Article
Computer Science, Information Systems
Feixiang Li, Chao Fang, Mingzhe Liu, Ning Li, Tian Sun
Summary: In this paper, an intelligent computation offloading mechanism with content cache in mobile edge computing is proposed. The network framework for computation offloading with content cache in mobile edge computing is provided. An optimal contract is designed based on necessary and sufficient conditions to obtain the joint task offloading, resource allocation, and a computation strategy with an intelligent mechanism.
Article
Computer Science, Information Systems
Huan Zhou, Tong Wu, Xin Chen, Shibo He, Deke Guo, Jie Wu
Summary: This article proposes a novel Reverse Auction-based Computation Offloading and Resource Allocation Mechanism, named RACORAM, for mobile Cloud-Edge computing. RACORAM uses reverse auction to stimulate edge server owners to participate in the offloading process, aiming to minimize the cost of the Cloud Service Center (CSC). The article also presents low-complexity algorithms to solve the optimization problems.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Shuang Fu, Fuhui Zhou, Rose Qingyang Hu
Summary: Mobile edge computing (MEC) enables wireless devices to offload computation tasks to powerful servers, providing them with more computing capability and lower latency. The relaying technique improves offloading performance, especially in poor channel conditions. This article focuses on a multiuser relay-aided MEC system that aims to minimize energy consumption. Using an iterative algorithm based on successive convex approximation (SCA), the problem of energy minimization is solved by jointly optimizing transmit power, offloading time duration, and CPU frequencies.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Chen Zhang, Hongwei Du
Summary: Mobile edge computing (MEC) reduces latency by pushing resources to distributed base stations (BSs) closer to users. To improve user experience and increase revenue, service providers (SPs) prefer using their own deployed BSs to provide services. This article proposes a resource allocation scheme that maximizes the total profit of all SPs at the MEC layer and provides high-quality services. Simulation results demonstrate the effectiveness of the proposed scheme.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Meysam Masoudi, Cicek Cavdar
Summary: This research investigates the power minimization problem for mobile devices by data offloading in multi-cell multi-user OFDMA mobile edge computing networks. By utilizing proposed algorithms, considerable power savings can be achieved, such as about 60% for large bit stream size compared to local computing baseline.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Article
Engineering, Electrical & Electronic
Sabyasachi Gupta, Dinesh Rajan, Joseph Camp
Summary: This article proposes a novel framework for a multi-user mobile edge computing (MEC) network, where users with high downlink rate demands and users with intensive computation tasks can collaborate to reduce task completion time and improve downlink user rates. By using non-orthogonal multiple access (NOMA), the users with computation tasks can offload part of the tasks to the edge cloud and the downlink users, while forwarding information received from the base station (BS) to the downlink users. A joint optimization of communication and computational resources, user pairings, task sharing, and relay bits is performed to minimize task completion time and satisfy downlink user incentives. Simulation results demonstrate significant reductions in task completion time and computational energy savings at the edge cloud, as well as improved downlink user rates compared to orthogonal transmission.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Hardware & Architecture
Nadine Abbas, Sanaa Sharafeddine, Azzam Mourad, Chadi Abou-Rjeily, Wissam Fawaz
Summary: This study proposes a joint computing, communication, and cost-aware task offloading optimization problem aimed at maximizing the number of completed tasks, while minimizing energy consumption and monetary cost in D2D-enabled heterogeneous MEC networks. The proposed scheme allows partial task offloading, achieves high performance results, and can be applied to large-scale networks.
