已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

LEO satellites selection-based computation offloading algorithm in aircraft-satellite multi-access edge computing networks

计算机科学 计算 计算卸载 GSM演进的增强数据速率 选择(遗传算法) 卫星 选择算法 边缘计算 分布式计算 算法 计算机网络 电信 人工智能 航空航天工程 工程类
作者
Jiadong Zhang,Rui‐Dong Zhang,Wenku Shi
出处
期刊:Computer Communications [Elsevier BV]
标识
DOI:10.1016/j.comcom.2024.05.011
摘要

The emergence of sixth-generation (6G) mobile networks and non-terrestrial networks (NTNs) has led to increased interest in low Earth orbit (LEO) satellite-based communication networks for their potential to provide global coverage and ubiquitous connectivity. In this paper, we investigate the LEO satellites selection-based computation offloading problem in the aircraft-satellite multi-access edge computing (ASMEC) network, where LEO satellites and edge computing processors are integrated to provide ubiquitous and low-latency communication and computation services for aircraft during flights. In contrast to most existing works, which directly assume a fixed number of satellites or orbits in satellite-based MEC networks, we investigate the problem of how many satellites and which satellites to select in the ASMEC network. Our objective is to minimize the average total time delay of tasks during aircraft-satellite computation offloading. To achieve this, we formulate a nonlinear integer programming (NLIP) problem and propose the LEO satellites selection-based computation offloading (LSSBCO) algorithm to solve it, which includes the shortest aircraft-satellite distance based access satellite selection (ASS-SD) algorithm and the nearest k(t) neighboring satellites selection (NSS-k(t)) algorithm. We evaluate the performance of the LSSBCO algorithm in terms of the average total time delay, the maximum throughput, the average aircraft-satellite distance, the average connection duration, and the number of satellite handovers. Numerical results show that the proposed algorithm outperforms the benchmark algorithms with a lower average total time delay.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Ava应助cpl采纳,获得10
1秒前
幽默沛山完成签到 ,获得积分10
1秒前
1秒前
青屿发布了新的文献求助10
3秒前
4秒前
xiao_niu发布了新的文献求助10
4秒前
wzc发布了新的文献求助10
4秒前
5秒前
7秒前
10秒前
木木发布了新的文献求助10
10秒前
今后应助科研通管家采纳,获得10
10秒前
隐形曼青应助科研通管家采纳,获得10
11秒前
ccczzz应助科研通管家采纳,获得10
11秒前
11秒前
11秒前
Copyright应助科研通管家采纳,获得10
12秒前
12秒前
田様应助科研通管家采纳,获得10
12秒前
小蘑菇应助科研通管家采纳,获得10
12秒前
12秒前
13秒前
13秒前
麟语桐发布了新的文献求助10
13秒前
16秒前
16秒前
Coral完成签到,获得积分10
16秒前
张教授发布了新的文献求助10
18秒前
眼睛大若菱完成签到,获得积分10
19秒前
aroseisarose发布了新的文献求助10
19秒前
Wish发布了新的文献求助10
19秒前
23秒前
Laura_cxs完成签到 ,获得积分10
26秒前
深情安青应助青屿采纳,获得10
26秒前
wx完成签到 ,获得积分10
27秒前
文艺寄松完成签到 ,获得积分10
27秒前
28秒前
28秒前
FashionBoy应助瘦瘦以亦采纳,获得10
29秒前
刘Boyce完成签到,获得积分10
29秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Prompt Engineering for Clinicians: Harnessing AI in Everyday Medical Practice 600
REAL-WORLD EFFICACY AND GENOMIC LANDSCAPE OF POLATUZUMA VEDOTIN-BASED FIRST-LINE THERAPY IN DIFFUSE LARGE B-CELL LYMPHOMA: A FOCUS ON TP53 MUTATIONS AND TREATMENT RESPONSE 500
Handbook of Luminescence Dating 500
Safety Pharmacology 500
《KNN基无铅压电陶瓷电学性能优化与物理机理研究》 500
Elgar Concise Encyclopedia of Space Law 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 计算机科学 化学工程 生物化学 物理 内科学 复合材料 催化作用 光电子学 物理化学 电极 细胞生物学 基因 遗传学
热门帖子
关注 科研通微信公众号,转发送积分 6944221
求助须知:如何正确求助?哪些是违规求助? 8629728
关于积分的说明 18305354
捐赠科研通 6379282
什么是DOI,文献DOI怎么找? 3079195
关于科研通互助平台的介绍 2120003
邀请新用户注册赠送积分活动 2056076