Journal ArticleDOI
Mobile Edge Computing Enabled 5G Health Monitoring for Internet of Medical Things: A Decentralized Game Theoretic Approach
Zhaolong Ning,Peiran Dong,Xiaojie Wang,Xiping Hu,Lei Guo,Bin Hu,Yi Guo,Tie Qiu,Ricky Y. K. Kwok +8 more
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TLDR
In this article, a cost-efficient in-home health monitoring system for IoMT by dividing it into two sub-networks, i.e., intra-WBANs and beyond WBANs, is presented.Abstract:
The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home health monitoring networks. However, excessive requirements of patients result in insufficient spectrum resources and communication overload. Mobile Edge Computing (MEC) enabled 5G health monitoring is conceived as a favorable paradigm to tackle such an obstacle. In this paper, we construct a cost-efficient in-home health monitoring system for IoMT by dividing it into two sub-networks, i.e., intra-Wireless Body Area Networks (WBANs) and beyond-WBANs. Highlighting the characteristics of IoMT, the cost of patients depends on medical criticality, Age of Information (AoI) and energy consumption. For intra-WBANs, a cooperative game is formulated to allocate the wireless channel resources. While for beyond-WBANs, considering the individual rationality and potential selfishness, a decentralized non-cooperative game is proposed to minimize the system-wide cost in IoMT. We prove that the proposed algorithm can reach a Nash equilibrium. In addition, the upper bound of the algorithm time complexity and the number of patients benefiting from MEC is theoretically derived. Performance evaluations demonstrate the effectiveness of our proposed algorithm with respect to the system-wide cost and the number of patients benefiting from MEC.read more
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Posted Content
Age of Information: An Introduction and Survey
TL;DR: The current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients is described and AoI timeliness metrics are described.
Journal ArticleDOI
Age of Information: An Introduction and Survey
TL;DR: In this paper, the authors summarize recent contributions in the broad area of AoI and present general AoI evaluation analysis that are applicable to a wide variety of sources and systems, starting from elementary single-server queues, and applying these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks.
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Dynamic-Fusion-Based Federated Learning for COVID-19 Detection
Weishan Zhang,Tao Zhou,Qinghua Lu,Xiao Wang,Chunsheng Zhu,Haoyun Sun,Zhipeng Wang,Sin Kit Lo,Fei-Yue Wang +8 more
TL;DR: The proposed novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections is feasible and performs better than the default setting of federatedLearning in terms of model performance, communication efficiency, and fault tolerance.
Journal ArticleDOI
Resource Scheduling in Edge Computing: A Survey
TL;DR: In this article, the authors present the architecture of edge computing, under which different collaborative manners for resource scheduling are discussed, and introduce a unified model before summarizing the current works on resource scheduling from three research issues.
Journal ArticleDOI
Distributed and Dynamic Service Placement in Pervasive Edge Computing Networks
Zhaolong Ning,Peiran Dong,Xiaojie Wang,Shupeng Wang,Xiping Hu,Song Guo,Tie Qiu,Bin Hu,Ricky Y. K. Kwok +8 more
TL;DR: This work first utilizes Lyapunov optimization method to decompose the long-term optimization problem into a series of instant optimization problems, then a sample average approximation-based stochastic algorithm is proposed to approximate the future expected system utility.
References
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Journal ArticleDOI
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
TL;DR: In this article, a game theoretic approach for computation offloading in a distributed manner was adopted to solve the multi-user offloading problem in a multi-channel wireless interference environment.
Journal ArticleDOI
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
He Li,Kaoru Ota,Mianxiong Dong +2 more
TL;DR: This article first introduces deep learning for IoTs into the edge computing environment, and designs a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing.
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Fog Assisted-IoT Enabled Patient Health Monitoring in Smart Homes
Prabal Verma,Sandeep K. Sood +1 more
TL;DR: Results depict that the proposed Bayesian belief network classifier-based model has high accuracy and response time in determining the state of an event when compared with other classification algorithms, which enhances the utility of the proposed system.
Journal ArticleDOI
Sub-Channel Assignment, Power Allocation, and User Scheduling for Non-Orthogonal Multiple Access Networks
Boya Di,Lingyang Song,Yonghui Li +2 more
TL;DR: This paper proposes a matching algorithm, which converges to a two-side exchange stable matching after a limited number of iterations, and shows that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonalmultiple access scheme.