Review
Telecommunications
Kuanishbay Sadatdiynov, Laizhong Cui, Lei Zhang, Joshua Zhexue Huang, Salman Salloum, Mohammad Sultan Mahmud
Summary: Edge Computing is an emerging paradigm that brings computation power closer to end devices, reducing latency and energy consumption. Optimization methods play a crucial role in scheduling computation offloading tasks in Edge Computing networks.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Engineering, Electrical & Electronic
Weiyang Feng, Ning Zhang, Shichao Li, Siyu Lin, Ruirui Ning, Shuzhong Yang, Yuan Gao
Summary: The paper introduces a reverse offloading framework to optimize the computation resource allocation in CVIS for reduced system latency and improved performance. By designing different strategies and algorithms, the burden on the VEC server is successfully reduced, resulting in enhanced performance outcomes.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Swapnil Shinde, Arash Bozorgchenani, Daniele Tarchi, Qiang Ni
Summary: With the emergence of smart vehicles, new applications such as computation offloading and Federated Learning have become important in Vehicular Networks. This study aims to optimize the performance of VNs by considering computation offloading and FL together, and selecting the appropriate number of FL iterations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Subin Eom, Hoon Lee, Junhee Park, Inkyu Lee
Summary: This paper investigates an asynchronous offloading protocol for mobile edge computing systems, addressing a joint optimization problem of transmit power, offloading size, and time-frequency resources to minimize the energy consumption of the system. By applying convex optimization techniques, the optimal solution for the asynchronous MEC offloading problem can be obtained. Numerical results demonstrate the effectiveness of the proposed asynchronous protocol over traditional synchronous approaches.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Yi Zhou, Cunhua Pan, Phee Lep Yeoh, Kezhi Wang, Maged Elkashlan, Branka Vucetic, Yonghui Li
Summary: The study proposes a low-latency virtual reality delivery system using UAV base stations to transmit VR content to multiple ground users. A low-complexity iterative algorithm is designed to minimize communication and computing latency among users, with caching found to be helpful in reducing latency.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Computer Science, Theory & Methods
Haowei Chen, Shuiguang Deng, Hongze Zhu, Hailiang Zhao, Rong Jiang, Schahram Dustdar, Albert Y. Zomaya
Summary: In mobile edge computing systems, users can offload tasks to nearby edge servers to improve computation capabilities and reduce transmission latency. However, the dynamic wireless channel state and user locations make it challenging to allocate resources and make offloading decisions. Additionally, the dependency among users also has a significant impact on collaborative work. In this study, we propose a mathematical optimization problem to address this issue and develop a distributed algorithm based on Markov approximation. Experimental results demonstrate the effectiveness of our scheme in reducing latency and energy consumption.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Neng Wan, Yating Luo, Guangping Zeng, Xianwei Zhou
Summary: This study proposes a multi-vehicle side communication and edge computing collaboration framework to maximize the use of communication and computation resources and reduce task computation latency. It presents low-complexity solution and an improved optimization algorithm for matching and resource allocation. Evaluation shows that the method effectively meets the latency requirements and improves task execution efficiency.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Sara Ghanavati, Jemal Abawajy, Davood Izadi
Summary: Fog computing is a preferred platform for low-latency applications, but effectively utilizing resources for delay-sensitive tasks is a challenge. Our proposed task scheduling algorithm successfully reduces system makespan and energy consumption.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Engineering, Electrical & Electronic
Mohsen Tajallifar, Sina Ebrahimi, Mohammad Reza Javan, Nader Mokari, Luca Chiaraviglio
Summary: In this paper, a novel resource management scheme is proposed for the joint allocation of transmit power and computational resources in a centralized radio access network architecture. The optimization problem is divided into two sub-problems and solved using convex-concave procedure and heuristic algorithm. Feasibility analysis and a baseline method are also proposed. Simulation results show the superiority of the joint method in terms of acceptance ratio, with an optimality gap less than 5%.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Zhixiong Chen, Zhaokun Zhou, Chen Chen
Summary: Utilizing data caching technology to reduce transmission, optimizing caching strategy, offloading decision, wireless and computing resource allocation for optimal system design.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2021)
Article
Engineering, Multidisciplinary
Xinjie Zhang, Xinglin Zhang, Wentao Yang
Summary: Mobile edge computation offloading (MECO) is a promising method to reduce the energy consumption of smart mobile devices (SMDs). This paper proposes an energy-efficient algorithm based on deep reinforcement learning to optimize the overall energy cost in a real-time multi-user MEC system.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Peng Wang, Kenli Li, Bin Xiao, Keqin Li
