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Ankara : The Department of Computer Engineering and The Graduate School of Engineering and Science of Bilkent University, 2014. Thesis (Master's) -- Bilkent University, 2014. Includes bibliographical references leaves 66-72. Following 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. Ilkhechi, Amir Rahimzadeh M.S. |
