Multi-access edge computing offloading in maritime monitoring sensor networks

Xin SU; Ziyi WANG; Yupeng WANG; Siyuan ZHOU

doi:10.11959/j.issn.2096-3750.2021.00205

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Multi-access edge computing offloading in maritime monitoring sensor networks

Topic: Edge Intelligence and Fog Computing in IoT | 更新时间：2024-06-05

- Multi-access edge computing offloading in maritime monitoring sensor networks
- Chinese Journal on Internet of Things Vol. 5, Issue 1, Pages: 36-52(2021)
- 作者机构：
  
  1. 河海大学物联网工程学院，江苏常州 213002
  2. 沈阳航空航天大学电子信息工程学院，辽宁沈阳 110136
  3. 河海大学计算机与信息学院，江苏南京 211106
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2021.00205
  CLC： TN929.52
- Published：30 March 2021，
  
  Published Online：2021-03，
- 稿件说明：
移动端阅览
XIN SU, ZIYI WANG, YUPENG WANG, et al. Multi-access edge computing offloading in maritime monitoring sensor networks. [J]. Chinese journal on internet of things, 2021, 5(1): 36-52.
DOI：

XIN SU, ZIYI WANG, YUPENG WANG, et al. Multi-access edge computing offloading in maritime monitoring sensor networks. [J]. Chinese journal on internet of things, 2021, 5(1): 36-52. DOI： 10.11959/j.issn.2096-3750.2021.00205.

摘要

多接入边缘计算（MAC

multi-access edge computing）可有效保障海洋观监测传感器网络（简称传感网）的低时延、高可靠数据传输及其各类相关海事应用。在近海场景下，结合边缘计算资源分布建立多用户单跳单播（MSU

multi-user single-hop unicast）与多用户多跳单播（MMU

multi-user multi-hop unicast）两种卸载模型。利用混合整数非线性规划分离优化目标，有效地分配传输功率，并通过改进传统人工鱼群算法（AFSA

artificial fish swarm algorithm）制定卸载决策。结果表明，相比传统方案，所提优化算法可降低网络时延近19%。在远海场景下，建立远海MSU卸载模型，结合网络连通概率提出合理的信道分配算法。结果表明，所提算法在网络连通时间充足时，可增加允许分配子信道数量，降低网络时延；在网络连通时间有限时，可控制卸载的海洋用户设备数量，保障网络传输时延。

Abstract

Multi-access edge computing can effectively guarantee the low-latency

high-reliability data transmission of ocean monitoring sensor networks and various related maritime applications.In the offshore scenario

two offloading models of multi-user single-hop unicast and multi-user multi-hop unicast were established in combination with the distribution of edge computing resources.The mixed integer nonlinear programming was used to separate optimization targets and effectively allocate transmission power.The unloading decisions were made by improving the traditional artificial fish swarms algorithm.The results show that the proposed optimization algorithm can reduce the network delay by nearly 19% compared with the traditional scheme.In the far-sea scenario

a multi-user single-hop unicast offloading model was established

and a reasonable channel allocation algorithm was proposed based on the network connection probability.The results show that when the network connection time is sufficient

the number of allowable sub-channels can be increased to reduce the network delay.When the network connection time is limited

the number of unloaded marine user equipment can be controlled to ensure the network transmission delay.

关键词

海洋观监测传感器网络多接入边缘计算人工鱼群算法信道分配

Keywords

maritime monitoring sensor networkmulti-access edge computingartificial fish swarm algorithmchannel allocation

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