Summary: This article discusses the multiobjective optimization problem in a multiuser, multi-task, and multiserver scenario in mobile edge computing, aiming to maximize the user's offloading benefits. By constructing a multivariable and multiobjective optimization problem, and developing an efficient multiobjective evolutionary algorithm to solve this problem.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Jiayun Zhou, Xinglin Zhang
Summary: This article addresses the joint task offloading and resource allocation problem in the scenario with cooperative MEC servers, proposing a two-level algorithm to solve the issue. Comprehensive evaluation results demonstrate the efficiency and fairness of the proposed algorithm compared to baselines.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Xingqiu He, Sheng Wang, Xiong Wang
Summary: Mobile Edge Computing (MEC) is a promising computing paradigm that brings cloud computing closer to end users. This paper focuses on the task scheduling among collaborative edge servers and proposes an online algorithm to maximize system utility while considering worst-case latency requirements and long-term energy consumption constraints. The theoretical analysis and simulation results show the effectiveness of the proposed algorithm in various situations.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Kuanishbay Sadatdiynov, Laizhong Cui, Lei Zhang, Joshua Zhexue Huang, Neal N. Xiong, Chengwen Luo
Summary: This paper proposes an intelligent two-stage computation offloading scheme to handle the large number of smart mobile devices in the IoE system. In the first stage, tasks are categorized and early offloading decisions are made based on offloading preferences. In the second stage, a multi-objective optimization problem is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II) for the remaining tasks. The simulation results show a 10% performance improvement in terms of latency and energy consumption compared to existing methods.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Zhengchuan Chen, Siling Liu, Yunjian Jia, Min Wang, Tony Q. S. Quek
Summary: This article proposes a novel hybrid duplex scheme with great potential in improving the spectral efficiency. By mitigating the self-interference in FD systems, the performance can be enhanced. The scheme is then applied to two-hop relaying systems, and by optimizing the FD duty cycle and source power allocation, the achievable rate can be significantly improved.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Yuan Wu, Yuxiao Song, Tianshun Wang, Liping Qian, Tony Q. S. Quek
Summary: This paper studies the Non-orthogonal Multiple Access (NOMA) assisted Federated Learning (FL) in wireless networks. It proposes a joint optimization algorithm for minimizing the system-wise cost by considering wireless power transfer, model transmission, and model aggregation. The proposed algorithm achieves the optimal solution and significantly reduces the system cost compared to traditional FL schemes.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Yaru Fu, Yue Zhang, Angus K. Y. Wong, Tony Q. S. Quek
Summary: In this paper, the interplay between personalized bundle recommendation and cache decision on the performance of wireless edge caching networks is explored from a revenue maximization perspective. The quantitative impact of bundle recommendation on different users' content request probability is examined, and the dependence of system revenue on bundle recommendation and caching policies is specified. A joint bundling, caching, and recommendation decision problem is formulated to maximize the achievable system revenue, considering the constraints of user-distinguished recommendation quality, recommendation amount, and cache capacity budget. A divide-then-conquer methodology is adopted to solve this non-tractable optimization problem, and detailed properties analysis for the proposed bundling and joint optimization algorithms is provided. Comprehensive numerical simulations validate the performance enhancement of the designed solutions compared to extensive conventional single-item recommendation oriented benchmarks.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Meiyan Song, Hangguan Shan, Howard H. Yang, Tony Q. S. Quek
Summary: In this paper, an interference coordination technology for D-TDD small cell networks is proposed by integrating fractional frequency reuse (FFR) with cell clustering. Numerical results show that the proposed scheme outperforms clustered D-TDD and traditional D-TDD in terms of improving uplink performance while slightly decreasing downlink performance, and can maximize spatially averaged MPT by jointly optimizing network parameters.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Ce Sun, Kui Cai, Guanghui Song, Tony Q. S. Quek, Zesong Fei
Summary: This paper proposes a novel belief propagation (BP) based detector for sneak path interference in ReRAM and combines it with a BP decoder of polar codes to improve the error rate performance of ReRAM.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Howard H. Yang, Ahmed Arafa, Tony Q. S. Quek, H. Vincent Poor
