Dynamic Task Offloading for Cloud-Assisted Vehicular Edge Computing Networks: A Non-Cooperative Game Theoretic Approach

Article Telecommunications

Cooperative vehicles-assisted task offloading in vehicular networks

Yaping Cui et al.

Summary: This paper proposes a task offloading strategy based on cooperation among vehicles, using parallel computing to provide low-delay computation services and decrease the total system delay.

TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES (2022)

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Article Computer Science, Information Systems

Task offloading in vehicular edge computing networks via deep reinforcement learning

Elham Karimi et al.

Summary: This paper proposes a solution for cooperation between MEC and central cloud decisions in vehicular networks to address resource limitations and high mobilities. Utilizing deep reinforcement learning, the network dynamics can be automatically learned to quickly find optimal solutions.

COMPUTER COMMUNICATIONS (2022)

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Article Mathematics

Task-Offloading Strategy Based on Performance Prediction in Vehicular Edge Computing

Feng Zeng et al.

Summary: This paper proposes a prediction-based task-offloading scheme for vehicular edge computing, aiming to achieve rapid computing service. By utilizing a deep-learning model to predict task-offloading result and service delay, the proposed scheme selects the optimal strategy for offloading tasks. Simulation results demonstrate the importance of each part of the proposed model and show that the scheme outperforms other methods in terms of performance.

MATHEMATICS (2022)

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Article Computer Science, Information Systems

Computation Offloading in Heterogeneous Vehicular Edge Networks: On-Line and Off-Policy Bandit Solutions

Arash Bozorgchenani et al.

Summary: This paper discusses the computation offloading problem in a vehicular edge computing (VEC) scenario and proposes learning-based solutions to tackle this challenge. By selecting the least congested network and optimizing base station selection and relaying mechanism, the proposed solutions reduce the latency of offloaded tasks and minimize task loss.

IEEE TRANSACTIONS ON MOBILE COMPUTING (2022)

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Article Computer Science, Hardware & Architecture

Vehicular Edge Computing and Networking: A Survey

Lei Liu et al.

Summary: Vehicular Edge Computing (VEC) is a promising solution that pushes computational and storage resources to the edge of networks, enabling low latency and reduced bandwidth consumption for vehicular users. Research in VEC includes an overview, applications, research topics, literature review, and future directions.

MOBILE NETWORKS & APPLICATIONS (2021)

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Article Engineering, Civil

Volunteer Assisted Collaborative Offloading and Resource Allocation in Vehicular Edge Computing

Feng Zeng et al.

Summary: The paper investigates the effective utilization of idle resources in volunteer vehicles to handle overloaded tasks in VEC servers, proposing a model and algorithm based on Stackelberg game. Through extensive simulations, the proposed scheme's effectiveness is demonstrated in reducing offloading costs for vehicles and improving utility for VEC servers.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)

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Article Chemistry, Analytical

Research on a Task Offloading Strategy for the Internet of Vehicles Based on Reinforcement Learning

Shuo Xiao et al.

Summary: This study introduces a task offloading algorithm for the Internet of Vehicles, utilizing local-edge clouds and reinforcement learning to optimize computing efficiency. The algorithm increases task success probability and achieves a balance between various constraints on utility.

SENSORS (2021)

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Article Computer Science, Information Systems