It also presents multiple messages broadcasting and all-to-all broadcasting algorithms to generate independent broadcast schedules for improving efficiency.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Tuo Shi, Zhipeng Cai, Jianzhong Li, Hong Gao, Jiancheng Chen, Ming Yang
Summary: This paper presents an online problem of jointly managing mobile edge services and routing distributed multi-hop requests in an MEC network. By proposing approximation algorithms and online algorithms, this problem can be effectively addressed.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Information Systems
Zhipeng Cai, Quan Chen, Tuo Shi, Tongxin Zhu, Kunyi Chen, Yingshu Li
Summary: Battery-free wireless sensor network (BF-WSN) is a new network architecture proposed to solve the lifetime limitation problem of conventional WSNs. BF-WSN can harvest energy from environmental resources or power stations, resulting in an unlimited lifetime in terms of energy. Its specific properties have brought new challenges in energy management, networking, and data acquisition. This survey aims to summarize and analyze the existing algorithms and applications of BF-WSNs.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Remote Sensing
Sitong Zhang, Yibing Li, Fang Ye, Xiaoyu Geng, Zitao Zhou, Tuo Shi
Summary: Unmanned Aerial Vehicles (UAVs) are crucial for collecting and transmitting data from remote areas, and collision-free navigation is essential for their successful operation. Existing methods for UAV collision avoidance face challenges such as high energy consumption and limited sensing ability. To address these challenges, we propose a hybrid collision-avoidance method that combines human-in-the-loop deep reinforcement learning (HL-DRL) and global planning. This method has been evaluated in simulated environments and has shown rapid adaptation and the ability to prevent UAVs from getting stuck in complex environments.
Article
Computer Science, Hardware & Architecture
Quan Chen, Song Guo, Zhipeng Cai, Jing Li, Tuo Shi, Hong Gao
Summary: This paper investigates the joint scheduling problem of data transmission and energy replenishment to optimize the maximum peak Age of Information (AoI) at the network edge with directional chargers. The theoretical bounds of the maximum peak AoI with respect to the charging latency are derived. Optimal and approximate scheduling algorithms are proposed to minimize the charging latency and the maximum peak AoI. The proposed algorithms have been shown to achieve high performance in terms of latency and AoI through theoretical analysis and simulation results.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Computer Science, Information Systems
Tongxin Zhu, Jianzhong Li, Hong Gao, Yingshu Li, Zhipeng Cai
Summary: This paper investigates the problem of AoI minimization data collection scheduling for BF-WSNs, proposes an optimal offline algorithm and an online algorithm, and analyzes their theoretical optimality and competitive ratio. Numerical results are provided to verify the performance of the proposed algorithms.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