Review
Computer Science, Information Systems
Gaurav Baranwal, Dinesh Kumar, Deo Prakash Vidyarthi
Summary: This paper provides a comprehensive survey of research works applying blockchain in resource allocation in cloud computing and distributed edge computing paradigms. It discusses the issues in centralized resource allocation approaches, introduces the structure, working, and characteristics of blockchain, and explores its benefits to resource allocation. The paper also presents a depth overview of blockchain-based resource allocation works in different domains and discusses the consensus mechanisms and key challenges.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Wenhao Fan, Shenmeng Li, Jie Liu, Yi Su, Fan Wu, Yuan'An Liu
Summary: This article proposes a joint task offloading and resource allocation scheme for accuracy-aware machine-learning-based IIoT applications in an edge-cloud-based network architecture. The Lyapunov optimization technique is applied to convert the long-term stochastic optimization problem into a short-term deterministic problem. Two algorithms are proposed to efficiently solve the problem, and the performance of the scheme is proved by theoretical analysis and extensive simulations.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Razie Roostaei, Zahra Dabiri, Zeinab Movahedi
Summary: Mobile Edge Computing offers cloud computation capabilities at the edge of the mobile network, but efficiency is influenced by purchasing power and resource competition. A game-based distributed scheme is proposed to address challenges in resource allocation and pricing for computation offloading, considering incentives and conflicts between edge providers and Mobile Users (MUs).
Review
Computer Science, Hardware & Architecture
Chuan Feng, Pengchao Han, Xu Zhang, Bowen Yang, Yejun Liu, Lei Guo
Summary: This paper presents a comprehensive survey of computation offloading in Mobile Edge Computing (MEC) networks, covering applications, offloading objectives, and offloading approaches. The key issues in offloading objectives, such as delay minimization, energy consumption minimization, revenue maximization, and system utility maximization, are discussed. The methods to achieve these objectives, including mathematical solver, heuristic algorithms, Lyapunov optimization, game theory, and Markov Decision Process (MDP) and Reinforcement Learning (RL), are compared. Finally, the current challenges and future directions of computation offloading in MEC networks are analyzed from various aspects.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Hongchang Ke, Hui Wang, Hongbin Sun
Summary: This paper introduces a mobile edge computing (MEC) framework in 5G wireless networks, which utilizes MEC servers to handle the computation tasks of wireless nodes, meeting the requirements of low latency and high reliability. The authors propose a deep reinforcement learning-based algorithm for task offloading and resource allocation, which achieves optimal decision-making policy through training neural networks. Simulation results show that this algorithm has good convergence and outperforms other baseline algorithms.
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)
Article
Telecommunications
Wen-Bin Sun, Jian Xie, Xin Yang, Ling Wang, Wei-Xiao Meng
Summary: This paper proposes an opportunistic access fog-cloud computing network (OFCN), which considers resource allocation and computation offloading under the constraints of users' quality of service (QoS) requirements. By dividing the original problem into four suboptimal problems and developing an iterative algorithm, the proposed OFCN can achieve lower latency and energy consumption compared to conventional fog-cloud computing networks.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
Article
Computer Science, Artificial Intelligence
Miaojiang Chen, Zeyuan Li, Peipei Chen, Wei Liu, Anfeng Liu
Summary: In this paper, a differential dynamic gradient descent (DDGD) optimization algorithm is proposed to solve the offloading decision and resource allocation problems in multiuser cooperative offloading mobile edge computing (COMEC) system. The algorithm can obtain better optimization solutions.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Automation & Control Systems
Sravani Kurma, Prabhat Kumar Sharma, Keshav Singh, Shahid Mumtaz, Chih-Peng Li
Summary: The efficient and effective framework for next-generation wireless networks should include features such as ultralow latency, ultrahigh reliability, and enhanced data rate. This article investigates the application of mission-critical ultrareliable low latency communication in an industrial Internet of Things environment. A novel transmission protocol is studied and the network's performance is analyzed. Monte-Carlo simulations are used to validate the analytical results.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Haijun Liao, Zhenyu Zhou, Nian Liu, Yan Zhang, Guangyuan Xu, Zhenti Wang, Shahid Mumtaz
