Privacy in VoIP networks: A κ-anonymity approach
Mudhakar Srivatsa, Arun Iyengar, et al.
INFOCOM 2009
Enterprises typically operates multiple datacenter sites, each handling workloads according to an enterprise-level strategy. Sharing resources across multiple sites (or enterprises) brings up several important problems. Each site may have its own policies that govern its interactions with other remote sites. Different policies impact the system performance in different ways. The site administrators and system designers need to understand the effects of a given set of policies on different workloads. In this paper, we describe an analysis methodology that determines the impact of policies on the workloads, and we present results and validation for a prototypical multi-site resource sharing system. Our analytical tool is capable of evaluating complex policies on a large scale system and permits independent policies for each site, so that policy makers can quickly evaluate several alternatives and their effects on the workloads before deploying them. © 2008 IEEE.
Mudhakar Srivatsa, Arun Iyengar, et al.
INFOCOM 2009
Ajay Mohindra, George Copeland, et al.
COOTS 1995
Ting Wang, Mudhakar Srivatsa, et al.
SDM 2012
Venkata Joopudi, Bharath Dandala, et al.
Journal of Biomedical Informatics