Browsing by Subject "Virtual computer systems."
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Item Open Access Network-aware virtual machine placement in cloud data centers with multiple traffic-intensive components(2014) Ilkhechi, Amir RahimzadehFollowing a shift from computing as a purchasable product to computing as a deliverable service to the consumers over the Internet, Cloud Computing emerged as a novel paradigm with an unprecedented success in turning utility computing into a reality. Like any emerging technology, with its advent, Cloud Computing also brought new challenges to be addressed. This work studies network and traffic aware virtual machine (VM) placement in Cloud Computing infrastructures from a provider perspective, where certain infrastructure components have a predisposition to be the sinks or sources of a large number of intensive-traffic flows initiated or targeted by VMs. In the scenarios of interest, the performance of VMs are strictly dependent on the infrastructure’s ability to meet their intensive traffic demands. We first introduce and attempt to maximize the total value of a metric named “satisfaction” that reflects the performance of a VM when placed on a particular physical machine (PM). The problem is NP-hard and there is no polynomial time algorithm that yields an optimal solution. Therefore we introduce several off-line heuristics-based algorithms that yield nearly optimal solutions given the communication pattern and flow demand profiles of VMs. We evaluate and compare the performance of our proposed algorithms via extensive simulation experiments.Item Open Access Stealth sandbox analysis of malware(2009) Uğurlu, Ömer SezginMalware is one of the biggest problems of the world of bits and bytes. Generally malware does activities a user normally does not do, such as becoming part of a virtual army or submitting confidential data of the user to the malware author. There are publicly available analysis services for unknown binaries. Sandbox analysis is performed by execution of an untrusted binary in an isolated environment. It is a very common technique for malware research. Publicly available sandbox analysis platforms help users to see traces of the execution without harming their system. Also it helps owners of the sandbox to collect malware and makes the job of analysts easier. One major problem of the public sandbox testing is that malware authors can also benefit from analysis of sandboxes. If they can identify sandbox systems they can hide malicious behavior. This thesis presents the publicly used Anubis sandbox, detection mechanisms used against Anubis[3], further possible detection mechanisms and our efforts for hiding fingerprint of Anubis from malware and decreasing the resulting false negative rates for the malware detection.