Jul 2026· 2026 6th International Conference on Intelligent Communications and Computing (ICICC)· pp. 186-192· 0 citations· 15 references
Abstract
With the rapid development of Low Earth Orbit (LEO) satellite networks, computational offloading and Network Function (NF) deployment have emerged as critical enablers for latency-sensitive services. However, existing approaches, such as the GBCO algorithm, typically execute tasks by locating satellites that have cached the required NF across the entire network, resulting in frequent inter-satellite transmissions and consequently increased system latency and energy consumption. To address this issue, this paper proposes a locality-sensitive computational offloading optimization algorithm, termed GCLSO. The proposed method prioritizes task execution on the access satellite to enhance computational locality, and under the condition that cache resources are limited, introduces an NF swapping mechanism to enable adaptive cache adjustment. The algorithm maintains low computational complexity while effectively reducing inter-satellite communication overhead. The simulation results demonstrate that, compared to the GBCO algorithm, the proposed approach achieves a significant improvement in time delay, while maintaining the same time complexity and without any increase in energy consumption.
Simulation results confirm that the proposed JORC framework substantially reduces latency, energy consumption, and overall system cost, while increasing the successful task completion ratio compared to existing baseline approaches.
Tanmay Baidya, Sangman Moh· Italian National Conference...· 0 citations
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Yuyu Liu, Qian Wu, Zeqi Lai et al.· Asia-Pacific Workshop on Net...· 0 citations
Satellite edge computing (SEC) has emerged as a promising paradigm to enhance in-orbit data processing capabilities and reduce transmission latency. However, satellite image processing tasks in SEC environments face critical challenges in efficient data handling, resource coordination, and transmission scheduling. The...
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Mobile edge computing (MEC) has emerged as a promising paradigm to support latency-sensitive applications by deploying computing and storage resources closer to end users. Service caching at the network edge is an effective approach to further reduce response latency and improve quality of service (QoS). However, the i...
Tianyang Zheng, Pengfei Yang, Kang Shen et al.· IEEE Internet of Things Jour...· 0 citations
The built-in caching capability of Named Data Networking (NDN) is one of the most transformative proposals of next-generation network architecture, as it simultaneously realizes network traffic reduction, resilience to node failures, and prompt data retrieval. However, existing caching policies either make too many cac...
Deep Pradipbhai Shah, Sai Sameer Yanamandra, Siva Girish Ramesh et al.· International Conference on...· 0 citations
Integrated Terrestrial–Non-Terrestrial Networks (ITNTN), which combine terrestrial base stations (BSs), High-Altitude Platform Stations (HAPS), and Low-Earth Orbit (LEO) satellites, are key enablers of 6G communication and edge computing (EC) services. However, energy-limited BSs, particularly HAPS and satellites, pose...
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