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AgNeSA: Agility-driven Non-Terrestrial Networks using Small Airborne Swarm

2023 IEEE Future Networks World Forum (FNWF)(2023)

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摘要
In the context of future Non-Terrestrial Networks (NTN) missions, the feasibility of employing compact airborne and space-borne swarms as efficient solutions for enhancing agility and scalability is gaining prominence. These swarms are structured to fragment substantial payloads into smaller units, each capable of providing specific functions and services. Despite their potential advantages, the operation of such swarms is beset with intricate challenges, particularly on the dynamic management of discovery and control mechanisms. This complexity is exacerbated when considering fractionated airborne resources that traverse distinct trajectories, giving rise to opportunistic functional operations. This paper introduces the Agility-driven NTN facilitating small airborne swarm formation (AgNeSA) approach to address the intricacies of communication and power agility within networked airborne resource control. AgNeSA leverages the concept of Software-Defined Virtual Space-borne Embedding (VSE) to facilitate a software-based dynamic control mechanism. The VSE service employs a resource reservation protocol based on priority levels to virtualize space-airborne applications, thereby surmounting the uncertainties and dynamism inherent in wireless inter-airborne communications. This is achieved through migration schedules and delay-tolerant networking (DTN) windows. To evaluate the efficacy of the proposed AgNeSA approach, the authors have developed an event-driven simulator for scheduling and visualization. Simulation results demonstrate that the migration-aware AgNeSA scheduling algorithm yields a more balanced energy consumption profile with reduced overall energy utilization compared to random and reactive scheduling approaches, all while maintaining comparable or lower latency levels.
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关键词
Non-terrestrial Networks,Agility,Random Approach,Scheduling Algorithm,Randomization Schedule,Reactive Approach,Operational Costs,Power Consumption,Linear Problem,Time Slot,Demand For Resources,Physical Resources,Energy Usage,Communication Delay,Optimization Goal,Physical Link,Power Cost,Total Usage,Service Requests,Physical Nodes,Virtual Services,Virtual Nodes,Virtual Link,Virtual Resources,Power Usage,Balance Of Power
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