Heterogeneous Federated CubeSat System: Problems, Constraints and Capabilities

Abstract

Different arguments were being presented in the last decade about CubeSats and their applications. Some of them address wireless communication (5G and 6G technologies) trying to achieve better characteristics as coverage and connectivity.Some arrived with terms as IoST (Internet of Space Things), Internet of Satellites (IoSat), DSS (Distributed Space Systems), and FSS (Federated Satellite Systems).All of them aim to use Small/NanoSatellites as constellations/swarms is to provide specific services, share unused resources, and evolve the concept of satellites-as-a-service (SaS).This paper aims to emophasize performance attributes of such cyber-physical systems, model their inherent operational constraints and at the very end, evaluate the quality of service in terms of figures of merit for the entering/leaving of new heterogeneous constituent systems, a.k.a satellites, to the constellation. This "whitepaper"-styled work focuses on presenting the definitions of this heterogeneous constellation problem, aims at its main capabilities and constraints, and proposes modeling approaches for this system representation and evaluation.

QoE-Aware Cost-Minimizing Capacity Renting for Satellite-as-a-Service Enabled Multiple-Beam SatCom Systems

“…In order to solve problem (16), we first characterize its convexity. To begin with, we first define the lower bound capacity amount required per cycle in which 𝜇 𝑏 (𝑡) is fixed by considering the following proposition.…”

“…where 𝛼 𝑏 𝑘,1 = max 𝑡 ∈Ω 𝑘 𝐿𝜆 𝑏 (𝑡)/𝑇 TS , 𝛼 𝑘,2 = max 𝑡 ∈Ω 𝑘 𝐿𝑔 −1 𝑄 max (1 − PBlk , 𝑡)/𝑇 TS , and 𝑔 −1 𝑄 max ( PBlk , 𝑡) is the inverse function of 𝑄 max 𝑛=0 𝑔 𝑛,𝑏 (𝑊 𝑏 𝑘 , 𝑡). Proof: The proof is given in Appendix A In the next move, based on the result of this proposition and the fact that ( 17) is a linear constraint, we state the convexity of problem (16) in the following theorem.…”

“…To ensure effective network resources renting from the IPs and optimal capacity allocation for customer communication services, the SPs have to cope with multiple challenges in maximizing their profit [9], [14]. Herein, the business problems at the SPs include (but are not limited to) capacity estimation accommodating the irregular and unpredictable "time-varying" data traffic from heterogeneous apps/services, and efficient management of rented resources during both peak and off-peak periods to reduce costs [15], [16]. Additionally, maintaining or expanding the customer base is a significant business challenge for both the IPs and SPs, and satisfying the diverse QoE requirements of customers is a key point of resource management that should be addressed carefully.…”

QoE-Aware Cost-Minimizing Bandwidth Renting for Satellite-as-a-Service enabled Multiple-Beam SATCOM Systems

“…Assuming the same service rate (𝜇 𝑘 ) values for all beams and, the remaining parameters set as indicated in Table I, the blocking probability simulation results are compared to the analysis results to verify their agreement. By utilizing the arrival rate function and service rate values of 𝜇 𝑘 = [330, 420, 430, 400, 380, 390] ×10 3 chunks randomly selected for a medium beam utilization of 0.5 to 0.8 as in [25], and calculating the stochastic queue length as outlined in (14), the instantaneous blocking probabilities 𝑝 𝑏 (𝑡)'s of all beams is obtained. The average mean blocking probability of all beams, 𝐵 𝑏=1 𝑇 𝑡=1 𝑝 𝑏 (𝑡)/(𝑇 𝐵), presented in Fig.…”

“…When renting the network resources from the IPs and allocating them to provide communication services to customers, the SPs have to cope with several challenges to maximize their profit [5], [12], [13]. Their business problems include (but are not limited to) capacity dimensioning to meet the irregular and unpredictable time-varying data traffic generated by heterogeneous apps/services, as well as managing the rented resource efficiently in both peak and off-peak periods to minimize expenses [14]. Maintaining or growing the customer base is another difficult task for both the IPs and SPs to maximize their revenue.…”