Nowadays intelligent vehicles are equipped with increasing resources for computing intensive driving applications. When these vehicles are parked, their unused computing resources can form a large pool of edge computi...
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ISBN:
(纸本)9798350378412
Nowadays intelligent vehicles are equipped with increasing resources for computing intensive driving applications. When these vehicles are parked, their unused computing resources can form a large pool of edge computing resources and be provided to support other parked vehicles or mobile devices with needs of offloading computing tasks. While the parked vehicles based edge computing assistance presents a novel computing paradigm, there is a challenging problem of potential computing service disruption as the parked intelligent vehicles (PIVs) leave the parking lots. To address this issue, we propose a joint offloading and service migration framework for vehicular edge computing in parking lots. In the framework, unfinished tasks can be migrated to another PIV or remained until completion to avoid task failures, and the processing results will be transmitted back through multi-hop relays between vehicles. Considering computing resource requirements of tasks and vehicle movement characteristics, we formulate the problem as a Markov Decision Process (MDP) to minimize task completion delays, with offloading stability constraints established for improving service completion sustainability. Due to dynamic multi-user scenarios and heterogeneous vehicular computing capabilities, the problem is difficult to model and solve. We thus propose a joint offloading and migration decision algorithm (JOMD3) based on dueling double deep Q network. Numerical results demonstrate that the proposed framework and algorithm can achieve lower average delay and faster convergence in comparison to baseline algorithms.
Connected vehicles rely on sophisticated software systems for diverse features, including navigation, entertainment, communication, and safety functions. As technology continues to advance, the reliance on software in...
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ISBN:
(纸本)9798350304367;9798350304374
Connected vehicles rely on sophisticated software systems for diverse features, including navigation, entertainment, communication, and safety functions. As technology continues to advance, the reliance on software in connected vehicles becomes increasingly integral to their overall performance and the delivery of innovative features. Therefore, in the domain of software-enabled automobiles, the implementation of over-the-air (OTA) software updates is deemed essential for the dissemination of software and fixes in connected vehicles. The conventional method of addressing this matter entailed manufacturers undertaking the task of recalling outdated vehicles;however, the central issue lies in the considerable challenge of effectively notifying owners through recall notices. This process gets further complicated by the presence of organizational and procedural obstacles, ultimately culminating in a significant number of vehicles operating on insecure and unstable software. In this paper, we present a multi-tier software update dissemination framework that systematically identifies appropriate fog nodes based on traffic density to optimize the convergence of updates. Furthermore, at the fog node, we advocate for a multi-agent labeling approach to identify pivotal vehicles capable of efficiently streaming received software updates to other vehicles. The updates are transmitted from the cloud to the fog node, which subsequently relays them through the labeled vehicles to reach other vehicles. Harnessing a fog distribution framework with multi-pivot schemes, the proposed approach has demonstrated a reduction in network convergence time compared to both single-vehicle and fog-based approaches.
technologyconvergence is one of the most efficient ways to make innovation. This study aims to predict the technologyconvergence in the defense field using link prediction. Based on the patent data from 2010 to 2019...
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ISBN:
(纸本)9781665421973
technologyconvergence is one of the most efficient ways to make innovation. This study aims to predict the technologyconvergence in the defense field using link prediction. Based on the patent data from 2010 to 2019, a link prediction model for convergencetechnology has been presented. The result shows that IT technologies are likely to play a crucial role in converging military technologies. In particular, measurement, control, and computing technologies are intermediaries, driving convergence across the present and future. While the importance of gunpowder and traditional weapon technologies will diminish, the importance of aircraft technologies such as drones will be greater. Furthermore, the network analysis shows that the convergence network structure will be more centralized and dense, which means that the convergence of technologies will strengthen in the future. This paper's main contribution is to present the future direction of defense R&D promotion from the viewpoint of technologyconvergence.
Emerging digital twins are garnering significant attention for the efficient management of complicated facilities and appliances. In the case of geographically dispersed edge clouds, the buildup and operation of digit...
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Stochastic gradient descent (SGD) is an optimization set of rules used to solve huge-scale optimization issues. It works by way of updating an approximate solution, primarily based on the gradient of the goal characte...
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In contrast to traditional computing, soft computing can be used to adjust prediction models and locate answers to difficult, real-world issues. Soft computing is more forgiving of ambiguity than classical computing. ...
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This paper is mainly the smart home system and some other intelligent devices and robot technology organic integration together, so that it can be more comprehensive for the robot service. At the same time, computer c...
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This paper investigates the distributed consensus computing problem over heterogeneous opportunistic networks with heterogeneity in communication, caching and computing power. In existing work on distributed consensus...
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A modified Grey Wolf Optimization (CGWO) algorithm is introduced, employing a cosine improvement factor strategy to address the challenges of slow convergence speed and low optimization accuracy encountered in the ini...
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This paper aims to investigate the ability of reconfigurable intelligent surfaces (RIS) damaged in multi-user environments to eliminate interference. Our research found that even if the RIS is damaged, interference ca...
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