Research on energy management of multi-user mobile edge computing offloading by Luyao WANG, Wenqian ZHANG, Guanglin ZHANG

“…In mobile edge computing system,the quality of computing experience can be improved greatly by offloading computing tasks from mobile devices to mobile edge computing servers.Consider incorporating renewable energy into a multi-user mobile edge system.Moreover,a battery as an energy harvesting device was added to the model to harvest energy and storage.The task allocation strategy in mobile edge computing system was formulated through the resource management algorithm based on reinforcement learning,which achieved the cost minimization of mobile devices (including delay cost and computing cost).The simulation results show that the proposed algorithm significantly minimizes the cost of mobile devices compared with other algorithms.…”
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Research on energy management of multi-user mobile edge computing offloading by Luyao WANG, Wenqian ZHANG, Guanglin ZHANG

“…In mobile edge computing system,the quality of computing experience can be improved greatly by offloading computing tasks from mobile devices to mobile edge computing servers.Consider incorporating renewable energy into a multi-user mobile edge system.Moreover,a battery as an energy harvesting device was added to the model to harvest energy and storage.The task allocation strategy in mobile edge computing system was formulated through the resource management algorithm based on reinforcement learning,which achieved the cost minimization of mobile devices (including delay cost and computing cost).The simulation results show that the proposed algorithm significantly minimizes the cost of mobile devices compared with other algorithms.…”
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Adaptive Fuzzy PID Control System for Satellite Earth Station Antenna Group Factor Based on Edge Calculation by Haibin SHAN, Yanjun SHI, Zijing LIU, Yuanhong LI, Wenhua ZHAO, Muquan HE, Chuzhou LI

“…The antenna tracking control system of satellite ground receiving station generally adopts PID control.Due to the infl uence of various uncertain factors, it is diffi cult to obtain the optimal control parameters for this kind of system, resulting in the PID control eff ect is not ideal.An adaptive fuzzy PID antenna tracking control system based on edge computing was designed.The parameters of PID controller were adjusted in time by fuzzy control algorithm, and the optimal calculation of fuzzy control input and output domain was realized in edge computing server.The simulation results showed that the adaptive fuzzy PID antenna tracking control system based on edge calculation could achieve good control eff ect.…”
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Ensemble Federated Learning Approach for Diagnostics of Multi-Order Lung Cancer by Umamaheswaran Subashchandrabose, Rajan John, Usha Veerasamy Anbazhagu, Vinoth Kumar Venkatesan, Mahesh Thyluru Ramakrishna

“…Hence, this is limited by the availability and quality of data at the centralized computing server. In this paper, we propose an ensemble Federated Learning-based approach for multi-order lung cancer classification. …”
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Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models by Le Thi My Hanh, Nguyen Thanh Binh, Khuat Thanh Tung

“…This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. …”
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Evaluation of the Cost of Intelligent Upgrades of Transportation Infrastructure for Intelligent Connected Vehicles by Zongwei Liu, Haokun Song, Hong Tan, Han Hao, Fuquan Zhao

“…The costs of RSUs, LIDARS, and edge computing servers as well as data transmission rate of 5G are key elements affecting the costs of intelligent upgrades of transportation infrastructure.…”
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A Lightweight Optimal Scheduling Algorithm for Energy-Efficient and Real-Time Cloud Services by Joohyung Sun, Hyeonjoong Cho

“…To support ever-chainging user needs such as large storage volumes, web search, and high-performance computing, numerous companies have expanded their systems to cloud computing servers. Cloud environment systems generally consume large amounts of electrical power, leading to tremendously high operational costs. …”
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Task Offloading Strategy of Vehicular Networks Based on Improved Bald Eagle Search Optimization Algorithm by Xianhao Shen, Zhaozhan Chang, Xiaolan Xie, Shaohua Niu

“…A task offloading model combining local vehicle computing, MEC (Mobile Edge Computing) server computing, and cloud computing is proposed. …”
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Flow-of-traffic prediction program based mobile edge computing for Internet of vehicles using double auction by Yan LIN, Shuai YAN, Yijin ZHANG, Chunguo LI, Feng SHU

