Abstract: This is a space era for unmanned aerial vehicles (UAVs) with complex autonomous systems to have an objective research on interplanetary studies. The UAV design for the space application is a complicated approach due to its involvement with initial conditions such as the atmospheric data of that particular planet and in later stages, where the experimental testing setup requires a separate infrastructure to match that atmospheric conditions. So, where the planetary data required for design are density, temperature, viscosity, pressure and gravity. These are initial conditions which affects the design and performance parameters in the conceptual stage of the planetary UAV. This paper describes the UAV conceptual design methodology for the Mars application which includes the configuration selection, sizing, aerodynamic analysis and performance evaluation using low fidelity tools such as XFLR5 and OCTAVE (Low order code). The design performance is compared with Earth atmosphere and Martian

• Publication Date: 31-May-2020
• DOI: 10.15224/978-1-63248-188-7-03
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Abstract: The provision of Desktop as a Service (DaaS) to companies using virtualization technology comes with advantages that improve service quality and reduce the costs incurred from service provision and maintenance. These advantages originate from the efficient use of resources in physical servers through virtual machine management. A virtual machine has various resource allocation and usage options in a single physical server where the machine is operated. Thus, a virtual machine management technique, such as virtual machine allocation and placement based on demand, enables the efficient management of data resources in the machine in accordance with the use patterns of users, even under complex load characteristics. Capitalizing on these innovative affordances, this study developed a virtual machine management technique for the efficient management of physical server resources. Companies can confirm the efficiency of the proposed technique via simulations grounded in resource use data from

• Publication Date: 31-May-2020
• DOI: 10.15224/978-1-63248-188-7-04
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