.png){kind=icon}
返回
Computation Efficient Task Offloading and Bandwidth Allocation in VEC Networks
.png){kind=icon}
OA
AI
DOI：10.1109/TVT.2024.3407356.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
With the development of intelligent connected vehicles, vehicular edge computing (VEC) systems can provide them with low latency and low energy consumption of task computation and data processing. In this paper, we propose a VEC-aided computing system by offloading tasks from vehicles to the edge computing node via the road side units (RSUs) to improve the computation efficiency. At first, we investigate the computation efficiency for task computation, regarded as the ratio of task bits to the cost in terms of the sum and latency and energy consumption. Then, we formulate a computation efficiency maximization problem to design the bandwidth allocation and task allocation. Due to the dynamically changing channels, available computational resource and bandwidth resource, the formulated optimization problem is non-convex. Therefore, we solve the joint bandwidth and task allocation problem by decoupling the original optimization problem into bandwidth allocation and task allocation sub-problems and solving them iteratively. At last, simulation results are provided to demonstrate that our proposed scheme performs better than the benchmark schemes.
Keyword:
Task analysis
Resource management
Computational efficiency
Optimization
Delays
Bandwidth
Computational modeling
Computation efficiency
task offloading
vehicular edge computing
期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
机构
引用论文
.png){kind=icon}
Joint Load Balancing and Offloading in Vehicular Edge Computing and Networks车载边缘计算和网络中的联合负载均衡和卸载
PREAI
分享收藏Design of recycling system for poly(methyl methacrylate) (PMMA). Part 1: recycling scenario analysis
PREAI
分享收藏
查看更多内容