“…With an aim of maximizing the efficiency of edge offloading and the resource utilization of edge computing server simultaneously, a new flow-of-traffic prediction based edge computing offloading solution was proposed for Internet of vehicles (IoV).Firstly, both the efficiency utility function of vehicle and the resource utilization of mobile edge computing (MEC) server were established by considering task priority.Next, the formulated dual-objective optimization problem was transformed into a double auction problem between vehicles and MEC servers.Finally, based on the designed flow-of-traffic based pricing function of vehicle and MEC server, a McAfee auction algorithm was adopted to complete the edge computing process.Simulation results show that benefiting from the flow-of-traffic prediction information, the proposed solution can significantly improve both the efficiency of computation offloading and the utilization of computation resource.…”
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A BiGRU Model Based on the DBO Algorithm for Cloud-Edge Communication Networks by Zhiyong Zha, Jianwen He, Lei Zhen, Mingyang Yu, Chenxi Dong, Zhikang Li, Geng Wu, Haoran Zuo, Kai Peng

“…With the development of IoT technology, central cloud servers and edge-computing servers together form a cloud–edge communication network to meet the increasing demand for computing tasks. …”
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Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing by Guangshun Li, Yuncui Liu, Junhua Wu, Dandan Lin, Shuaishuai Zhao

“…Cloud computing technology is widely used at present. However, cloud computing servers are far from terminal users, which may lead to high service request delays and low user satisfaction. …”
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Flow-of-traffic prediction program based mobile edge computing for Internet of vehicles using double auction by Yan LIN, Shuai YAN, Yijin ZHANG, Chunguo LI, Feng SHU

“…With an aim of maximizing the efficiency of edge offloading and the resource utilization of edge computing server simultaneously, a new flow-of-traffic prediction based edge computing offloading solution was proposed for Internet of vehicles (IoV).Firstly, both the efficiency utility function of vehicle and the resource utilization of mobile edge computing (MEC) server were established by considering task priority.Next, the formulated dual-objective optimization problem was transformed into a double auction problem between vehicles and MEC servers.Finally, based on the designed flow-of-traffic based pricing function of vehicle and MEC server, a McAfee auction algorithm was adopted to complete the edge computing process.Simulation results show that benefiting from the flow-of-traffic prediction information, the proposed solution can significantly improve both the efficiency of computation offloading and the utilization of computation resource.…”
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Distributed task offloading in a multi-tier cloud infrastructure by Pandey, Pratyush Kumar

“…With the advent of edge computing, computational servers were brought closer to end devices to reduce the latency of offloading tasks. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Cloud Manufacturing: Tinjauan Literatur dan Pengembangan Layanannya untuk Perencanaan Fasilitas Produksi by Agus Sutanto

“… Cloud Manufacturing is an advanced manufacturing model which provides services by utilizing a shared resource pool such as computers, servers, networking, Internet and application softwares. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Continual learning approaches for single cell RNA sequencing data by Gorkem Saygili, Busra OzgodeYigin

“…Loading even a single dataset into the memory of an ordinary, off-the-shelf computer can be infeasible, and using computing servers might not always be an option. This paper presents continual learning as a solution to such hardware bottlenecks. …”
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Studies on energy performances of green data centres by Toh, Wee Lun.

“…Data centers are special facilities that house various equipments such as computers, servers, racks and related IT hardware. They are used to store, manage, process and exchange digital data and information. …”
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Review on Green Technology Implementation Challenges in University Data Centre by Mohd, Rashid, Noraziah, Ahmad

“…A data centre is a network of computer servers used by an organization to either save, process or distribute large amounts of data. …”
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Influence of cellulose nanofiber fluid on flow instability and heat transfer of two-phase closed thermosyphon by Chan hee Lee, Seong-Won Seo, Dong Kyou Park, Kwon-Yeong Lee

“…Additionally, the findings of this study can be applied to solar thermal power generation or heat pipe research for cooling strategies in computing servers, depending on the input heat load.…”
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