Summary: Digital twin (DT) is a cutting-edge technology for intelligent optimization of electrical equipment management, but it still faces reliability and communication efficiency problems. This paper proposes a Cloud-edge-device Collaborative reliable and Communication-efficient DT named C-3-FLOW. By jointly optimizing device scheduling, channel allocation, and computational resource allocation, C-3-FLOW minimizes the long-term global loss function and time-average communication cost. Simulation results verify its superior performance in loss function, communication efficiency, and carbon emission reduction.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Dingde Jiang, Feng Wang, Zhihan Lv, Shahid Mumtaz, Saba Al-Rubaye, Antonios Tsourdos, Octavia Dobre
Summary: This article proposes a user-oriented content distribution scheme for satellite-terrestrial networks (STN) to improve content distribution efficiency. The scheme includes algorithms for network division, caching satellite deployment, cache node selection, and content updating mechanism. Simulation results demonstrate that the scheme can reduce propagation delay and network load under different network conditions and has stability and self-adaptability.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Electrical & Electronic
Amit Samanta, Tri Gia Nguyen, Thao Ha, Shahid Mumtaz
Summary: Due to the increasing number of real-time mobile applications and Industrial Internet-of-Things (IIoT) devices, the edge computing paradigm has become a useful platform for real-time IoT applications. However, the varying resource requirements of IIoT devices pose a challenge for effective utilization. In this study, we propose a novel resource-agnostic microservice offloading scheme called RAISE, which efficiently estimates the resource requirements of IIoT devices and maximizes their utilization in the network. Experimental results demonstrate that RAISE outperforms existing methods, SDTO and DTOS, in terms of network throughput and Quality-of-Service (QoS), while also reducing cost and improving reliability.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Yi Fang, Junming Zhuo, Huan Ma, Shahid Mumtaz, Yonghui Li
Summary: We propose a new index-modulation-aided differential chaos shift keying (DCSK) system, the CTIM-DCSK system, that utilizes frequency and time resources for high-data-rate transmissions. The system uses orthogonal sinusoidal carriers to transmit reference-chaotic and information-bearing signals, while the frequency and time resources are used as indices for additional information bits. The proposed CTIM-DCSK system improves bit error rate (BER) performance and complexity reduction by using time slots to convey the same index bits. Noise reduction methods at the receiver further enhance BER performance. The theoretical BER expressions are derived and compared with existing counterparts, confirming the accuracy and advantage of the proposed CTIM-DCSK system. Therefore, it is a competitive candidate for low-complexity Internet-of-Things applications.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Huan Ma, Yi Fang, Pingping Chen, Shahid Mumtaz, Yonghui Li
Summary: A new MIM-DCSK scheme is proposed in this paper to enhance the data rate, energy efficiency, and spectral efficiency of traditional DCSK scheme. It considers time slot, carrier, and Walsh code as indices to convey additional information bits, achieving high data rate, spectral efficiency, and energy efficiency. The theoretical analysis and simulation results demonstrate the superiority of the proposed scheme, which is a promising solution for low-power and low-cost short-wireless communications.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Editorial Material
Computer Science, Information Systems
Syed Hassan A. Shah
ACM TRANSACTIONS ON SENSOR NETWORKS
(2023)
Article
Engineering, Electrical & Electronic
Gaofeng Nie, Ting Ma, Zhi Zhang, Hui Tian, Shahid Mumtaz, Zihang Ding
Summary: This paper aims to accelerate the large area data collection process by using multiple unmanned aerial vehicles (UAVs) in a parallel manner, and proposes a coarse multi-UAV trajectory design solution without repeated edges to minimize the data collection completion time. The wide area is partitioned using a division unit structure with four stay points, and it is proven that a closed-loop trajectory exists for any area that consists of division units with the proposed structure. Simulation results show that the proposed coarse closed-loop trajectory design method approaches the lower bound of the data collection completion time with a loss less than 10%.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Editorial Material
