Mining diverse opinions
Mudhakar Srivatsa, Sihyung Lee, et al.
MILCOM 2012
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, Sihyung Lee, et al.
MILCOM 2012
Vijay A. Balasubramaniyan, Arup Acharya, et al.
ICDCS 2008
Murthy Devarakonda
IEEE Concurrency
Murthy Devarakonda, Ajay Mohindra, et al.
USENIX ATC 1995