Availability Modeling of Computing Systems with Virtual Architectures

Cloud computing services are built on the premise of high availability. These services are sold to customers who are expecting a reduced cost particularly in the area of failures and maintenance. At the Infrastructure as a Service (IaaS) layer resources is sold to customers as virtual machines (VMs) with CPU and memory specifications. Both these resources are not necessarily guaranteed. This is because virtual machines can share the same hardware resources. If resources aren't allocated properly, one virtual machine for example, may use up too much CPU power reducing the processing power available to other virtual machines. This can result in response time failures. In this research a framework is developed that integrates hardware, software and response time failures. Response time failures occur when a request is made to a server and does not complete on time. The framework allows the cloud purchaser to test the system under stressed conditions, allocating more or less virtual machines to determine the availability of the system. The framework also allows the cloud provider to separately evaluate the availability of the hardware and other software systems.

Availability Modeling of Computing Systems with Virtual Architectures

Cloud computing services are built on the premise of high availability. These services are sold to customers who are expecting a reduced cost particularly in the area of failures and maintenance. At the Infrastructure as a Service (IaaS) layer resources is sold to customers as virtual machines (VMs) with CPU and memory specifications. Both these resources are not necessarily guaranteed. This is because virtual machines can share the same hardware resources. If resources aren't allocated properly, one virtual machine for example, may use up too much CPU power reducing the processing power available to other virtual machines. This can result in response time failures. In this research a framework is developed that integrates hardware, software and response time failures. Response time failures occur when a request is made to a server and does not complete on time. The framework allows the cloud purchaser to test the system under stressed conditions, allocating more or less virtual machines to determine the availability of the system. The framework also allows the cloud provider to separately evaluate the availability of the hardware and other software systems.

Ground Testing Strategies for Verifying the Slew Rate Tolerance of Star Trackers

The performance of a star tracker is largely based on the availability of its attitude solution. Several methods exist to assess star tracker availability under both static and dynamic imaging conditions. However, these methods typically make various idealizations that can limit the accuracy of these results. This study aims to increase the fidelity of star tracker availability modeling by accounting for the effects of detection logic and pixel saturation on star detection. We achieve this by developing an analytical model for the focal plane intensity distribution of a star in the presence of sensor slew. Using the developed model, we examine the effects of slew rate on star detection using simulations and lab tests. The developed approach allows us to determine the maximum slew rate for which a star of a given stellar magnitude can still be detected. This information can then be used to describe the availability of a star tracker attitude solution as a function of slew rate, both spatially, across the entire celestial sphere, or locally, along a specified orientation track.

Ground Testing Strategies for Verifying the Slew Rate Tolerance of Star Trackers

The performance of a star tracker is largely based on the availability of its attitude solution. Several methods exist to assess star tracker availability under both static and dynamic imaging conditions. However, these methods typically make various idealizations that can limit the accuracy of these results. This study aims to increase the fidelity of star tracker availability modeling by accounting for the effects of detection logic and pixel saturation on star detection. We achieve this by developing an analytical model for the focal plane intensity distribution of a star in the presence of sensor slew. Using the developed model, we examine the effects of slew rate on star detection using simulations and lab tests. The developed approach allows us to determine the maximum slew rate for which a star of a given stellar magnitude can still be detected. This information can then be used to describe the availability of a star tracker attitude solution as a function of slew rate, both spatially, across the entire celestial sphere, or locally, along a specified orientation track.

Availability Modeling and Performance Improving of a Healthcare Internet of Things (IoT) System

Internet of Things (IoT) is improving human life in a more convenient and simpler way. One of the most promising IoT applications is healthcare. In this paper, an availability model of a healthcare IoT system is proposed which is composed of two groups of structures described by separate Markov state-space models. The two separate models are analyzed and combined to implement the whole IoT system modeling. The system balance equations are solved under a given scenario and some performance metrics of interest, such as probabilities of full service, degraded service, and the system unavailability, are derived. Detailed numerical evaluation of selected metrics is provided for further understanding and verification of the analytic results. An availability performance improving (API) method is also proposed for increasing the probability of system full service and decreasing the system unavailability. The proposed system modeling and performance improving method can serve as a useful reference for general IoT system design and evaluation.