Computer Science, Information Systems
Tu N. Nguyen, Vincenzo Piuri, Lianyong Qi, Shahid Mumtaz, Warren Huang-Chen Lee
Summary: The papers in this special issue focus on technological innovations in wearable, implantable, mobile, and remote healthcare, including IoT, sensor informatics, and patient monitoring applications. These innovations track key health indicators to improve lifestyle and health disorders. IoT devices play a crucial role in helping patients manage their health conditions. The growing field of healthcare wearables presents opportunities for biomedical informatics research to solve complex healthcare problems and improve decision making.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Telecommunications
Zhenyu Zhou, Xinyi Chen, Haijun Liao, Zhong Gan, Fei Xiao, Qi Tu, Wenwen Sun, Yun Liu, Shahid Mumtaz, Mohsen Guizani
Summary: This paper proposes a multi-timescale VNF Embedding and floW Scheduling algorithm named NEWS to maximize throughput while reducing VNF embedding cost and energy consumption. The joint optimization problem is transformed into three subproblems, including large-timescale VNF embedding, small-timescale admission control, and small-timescale route selection and computation resource allocation. Simulations demonstrate that NEWS performs superior in terms of throughput, embedding cost, and energy consumption.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2023)
Article
Telecommunications
Zhiwei Guo, Keping Yu, Kostromitin Konstantin, Shahid Mumtaz, Wei Wei, Peng Shi, Joel J. P. C. Rodrigues
Summary: With the development of green wireless communication, the green Internet of Vehicles (GIoV) has emerged as a potential solution for future transportation. Intelligent traffic forecasting for key nodes in GIoV is a significant research topic. This work combines deep embedding and graph embedding to propose a deep collaborative intelligence-driven traffic forecasting model in GIoV, aiming to establish more reliable feature spaces and improve forecasting efficiency. Experimental results on a real-world dataset show a reduction in forecasting deviation by about 15%-25%.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2023)
Editorial Material
Engineering, Electrical & Electronic
Shahid Mumtaz, Mehmet Yuce, Jun Chen, Subhas Mukhopadhyay, Edward Sazonov, Joel J. P. C. Rodrigues, Chunsheng Zhu, Ikram Ashraf
IEEE SENSORS JOURNAL
(2023)
Article
Chemistry, Analytical
Yiming Huo, Xingqin Lin, Boya Di, Hongliang Zhang, Francisco Javier Lorca Hernando, Ahmet Serdar Tan, Shahid Mumtaz, Ozlem Tugfe Demir, Kun Chen-Hu
Summary: Massive MIMO, combined with leading-edge technologies, methodologies, and architectures, is set to be a cornerstone technology in the next-generation wireless systems. Recent advancements, such as intelligent reflecting surfaces, artificial intelligence, and Terahertz communications, are expected to enhance the capabilities and performance of future massive MIMO systems. Diverse applications, including wireless localization, vehicular communications, and inter-planetary communications, will continue to thrive.
Article
Computer Science, Hardware & Architecture
Mingxin Cai, Yutong Liu, Linghe Kong, Guihai Chen, Liang Liu, Meikang Qiu, Shahid Mumtaz
Summary: Flow monitoring is widely used in SDNs to monitor network performance and detect heavy hitters for DDoS attack prevention. Existing approaches either focus solely on accuracy or sacrifice accuracy for fast detection, lacking flexibility to meet different monitoring needs. To address this problem, we propose a novel flow monitoring framework, cReFeR, which achieves accuracy-ensured and resource-saving monitoring in SDNs by customizing monitoring services for applications and reducing the volume of flow statistics collection.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2023)
Article
Engineering, Civil
Ying Ju, Zhiwei Cao, Yuchao Chen, Lei Liu, Qingqi Pei, Shahid Mumtaz, Mianxiong Dong, Mohsen Guizani
Summary: This paper investigates the use of non-orthogonal multiple access for secure offloading in vehicular edge computing networks, considering the presence of multiple malicious eavesdropper vehicles. A joint optimization problem is formulated to minimize system energy consumption while satisfying computation delay constraints, and a learning algorithm-based scheme is proposed to solve the problem.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
