Resource provisioning in compute clouds often requires an estimate of the capacity needs of Virtual Machines (VMs). The estimated VM size is the basis for allocating resources commensurate with demand. In contrast to the traditional practice of estimating the size of VMs individually, we propose a joint-VM provisioning approach in which multiple VMs are consolidated and provisioned together, based on an estimate of their aggregate capacity needs. This new approach exploits statistical multiplexing among the workload patterns of multiple VMs, i.e., the peaks and valleys in one workload pattern do not necessarily coincide with the others. Thus, the unused resources of a low utilized VM can be borrowed by the other co-located VMs with high utilization. Compared to individual-VM based provisioning, joint-VM provisioning could lead to much higher resource utilization. This paper presents three design modules to enable such a concept in practice. Specifically, a performance constraint describing the capacity need of a VM for achieving a certain level of application performance; an algorithm for estimating the aggregate size of multiplexed VMs; a VM selection algorithm that seeks to find those VM combinations with complementary workload patterns. We showcase that the proposed three modules can be seamlessly plugged into applications such as resource provisioning, and providing resource guarantees for VMs. The proposed method and applications are evaluated by performance data collected from about 16 thousand VMs in commercial data centers. The results demonstrate more than 45% improvements in terms of the overall resource utilization.

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The Internet today provides no support for privacy or authentication of multicast packet. However, an increasing number of applications will require secure multicast senices in order to restrict group membership and enforce accountability of group members. A major problem associated with the deployment of secure multicast delivery services is the scalability of the key distribution protocoL This is particularly true with regard to the handling of group membership changes, such as member departures and/or expulsions, which necessitate the distribution of a new session key to all the remaining group members.As the frequency of group membership changes increases, it becomes necessary to reduce the cost of key distribution operations. This paper explores the use of batching of group membership changes to reduce the frequency, and hence the cost, of key redistribution operations. It focuses explicitly on the problem of cumulnrive member removal and present an algorithm that minimizes the number of messages required to distribute new keys to the remaining group members. The algorithmis used in conjunction with a new multicast key management scheme which uses a set of auxiliary keys in order to improve scalability. In contrast to previous schemes which generate a fixed hierarchy of keys, the proposed scheme dynamically generates the most suitable key hierarchy by composing different keys. Our cumulative member removal algorithm uses Boolean function minimization techniques, and outperforms all other schemes known to us in terms of message complexity.

The Internet transport infrastructure is moving toward a model of high-speed routers interconnected by intelligent optical core networks. A consensus is emerging in the industry on utilizing an IP-centric control plane within optical networks to support dynamic provisioning and restoration of lightpaths. At the same time, there are divergent views on how IP routers must interact with optical core networks to achieve end-to-end connectivity. This article describes the architectural alternatives for interconnecting IP routers over optical networks, considering the routing and signaling issues. Also, the application of IP-based protocols for dynamic provisioning and restoration of lightpaths, as well as the interworking of multivendor optical networks is described.

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