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Performance and Security Provisioning for Mobile Telecom CloudVaezpour, Seyed Yahya 27 August 2015 (has links)
Mobile Telecom Cloud (MTC) refers to cloud services provided by mobile telecommunication companies. Since mobile network operators support the last-mile Internet access to users, they have advantages over other cloud providers by providing users with better mobile connectivity and required quality of service (QoS). The dilemma in meeting higher QoS demands while saving cost poses a big challenge to MTC providers. We tackle this challenge by strategically placing users' data in distributed switching centres to minimize the total system cost and maximize users' satisfaction. We formulate and solve the optimization problems using linear programming (LP) based branch-and-bound and LP with rounding.
Furthermore, we discuss MTC brokerage which allows MTC providers to act as a brokerage to broker third-party cloud providers' (TPC) cloud resources and integrate the resources reserved from TPC with those of their own MTC. We address the technical challenges of optimally allocating users' cloud requests to MTC and TPC data centres to meet users' QoS requirement with minimum cost. We also study the price range that can be profitable to a MTC brokerage. We then investigate the resource reservation problem with dynamic request changes. We evaluate our solution using real Google traces collected over a 29-day period from a Google cluster.
We also address security provisioning in MTC. Mobile cloud allows users to offload computational intensive applications to a mobile phone's agent in the cloud, which could be implemented as a thin virtual machine (VM), also termed as phone clone. Due to shared hardware components among co-resident VMs, a VM is subject to covert channel attacks and may potentially leak information to other VMs located in the same physical host. We design SWAP: a security aware provisioning and migration scheme for phone clones. We evaluate our solution using the Reality Mining and the Nodobo dataset. Experimental results indicate that our algorithms are nearly optimal for phone clone allocation and are effective in maintaining low risk and minimizing the number of phone clone migrations. / Graduate / 0984
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