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检索条件"主题词=computing offloading"

共 129 条记录，以下是31-40 订阅

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Joint Dynamic Pricing and computing offloading in Edge-to-Cloud Collaboration 27

Joint Dynamic Pricing and Computing Offloading in Edge-to-Cl...

引用

27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Yin, Tong Chen, Xin Jiao, Libo Liao, Jiaxuan Beijing Informat Sci & Technol Univ Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9798350349184;9798350349191

With the continuous development of integrated satellite ground networks, edge servers are laid out on low orbit earth (LEO) satellites to provide seamless services for some remote areas. In order to further improve service quality for mobile devices, the collaborative work between edge and cloud has received widespread attention. In this article, we consider the scenario of insufficient base station (BS) coverage in remote areas and investigate a hybrid model of computing offloading and resource allocation for edge cloud collaborative computing, in which edge servers with limited resources collaborate with the cloud by purchasing cloud computing resources. In this way, cloud server (CS) and edge servers separately price their computing and storage resources to stimulate each other to participate in cooperation and maximize their respective utility. We jointly optimize the size of offloading tasks, offloading strategies for devices and resource pricing issues for edge servers and CS based on comprehensive consideration of price cost, energy cost and latency limitation. A multi-level Stackelberg game is formulated among the CS (leader), BSs (followers) and satellites (followers) in level I-II, the BSs (leaders), satellites (leaders) and IoT devices (followers) in level II-III. Furthermore, we prove the existence and uniqueness of Stackelberg equilibrium (SE) in Stackelberg game. The SERI algorithm is proposed and simulations is conducted to show that SERI algorithm has good convergence performance and better entity utility.

关键词： computing offloading Edge-to-Cloud Collaboration Integrated Satellite Ground Networks Game Theory

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A Novel Edge computing offloading and Privacy-preserving Scheme for Energy Internet 5

A Novel Edge Computing Offloading and Privacy-preserving Sch...

引用

5th IEEE International Conference on Cryptography, Security and Privacy (CSP)

作者： Li, Kunchang Han, Xu Yang, Yifan Wang, Shuhao Shi, Runhua Li, Jianbin North China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China

ISBN: (纸本)9781728186214

With the rapid development of Internet of things technology, "massive" data generated by Internet of things terminals, which leads to the problem of excessive cloud computing pressure and network delay. Therefore, edge computing emerges as the time requires. At the same time, the privacy security of edge computing is particularly important. In this paper, ZSS short signature algorithm and Paillier homomorphic cryptosystem are used to propose a secure and efficient edge computing privacy-preserving in energy Internet. The scheme can achieve data confidentiality and privacy-preserving. Finally, the model of unloading is established to solve the problem quickly. Experimental results show that our scheme has less computation and communication overhead.

关键词： energy internet edge computing privacy-preserving data aggregation computing offloading

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Double DQN Based Associative Tasks computing offloading Scheme for Internet of Medical Things 34

Double DQN Based Associative Tasks Computing Offloading Sche...

引用

IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Jiang, Fan Qin, Junwei Wang, Junxuan Guo, Mengyan Shaanxi Key Lab Informat Commun Network & Secur Xian Peoples R China Xian Univ Posts & Telecommun Xian Peoples R China Xidian Univ Xian Peoples R China

ISBN: (纸本)9781665464833

Internet of Medical Things (IoMT) is regarded as an imperative technology for intelligent healthcare in the foreseeable 6G era. Due to the limited computing power of edge devices and task-related coupling, IoMT faces significant challenges. Considering the associative relationship among tasks, this paper proposes a computing offloading policy for multiple-user devices (UDs) under a multi-access edge computing (MEC) system. Specifically, we formulate the offloading scheme as a mixed-integer nonconvex optimization problem to minimize the total delay and energy consumption. To obtain the optimal solution, a double deep Q-network (Double DQN) based associative tasks computing offloading (DDATO) algorithm is then proposed, which can make the best offloading decision under the condition that tasks of UDs are associative. In addition, we use a dynamic epsilon-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods, the proposed algorithm can lower the total cost more efficiently within the maximum delay and energy consumption tolerance.

