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For economic benefits and efficient management of resources, organizations are increasingly moving towards the paradigm of "cloud computing" by which they are allowed on-demand delivery of hardware, software and data as services. However, there are many security challenges which are particularly exacerbated by the multitenancy and virtualization features of cloud computing that allow sharing of resources among potentially untrusted tenants in access controlled cloud datacenters. This can result in increased risk of data leakage. To address this risk vulnerability, we propose an efficient risk-aware virtual resource assignment mechanism for clouds multitenant environment. In particular, we introduce the notion of sensitivity in datacenters and the objective is to minimize the risk of data leakage. In addition, the risk should not exceed in high sensitivity datacenters in comparison to low sensitivity datacenters. We present three assignment heuristics and compare their relative performance.

Network function virtualization (NFV) and software-defined networking (SDN) are two technologies that have emerged to reduce capital and operational costs, and to simplify network management. In this paper, we propose an SDN-based system that provisions virtual network functions (VNFs) to minimize round trip time (RTT) delay and synchronization delay requirements. Our system uses graphic-theoretic approaches to place newly requested VNFs including four centrality functions -betweenness, degree, closeness, and Katz. The system performance is evaluated using two random graph topologies representing the physical and logical structures. The impact of increasing the number of deployed VNFs is considered. The results indicate that the degree and Katz selection methods mostly provide the minimum RTT for physical networks, whereas the betweenness selection provides minimum RTT values for logical networks. Moreover, the closeness selection method provides the best synchronization delay for both logical and physical networks.

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