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One of the biggest advantages of cloud infrastructures is the elasticity. Cloud services are monitored and based on the resource utilization and performance load, they get scaled up or down, by provision or deprovision of cloud resources. The goal is to guarantee the customers an acceptable performance with a minimum of resources. Such Quality of Service (QoS) characteristics are stated in a contract, called Service Level Agreement (SLA) negotiated between customer and provider. The approach of this paper shows that with additional imprecise information (e.g. expected daytime/weektime performance) modeled with fuzzy logic and used in a behavior, load and performance prediction model, the up and down scaling mechanism of a cloud service can be optimized. Evaluation results confirm, that using this approach, SLA violation can be minimized.

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Mega-constellations are being deployed to offer innovative services to Earth's users. Our work shows how they can provide seamless connectivity to LEO spacecrafts too, and transform them into highly responsive nodes of a space-to-space network characterized by high throughput, low latency, and low cost. For realizing the new mega-constellation services in space paradigm, we present a complete design of the LEO space terminal. By focusing on existing mega-constellations, we derive the service performance under realistic scenarios, and compare it with existing services like Ground Station Networks and Data Relay Systems. All the results show that the new approach can be potentially disruptive for the space ecosystem, by transforming each satellite into a 24/7 available node of a high performance space network, thus enabling a myriad of innovative applications.

Numerical integration of orbit trajectories for a large number of initial conditions and for long time spans is computationally expensive. Semi-analytical methods were developed to reduce the computational burden. An elegant and widely used method of semi-analytically integrating trajectories of objects subject to atmospheric drag was proposed by King-Hele (KH). However, the analytical KH contraction method relies on the assumption that the atmosphere density decays strictly exponentially with altitude. If the actual density profile does not satisfy the assumption of a fixed scale height, as is the case for Earth's atmosphere, the KH method introduces potentially large errors for non-circular orbit configurations.In this work, the KH method is extended to account for such errors by using a newly introduced atmosphere model derivative. By superimposing exponentially decaying partial atmospheres, the superimposed KH method can be applied accurately while considering more complex density profiles. The KH method is further refined by deriving higher order terms during the series expansion. A variable boundary condition to choose the appropriate eccentricity regime, based on the series truncation errors, is introduced. The accuracy of the extended analytical contraction method is shown to be comparable to numerical Gauss-Legendre quadrature. Propagation using the proposed method compares well against non-averaged integration of the dynamics, while the computational load remains very low.