关键词： Internet of Medical Things (IoMT) Multi-access Edge computing (MEC) Associative Tasks Double Deep Q-Network computing offloading

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The Privacy Preserving In computing offloading 2

The Privacy Preserving In Computing Offloading

引用

2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Zhao, Meng Li, Shuyu Shaanxi Normal Univ Sch Comp Sci Xian Shaanxi Peoples R China

ISBN: (纸本)9781467390262

Recently, computing offloading is a technology to solve the problem of the constraint of the mobile device, such as the power, memory and so on. Meantime, when the users decide to offloading, they must make sure that the data cannot be revealed. In this paper presents an overview of the privacy preserving in computing offloading from the perspectives of the offloading strategies, the energy performance, the technologies for privacy and security protecting in computation offloading decision. What's more, this paper give the flowchart of the privacy preserving in computation offloading. Finally, the author describes directions for future researches.

关键词： computing offloading privacy preserving

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An Energy-efficient computing offloading Framework for Blockchain-enabled Video Streaming Systems

An Energy-efficient Computing Offloading Framework for Block...

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IEEE Global Communications Conference (GLOBECOM)

作者： Yuan, Shijing Li, Jie Zhu, Yuxuan Wu, Chentao Ding, Yue Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Univ Michigan Shanghai Jiao Tong Univ Joint Inst Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Software Shanghai Peoples R China

ISBN: (纸本)9781665435406

Blockchain and edge computing have been widely applied in video streaming systems. However, previous works lack a joint consideration of video redundancy and full utilization of edge resources (bandwidth resources, CPU frequency), resulting in suboptimal performance of video streaming systems. In this paper, we propose a computing offloading framework for blockchain-enabled video streaming systems to fully exploit edge resources and reduce energy consumption. Specifically, we formulate computing offloading, resource allocation, and adaptive compression as a joint optimization problem. We transform and decompose the original non-convex problem and propose an algorithm based on the alternating direction method of multipliers (ADMM) to solve the decomposed problem in a distributed manner. Simulation results demonstrate that our scheme can effectively reduce energy consumption and fully utilize the bandwidth and computational resources.

关键词： Edge computing blockcahin computing offloading resource allocation adaptive compression

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Energy-Efficient Trajectory Design and computing offloading in UAV-aided IoT Networks

Energy-Efficient Trajectory Design and Computing Offloading ...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Chen, Shijia Du, Pengfei Liu, Ziyue Qing, Chaojin Zhang, Xuejun Xihua Univ Engn Res Ctr Intelligent Air Ground Integrated Ve Minist Educ Chengdu 610039 Peoples R China Beijing Univ Aeronaut & Astronaut Sch Elect Informat & Engn Beijing 100191 Peoples R China

ISBN: (纸本)9798350377675;9798350377682

In this paper, we propose to minimize the total energy expenditure in unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) internet of things (IoT) networks by employing the non-orthogonal multiple access (NOMA). Considering the obstacles of an urban city environment, a composite optimization model incorporating both the flight trajectory and computational offloading is initially formulated. To address this non-convex problem, the original problem is converted into two independent subproblems, and then an energy-efficient trajectory design and computing offloading algorithm is developed by employing the successive convex approximation (SCA) and quadratic approximation approaches. Moreover, comprehensive simulation results verify that the proposed algorithm achieves a decrease in weighted energy expenditure by 14.8% in comparison to the algorithms employing a fixed trajectory, fixed transmit power, and the orthogonal multiple access (OMA).

关键词： UAV-aided IoT networks MEC NOMA trajectory optimization computing offloading

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An Area-based offloading Policy for computing offloading in MEC-assisted Wireless Mesh Network

An Area-based Offloading Policy for Computing Offloading in ...

