This paper addresses high precision 5G positioning and dynamic tracking, which has risen increasingly attention from industry and academia recently. The recent works show that the position of user equipment (UE) could...
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We propose a SD-TSN-based overlay network scheme to realize deterministic transmission for edge computing distributed cloud in optical network. A gateway is implemented to establish data transmission tunnels among clo...
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This paper investigates the adaptive bitrate (ABR) video semantic communication over wireless networks. In the considered model, video sensing devices must transmit video semantic information to an edge server, to fac...
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Based on coupled network theory, a bounded time error model for network determinism is proposed. The limit of traffic scheduling performance affected by time synchronization error in cross-domain time-sensitive networ...
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This paper proposes a TSNDO scheme utilizing time-sensitive networking to discipline clocks, providing precise time for distributed networks. The experimental results demonstrate that TSNDO achieves the time accuracy ...
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A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or State Var system(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is...
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A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or State Var system(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its *** the inverse system method and the Linear Quadratic Regulation(LQR),an optimized SVC controller is *** simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.
In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refe...
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In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual scene,which results in high latency and energy consumption. Therefore, it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption. In this article, we aim at finding a tradeoff between latency and energy consumption. We formalize the computation offloading problem base on mobile edge computing(MEC)into a constrained multiobjective optimization problem(CMOP) and utilize NSGA-II to solve it. The simulation results demonstrate that NSGA-II can find the Pareto set, which reduces the latency and energy consumption effectively. In addition, a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the actual situation.
In view of the development of low-orbit satellite constellation and the increasing demand for computing ability and privacy protection of space-based applications, a satellite-based multi-task federated learning syste...
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Multiple unmanned aerial vehicles (UAVs) computation offloading plays a major role in the sixth generation (6G) mobile networks for resolving conflicts between computation-intensive or time-sensitive tasks and sensor ...
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ISBN:
(数字)9798350303582
ISBN:
(纸本)9798350303599
Multiple unmanned aerial vehicles (UAVs) computation offloading plays a major role in the sixth generation (6G) mobile networks for resolving conflicts between computation-intensive or time-sensitive tasks and sensor nodes (SNs) with limited capabilities. Emerging artificial intelligence businesses such as multimodal data confusion and multi-video streams processing bring new challenges to UAV-aided communication and computation networks due to their multi-point and streaming characteristics. This paper focuses on a multi-UAV aided multi-point streaming tasks scenario where the SNs generate subtasks comprising various workflows randomly in a service period. We model the sequential relationship between multi-point tasks and time constraints for different workflows and aim to minimize the average energy consumption of all SNs while satisfying different time constraints by jointly optimizing the UAV-SN association policy and UAV deployment locations. To address the non-convexity problem, we decompose the problem into two subproblems, which we then solve alternately with the Markov approximation algorithm and convex optimization until convergence. Numerical results show that the proposed algorithm can effectively lower the average energy consumption of all SNs by a maximum of 35.6% compared to other schemes while maintaining a successful service ratio of 93%.
Vehicular crowdsensing system plays an important role in monitoring the dynamic characteristics of real environment with the assistance of mobile edge computing (MEC). However, connected vehicles (CVs) continuously ge...
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