Summary: This paper investigates the age-of-information (AoI) problem in random access networks and proposes an analytical framework to consider the effects of spatiotemporal interactions on AoI. Accurate and tractable expressions are derived to quantify the network average AoI and the outage probability of peak AoI. In addition, a decentralized channel access policy is developed to minimize AoI based on local observations. The study reveals a tradeoff in packet arrival rate for minimizing the network average AoI and shows the effectiveness of the slotted ALOHA protocol in reducing AoI.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Yu Han, Shi Jin, Chao-Kai Wen, Tony Q. S. Quek
Summary: Reconfigurable intelligent surface (RIS) can passively manipulate electromagnetic waves to enhance mobile communication services, but the lack of a signal processing module makes channel estimation challenging. By utilizing an extra large RIS for assistance, accurate user visibility region identification and channel reconstruction using multiple users' pilots can be achieved.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Zhongyu Wang, Zhaoyang Zhang, Yuqing Tian, Qianqian Yang, Hangguan Shan, Wei Wang, Tony Q. S. Quek
Summary: This paper proposes a novel asynchronous federated learning framework that adapts to the heterogeneity of users, communication environments, and learning tasks by considering delays in training and uploading local models and the resulting staleness among received models. A centralized fusion algorithm is designed to determine fusion weights during global updates, aiming to achieve fast and smooth convergence while enhancing training efficiency.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
Article
Telecommunications
Yu Hua, Yaru Fu, Qi Zhu
Summary: Cache-enabled device-to-device communication is a promising technique to handle the increase in mobile data traffic. A recommendation system can reduce heterogeneity among users and enhance the benefits of edge caching.
CHINA COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Zheng Shi, Hong Wang, Yaru Fu, Xinrong Ye, Guanghua Yang, Shaodan Ma
Summary: In this paper, the combination of reconfigurable intelligent surface (RIS) and hybrid automatic repeat request with incremental redundancy (HARQ-IR) is proposed to improve the power efficiency, latency, and reliability of IoT communications. The outage probability of single-input single-output (SISO) HARQ-IR-RIS aided IoT networks is derived in closed-form for Rician fading channels and multiple RISs, and the asymptotic outage analysis is conducted. The asymptotic results are extended to single-input multiple-output (SIMO)/multiple-input multiple-output (MIMO) HARQ-IR-RIS aided IoT networks using random matrix theory. The design complexity of phase shifts, transmit powers, and rate is reduced based on the derived expressions to achieve minimum age of information (AoI) while satisfying power and outage constraints.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Yaru Fu, Jianqing Liu, Junming Ke, John Kwok Tai Chui, Kevin King Fai Hung
Summary: In this study, we examine the problem of dynamic cache update in wireless content caching networks from a cost minimization perspective. We propose suboptimal and optimal algorithms to address the non-convex optimization problem. The results show that the suboptimal solution achieves near-optimal performance, and high cache capacity does not always have a positive effect on system performance when update cost is considered.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Changsen Feng, Bomiao Liang, Zhengmao Li, Weijia Liu, Fushuan Wen
Summary: The wide deployment of renewable energy resources and the more proactive demand-side management have led to a new paradigm in power system operation and electricity market trading, which has boosted the emergence of the peer-to-peer market. This paper proposes a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. The framework includes an event-driven local P2P market and sensitivity analysis to evaluate the impacts of P2P transactions on the distribution network, ensuring secure operation.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Proceedings Paper
Computer Science, Information Systems
Jingheng Zheng, Wanli Ni, Hui Tian, Deniz Gunduz, Tony Q. S. Quek
Summary: This paper proposes a SemiFL framework for cellular-based federated learning, which addresses the waste of computing resources at the base station by simultaneously sending gradient updates and training samples. The proposed framework improves accuracy and convergence speed compared to conventional FL.
IEEE INFOCOM 2022 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)
(2022)
Proceedings Paper
Computer Science, Information Systems
Kexin Xiong, Zhongyuan Zhao, Wei Hong, Mugen Peng, Tony Q. S. Quek
Summary: In this paper, the design of few-shot learning in wireless networks was studied, proposing a meta-learning model-based scheme and a coalition formation-based model selection scheme. The simulation results show that the proposed scheme can improve model accuracy performance with low communication costs.
2022 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS)
(2022)
Proceedings Paper
Computer Science, Information Systems
Jianpeng Xu, Bo Ai, Tony Q. S. Quek, Yupei Liuc
Summary: This paper investigates the issue of external interference suppression in the reconfigurable intelligent surface (RIS)-aided high-speed railway (HSR) network and proposes a deep reinforcement learning (DRL)-based scheme for designing the phase shifts at the RIS. Simulation results demonstrate the effectiveness of the proposed scheme.
2022 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS)
(2022)