引用

IEEE/CIC International Conference on Communications in China (ICCC)

作者： Shi, Wenxiao Zhang, Jiadong Zhang, Ruidong Hu, Kegang Jilin Univ Coll Commun Engn Changchun 130012 Peoples R China

ISBN: (纸本)9781728107325

Mobile edge computing (MEC) enables cloud computing capabilities at the edge of network with close proximity and low latency. Wireless mesh network (WMN) is a multi-hop communications network with features such as decentralization, scalability, and self-organization. The MEC-assisted WMN has very promising applications, which can be implemented in some special environments such as battlefield surveillance, disaster incidents, and emergency situations. In this paper, we use ns3 network simulator to build a mobile edge mesh computing (MEMC) system. We design an area-based offloading policy (ABOP) algorithm. Our numerical results demonstrate an improved performance, where mesh client can offload as many tasks as possible in different areas with low delay and high competition ratio.

关键词： Mobile edge computing wireless mesh network computing offloading

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Big Data Driven computing offloading Scheme with Driverless Vehicles Assistance 17

Big Data Driven Computing Offloading Scheme with Driverless ...

引用

IEEE 17th Int Conf on Dependable, Autonom and Secure Comp / IEEE 17th Int Conf on Pervas Intelligence and Comp / IEEE 5th Int Conf on Cloud and Big Data Comp / IEEE 4th Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)

作者： Chen, Chengling Su, Zhou Li, Weiwei Wang, Yuntao Shanghai Univ Sch Mech & Automat Shanghai Peoples R China

ISBN: (纸本)9781728130248

In the era of big data, edge computing is emerged as a promising paradigm to alleviate the pressure on the backbone network and facilitate vehicular services on the road. As edge nodes deployed for vehicular applications, roadside units (RSUs) need to undertake a large number of local computing tasks. However, due to the uncertainty of the vehicular network topology, static RSU deployments are subject to short-term overload and cannot handle various delay-sensitive computing tasks concurrently. To address the problem, we propose a big data driven computing offloading scheme to dispatch idle driverless vehicles to enhance the capacities of RSUs dynamically. First, we present a trust assessment model to evaluate the credibility of driverless vehicles. Then, a multi-attribute reverse auction is applied to maximize the utilities of RSUs and driverless vehicles. In addition, a secure forwarding method is developed to protect the privacy of computing tasks.

关键词： Vehicular ad-hoc networks reverse auction computing offloading driverless vehicles

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Multi-Layer Resource computing offloading Based on Power Price Difference 23

Multi-Layer Resource Computing Offloading Based on Power Pri...

引用

23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Wang, Bo Guo, Chengrui Huang, Dongyan Guilin University of Electronic Technology Key Laboratory of Wideband Communication and Signal Processing Guilin China

ISBN: (纸本)9798350325959

Sixth-generation (6G) mobile communication technologies will drive convergence in areas such as cloud computing and multi-access edge computing (MEC) through integrated satellite-terrestrial networks, aiming to provide quality computing services to user equipment (UE). However, it is important to note that the power price may vary among different regions. This paper aims to study a multi-layer computing resource system that takes into account power price differences. For the multi-layer resource computing offloading problem, the optimization objective is defined as minimizing the weighted sum of the time cost and offloading cost. To address this problem, a Q-Learning-based multi-layer resource offloading (Q-MRO) scheme is proposed. Simulation results show that the Q-MRO scheme can obtain a lower total cost compared with other benchmark schemes. © 2023 IEEE.

关键词： computing offloading Multi-access edge computing (MEC) Multi-layer resource Power price Q-Learning

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Cost-Efficient computing offloading in computing First Networks Supported by EONs

Cost-Efficient Computing Offloading in Computing First Netwo...

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2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Xin, Jingjie Li, Xin Zhang, Lu Zhao, Chenyu Zhang, Yongjun Huang, Shanguo Schoolg of Electronic and Engineering Beijing University of Posts and Telecommunications Beijing China

This paper proposes a cost-efficient computing offloading (CECO) scheme to determine offloading decisions for requests arriving at EON-supported computing first networks. Results show CECO can improve acceptance ratio... 详细信息

ISBN: (纸本)9798350312614

关键词： computing first network computing offloading cost-efficient resource allocation

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