Beacon is a Java-based open source OpenFlow controller created in 2010. It has been widely used for teaching, research, and as the basis of Floodlight. This paper describes the architectural decisions and implementation that achieves three of Beacon's goals: to improve developer productivity, to provide the runtime ability to start and stop existing and new applications, and to be high performance.

We describe the implementation of an OpenFlow Switch on the NetFPGA platform. OpenFlow is a way to deploy experimental or new protocols in networks that carry production traffic. An OpenFlow network consists of simple flow-based switches in the datapath, with a remote controller to manage several switches. In practice, OpenFlow is most often added as a feature to an existing Ethernet switch, IPv4 router or wireless access point. An OpenFlow-enabled device has an internal flow-table and a standardized interface to add and remove flow entries remotely.Our implementation of OpenFlow on the NetFPGA is one of several reference implementations we have implemented on different platforms. Our simple OpenFlow implementation is capable of running at line-rate and handling all the traffic that is going through the Stanford Electrical Engineering and Computer Science building. We compare our implementation's complexity to a basic IPv4 router implementation and a basic Ethernet learning switch implementation. We describe the OpenFlow deployment into the Stanford campus and the Internet2 backbone.

With scalable high-performance storage entirely in DRAM, RAMCloud will enable a new breed of data-intensive applications.

In this paper, we review and compare four algorithms for the identification of contact stiffness and damping during robot constrained motion. The intended application is dynamics modeling and simulation of robotic assembly operations in space. Accurate simulation of these tasks requires contact dynamics models, which in turn use contact stiffness and damping to calculate contact forces. Hence, our primary interest in identifying contact parameters stems from their use as inputs to simulation software with contact dynamics capability. Estimates of environmental stiffness and damping are also valuable for force tracking and stability of impedance controllers. The algorithms considered in this work include: a signal processing method, an indirect adaptive controller with modifications to identify environment damping, a model reference adaptive controller and a recursive least-squares estimation technique. The last three methods have been proposed for real-time implementation in impedance and force-tracking controllers. The signal processing scheme uses a frequency estimate calculated with fast Fourier transform of the force signal and is an off-line method. The algorithms are first evaluated using numerical simulation of a benchmark test. Experiments conducted with a robotic arm contacting a flexible wall provide a further demonstration of their performance. Our results indicate that the indirect adaptive controller has the best combination of performance and ease of use. In addition, the effect of persistently exciting signals is discussed.

Disk-oriented approaches to online storage are becoming increasingly problematic: they do not scale gracefully to meet the needs of large-scale Web applications, and improvements in disk capacity have far outstripped improvements in access latency and bandwidth. This paper argues for a new approach to datacenter storage called RAMCloud, where information is kept entirely in DRAM and large-scale systems are created by aggregating the main memories of thousands of commodity servers. We believe that RAMClouds can provide durable and available storage with 100-1000x the throughput of disk-based systems and 100-1000x lower access latency. The combination of low latency and large scale will enable a new breed of dataintensive applications.