CFEC: An Ultra-Low Latency Microservices-Based In-Network Computing Framework for Information-Centric IoVs

IF 5.8 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.2024.3463413
Muhammad Salah ud din;Muhammad Atif ur Rehman;Byung-Seo Kim
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Abstract

The advancement of vehicular onboard units (OBUs) has led to compute-intensive and delay-sensitive vehicular applications. Undeniably edge-assisted static roadside computing terminal (sRCT) offers immediate computations, a surge of smart vehicles and intensive computation requests during crowded hours may overload the sRCT, leading to performance degradation and intolerable delays. Therefore, to facilitate proximate computations and achieve ultra-low latency, this article envisions a Consortium of mobile vehicular Fog, Edge, and Cloud (CFEC) an ultra-low latency microservices-centric in-network computing framework for vehicular Named Data networks (VNDN). CFEC develops a fog-profiler-assisted mobile vehicular fog based on vehicles’ mobility patterns and available resource characteristics to ensure reliable computation offloading and reverse-path stability in a dynamic vehicular environment. Furthermore, CFEC introduces an intermediary ZTMC controller that effectively filters out underutilized sRCTs and routes computation requests to nearby, filtered sRCTs, thus minimizing transmission time and accelerating computations even during crowded hours. Simulations results revealed that CFEC significantly reduces computational satisfaction delays by up to 32.5%, 48.5%, and 31.9%, 51.025% against varying interest and node rates, respectively while in extreme traffic conditions, CFEC achieved an impressive computation satisfaction ratio of around 85% compared with benchmark schemes.
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CFEC:面向以信息为中心的物联网的基于超低延迟微服务的网内计算框架
车载单元(OBUs)的发展导致了计算密集型和延迟敏感的车载应用。不可否认,边缘辅助静态路边计算终端(sRCT)提供即时计算,智能车辆的激增和密集的计算请求可能会使sRCT过载,导致性能下降和无法忍受的延迟。因此,为了促进近似计算并实现超低延迟,本文设想了一个移动车辆雾、边缘和云(CFEC)联盟,这是一个用于车辆命名数据网络(VNDN)的超低延迟以微服务为中心的网络内计算框架。CFEC基于车辆的移动模式和可用资源特性,开发了一种雾廓线辅助的移动车辆雾,以确保在动态车辆环境下可靠的计算卸载和反向路径稳定性。此外,CFEC引入了一个中间ZTMC控制器,该控制器有效地过滤掉未充分利用的srct,并将计算请求路由到附近的过滤srct,从而最大限度地减少传输时间并加速计算,即使在拥挤的时间。模拟结果表明,CFEC在不同利率和节点率下,计算满意度延迟分别显著降低了32.5%、48.5%和31.9%、51.025%,而在极端交通条件下,与基准方案相比,CFEC的计算满意度达到了85%左右。
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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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