Computation migration and resource allocation in heterogeneous vehicular networks: a deep reinforcement learning approach

H Wang, H Ke, G Liu, W Sun - IEEE Access, 2020 - ieeexplore.ieee.org
With the development of 5G technology, the requirements for data communication and
computation in emerging 5G-enabled vehicular networks are becoming increasingly …

Distributed convex relaxation for heterogeneous task replication in mobile edge computing

P Dai, B Han, X Wu, H Xing, B Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) is expected to support real-time services at wireless
networks, where task replication is applied to guarantee job completion within a strict …

Online optimization of energy-efficient user association and workload offloading for mobile edge computing

J Zhang, Q Cui, X Zhang, W Ni, X Lyu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper presents a new stochastic optimization framework for user association and task
offloading in mobile edge computing (MEC) networks with spatial and temporal variations of …

Latency-energy joint optimization for task offloading and resource allocation in mec-assisted vehicular networks

Y Cong, K Xue, C Wang, W Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, we study the task offloading problem on mobile edge in vehicular networks.
Specifically, we take computational resource constraints into consideration, and aim to …

Exploring hybrid active-passive RIS-aided MEC systems: From the mode-switching perspective

H Xie, D Li, B Gu - IEEE Transactions on Wireless …, 2024 - ieeexplore.ieee.org
Mobile edge computing (MEC) has been regarded as a promising technique to support
latency-sensitivity and computation-intensive serves. However, the low offloading rate …

[HTML][HTML] A multi-objective approach for optimizing edge-based resource allocation using TOPSIS

H Mohamed, E Al-Masri, O Kotevska, A Souri - Electronics, 2022 - mdpi.com
Existing approaches for allocating resources on edge environments are inefficient and lack
the support of heterogeneous edge devices, which in turn fail to optimize the dependency on …

Resource competition in blockchain networks under cloud and device enabled participation

Y Liang, Y Li, J Guo, Y Li - IEEE Access, 2022 - ieeexplore.ieee.org
Blockchain technology is a promising resource management architecture due to its ability of
building trust in a decentralized transaction. Block mining participants, ie miners, are …

Computation power maximization for mobile edge computing enabled dense network

Z Wan, X Dong - Computer Networks, 2023 - Elsevier
High-density connection is among the natures of next-generation wireless communication
systems. Meanwhile, various computation-intensive smart applications are becoming …

Resource scheduling for delay minimization in multi-server cellular edge computing systems

Y Zhang, P Du, J Wang, T Ba, R Ding, N Xin - IEEE Access, 2019 - ieeexplore.ieee.org
This paper studies resource scheduling for delay minimization in multi-server cellular edge
computing systems. The traditional method defines queue length-based Lyapunov functions …

PLHAS: Privacy-preserving localized hybrid authentication scheme for large scale vehicular ad hoc networks

F Altaf, S Maity - Vehicular Communications, 2021 - Elsevier
Existing authentication schemes for vehicular ad hoc networks (VANETs) are not scalable to
high-density and safety-critical VANETs. These schemes ignore the very important and …