Enabling Real-Time Computing and Transmission Services in Large-Scale LEO Satellite Networks

IF 7.1 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Vehicular Technology Pub Date : 2025-03-21 DOI:10.1109/TVT.2025.3550806
Binquan Guo;Zhou Zhang;Saman Atapattu;Miao Pan;Ye Yan;Zehui Xiong;Hongyan Li
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Abstract

Enhanced by onboard computing resources and inter-satellite links (ISLs), large-scale satellite networks (SNs) can supplement terrestrial networks, facilitating real-time edge computing and transmission in remote areas at low latency. This capability benefits applications such as real-time remote object tracking, vehicular edge computing, and environmental monitoring. However, different from terrestrial vehicular networks, satellite mobility and the intermittent nature of ISLs often render many computing satellites inaccessible, necessitating efficient scheduling scheme for joint computing and communication resource allocation. To meet this requirement, we investigate joint computing and transmission strategy for real-time computing applications over SNs to reduce end-to-end delays. We formulate the real-time computing and transmission problem over time-varying SNs as an integer linear programming problem. The mathematical optimization method has an exponential time complexity of ${O}(2|\mathcal {L}^{\tau }| \cdot (4 |\mathcal {V}^{\tau }| + 4 |\mathcal {L}^{\tau }|)^{2|\mathcal {L}^{\tau }|})$ in the worst case, which grows rapidly with the growth of network sizes. Here, $|\mathcal {V}^{\tau }|$ and $|\mathcal {L}^{\tau }|$ denote the number of nodes and links, respectively, within the time window ${\tau }$. Resorting to the designed $k$-shortest path-based method yields a worst-case complexity of $O(|\mathcal {V}^{\tau }|! \cdot |\mathcal {V}^{\tau }|^{3})$. While efficient under common scenarios, its running time is still relatively unstable and may become tens of times longer when computing resources become scarce. To enhance efficiency, we further design a graph-based algorithm that leverages the solution space's unique structure, thereby achieving optimal solutions with polynomial time complexity ${O}(3|\mathcal {L}^{\tau }| + (2\log {|\mathcal {V}^{\tau }|}+1) |\mathcal {V}^{\tau }|)$. Extensive evaluations conducted on the world's largest Starlink system validate the efficacy of the designed methods and highlight their potential synergy.
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实现大规模LEO卫星网络的实时计算和传输业务
通过星载计算资源和星间链路的增强,大规模卫星网络可以补充地面网络,促进远程地区低时延的实时边缘计算和传输。这种能力有利于实时远程目标跟踪、车辆边缘计算和环境监测等应用。然而,与地面车载网络不同,卫星的移动性和isl的间歇性往往导致许多计算卫星无法访问,需要有效的调度方案来联合分配计算和通信资源。为了满足这一需求,我们研究了基于SNs的实时计算应用的联合计算和传输策略,以减少端到端延迟。我们将时变网络上的实时计算和传输问题表述为一个整数线性规划问题。数学优化方法的时间复杂度在最坏情况下为指数级${O}(2|\mathcal {L}^{\tau }| \cdot (4 |\mathcal {V}^{\tau }| + 4 |\mathcal {L}^{\tau }|)^{2|\mathcal {L}^{\tau }|})$,随着网络规模的增大而迅速增长。这里,$|\mathcal {V}^{\tau }|$和$|\mathcal {L}^{\tau }|$分别表示时间窗口${\tau }$内的节点和链接的数量。采用设计的$k$ -最短路径方法得到的最坏情况复杂度为$O(|\mathcal {V}^{\tau }|! \cdot |\mathcal {V}^{\tau }|^{3})$。虽然在常见场景下是高效的,但其运行时间仍然相对不稳定,当计算资源变得稀缺时,其运行时间可能会延长数十倍。为了提高效率,我们进一步设计了一种基于图的算法,利用解空间的独特结构,从而获得多项式时间复杂度的最优解${O}(3|\mathcal {L}^{\tau }| + (2\log {|\mathcal {V}^{\tau }|}+1) |\mathcal {V}^{\tau }|)$。对世界上最大的星链系统进行了广泛的评估,验证了所设计方法的有效性,并强调了它们潜在的协同作用。
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来源期刊
CiteScore
6.00
自引率
8.80%
发文量
1245
审稿时长
6.3 months
期刊介绍: The scope of the Transactions is threefold (which was approved by the IEEE Periodicals Committee in 1967) and is published on the journal website as follows: Communications: The use of mobile radio on land, sea, and air, including cellular radio, two-way radio, and one-way radio, with applications to dispatch and control vehicles, mobile radiotelephone, radio paging, and status monitoring and reporting. Related areas include spectrum usage, component radio equipment such as cavities and antennas, compute control for radio systems, digital modulation and transmission techniques, mobile radio circuit design, radio propagation for vehicular communications, effects of ignition noise and radio frequency interference, and consideration of the vehicle as part of the radio operating environment. Transportation Systems: The use of electronic technology for the control of ground transportation systems including, but not limited to, traffic aid systems; traffic control systems; automatic vehicle identification, location, and monitoring systems; automated transport systems, with single and multiple vehicle control; and moving walkways or people-movers. Vehicular Electronics: The use of electronic or electrical components and systems for control, propulsion, or auxiliary functions, including but not limited to, electronic controls for engineer, drive train, convenience, safety, and other vehicle systems; sensors, actuators, and microprocessors for onboard use; electronic fuel control systems; vehicle electrical components and systems collision avoidance systems; electromagnetic compatibility in the vehicle environment; and electric vehicles and controls.
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