面向物联网的网内计算移动边缘卸载架构

IF 5.5 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Services Computing Pub Date : 2024-09-18 DOI:10.1109/TSC.2024.3463475
Di Wu;Zunliang Wang;Huijiang Pan;Haipeng Yao;Tianle Mai;Song Guo
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引用次数: 0

摘要

近年来,物联网(IoT)设备和应用的快速增长对现有的移动边缘计算(MEC)架构提出了重大挑战。MEC架构中固有的延迟不确定性使得它难以支持自动驾驶汽车等对延迟敏感的应用。此外,连接设备数量的增加导致了MEC服务器有限吞吐量方面的重大挑战。随着最近可编程网络硬件(如smartnic和可编程交换机)的进步,基于网络的计算(network -based Computing, NBC)范式得到了广泛的关注。利用线速率处理能力,NBC为高吞吐量和低延迟处理提供了一个很有前途的解决方案。本文旨在探讨将NBC整合到现有MEC架构中的潜在好处和挑战。我们提出的架构的可行性使用两个用例进行了评估,线性二次调节器(LQR)控制和复杂事件处理(CEP),显示了延迟性能的显着改善。
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In-Network Computing Empowered Mobile Edge Offloading Architecture for Internet of Things
In recent years, the rapid growth of Internet of Things (IoT) devices and applications has posed significant challenges for existing Mobile Edge Computing (MEC) architectures. The inherent latency uncertainties in MEC architectures make it difficult to support latency-sensitive applications such as autonomous vehicles. Additionally, the increasing number of connected devices has led to substantial challenges in terms of limited throughput for MEC servers. With the recent advancements in programmable network hardware, such as SmartNICs and programmable switches, the Network-based Computing (NBC) paradigm has gained widespread attention. Leveraging line-rate processing capabilities, NBC offers a promising solution for high throughput and low latency processing. This paper aims to explore the potential benefits and challenges of incorporating NBC into existing MEC architectures. The feasibility of our proposed architecture is evaluated using two use cases, Linear Quadratic Regulator (LQR) control and Complex Event Processing (CEP), demonstrating significant improvements in latency performance.
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来源期刊
IEEE Transactions on Services Computing
IEEE Transactions on Services Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
11.50
自引率
6.20%
发文量
278
审稿时长
>12 weeks
期刊介绍: IEEE Transactions on Services Computing encompasses the computing and software aspects of the science and technology of services innovation research and development. It places emphasis on algorithmic, mathematical, statistical, and computational methods central to services computing. Topics covered include Service Oriented Architecture, Web Services, Business Process Integration, Solution Performance Management, and Services Operations and Management. The transactions address mathematical foundations, security, privacy, agreement, contract, discovery, negotiation, collaboration, and quality of service for web services. It also covers areas like composite web service creation, business and scientific applications, standards, utility models, business process modeling, integration, collaboration, and more in the realm of Services Computing.
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