2 research outputs found
Design and Management of DOT: A Distributed OpenFlow Testbed
Abstract-With the growing adoption of Software Defined Networking (SDN), there is a compelling need for SDN emulators that facilitate experimenting with new SDN-based technologies. Unfortunately, Mininet [1], the de facto standard emulator for software defined networks, fails to scale with network size and traffic volume. The aim of this paper is to fill the void in this space by presenting a low cost and scalable network emulator called Distributed OpenFlow Testbed (DOT). It can emulate large SDN deployments by distributing the workload over a cluster of compute nodes. Through extensive experiments, we show that DOT can overcome the limitations of Mininet and emulate larger networks. We also demonstrate the effectiveness of DOT on four Rocketfuel topologies. DOT is available for public use and community-driven development at dothub.org
CQNCR: Optimal VM migration planning in cloud data centers
Abstract—With the proliferation of cloud computing, virtu-alization has become the cornerstone of modern data centers and an effective solution to reduce operational costs, maximize utilization and improve performance and reliability. One of the powerful features provided by virtualization is Virtual Machine (VM) migration, which facilitates moving workloads within the infrastructure to reach various performance objectives. As recent virtual resource management schemes are more reliant on this feature, a large number of VM migrations may be triggered simultaneously to optimize resource allocations. In this context, a challenging problem is to find an efficient migration plan, i.e., an optimal sequence in which migrations should be triggered in order to minimize the total migration time and impact on services. In this paper, we propose CQNCR (read as sequencer), an effective technique for determining the execution order of massive VM migrations within data centers. Specifically, given an initial and a target resource configuration, CQNCR sequences VM migrations so as to efficiently reach the final configuration with minimal time and impact on performance. Experiments show that CQNCR can significantly reduce total migration time by up to 35 % and service downtime by up to 60%. I