Analysis of Performance and Power Aspects of Hypervisors in Soft Real-Time Embedded Systems

The exponential growth of malware designed to attack soft real-time embedded systems has necessitated solutions to secure these systems. Hypervisors are a solution, but the overhead imposed by them needs to be quantitatively understood. Experiments were conducted to quantify the overhead hypervisors impose on soft real-time embedded systems. A soft real-time computer vision algorithm was executed, with average and worst-case execution times measured as well as the average power consumption. These experiments were conducted with two hypervisors and a control configuration. The experiments showed that each hypervisor imposed differing amounts of overhead, with one achieving near native performance and the other noticeably impacting the performance of the system

NEURAL NETWORK ON VIRTUALIZATION SYSTEM, AS A WAY TO MANAGE FAILURE EVENTS OCCURRENCE ON CLOUD COMPUTING

Cloud computing is one important direction of current advanced technology trends, which is dominating the industry in many aspects. These days Cloud computing has become an intense battlefield of many big technology companies, whoever can win this war can have a very high potential to rule the next generation of technologies. From a technical point of view, Cloud computing is classified into three different categories, each can provide different crucial services to users: Infrastructure (Hardware) as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS). Normally, the standard measurements for cloud computing reliability level is based on two approaches: Service Level Agreements (SLAs) and Quality of Service (QoS). This thesis will focus on IaaS cloud systems’ Error Event Logs as an aspect of QoS in IaaS cloud reliability. To have a better view, basically, IaaS is a derivation of the traditional virtualization system where multiple virtual machines (VMs) with different Operating System (OS) platforms, are run solely on one physical machine (PM) that has enough computational power. The PM will play the role of the host machine in cloud computing, and the VMs will play the role as the guest machines in cloud computing. Due to the lack of fully access to the complete real cloud system, this thesis will investigate the technical reliability level of IaaS cloud through simulated virtualization system. By collecting and analyzing the event logs generated from the virtualization system, we can have a general overview of the system’s technical reliability level based on number of error events occur in the system. Then, these events will be used on neural network time series model to detect the system failure events’ pattern, as well as predict the next error event that is going to occur in the virtualization system