Crux: Locality-Preserving Distributed Services

Distributed systems achieve scalability by distributing load across many machines, but wide-area deployments can introduce worst-case response latencies proportional to the network's diameter. Crux is a general framework to build locality-preserving distributed systems, by transforming an existing scalable distributed algorithm A into a new locality-preserving algorithm ALP, which guarantees for any two clients u and v interacting via ALP that their interactions exhibit worst-case response latencies proportional to the network latency between u and v. Crux builds on compact-routing theory, but generalizes these techniques beyond routing applications. Crux provides weak and strong consistency flavors, and shows latency improvements for localized interactions in both cases, specifically up to several orders of magnitude for weakly-consistent Crux (from roughly 900ms to 1ms). We deployed on PlanetLab locality-preserving versions of a Memcached distributed cache, a Bamboo distributed hash table, and a Redis publish/subscribe. Our results indicate that Crux is effective and applicable to a variety of existing distributed algorithms.Comment: 11 figure

Arts Teacher Evaluation: How One Charter School Network Shows Its Support

The purpose of this study is to understand the evaluation and support system for specials teachers at National Heritage Academy Charter schools. This study uses an exploratory sequential mixed methodology. Research included interviews with leadership members of Brooklyn Dreams Charter School, followed by a survey sent to all of the New York NHA specials teachers. Both parties came to the conclusion that leaders were under-prepared to fully evaluate and support specials teachers due to lack of knowledge in the specialized subject matter as well as insufficient training in using the company’s evaluation tool as it applies to specials teachers. I suggest the organization work to improve the evaluation tool to have the flexibility to work for any staff member that does not fit the mold of a general education teacher and for the organization to also work towards restructuring some key staff positions to better support specials teachers across the charter. Specific guidance documents are suggested for each specialty to support the evaluation tool along with an added position with special skillset in specials teacher. These results and suggestions can be useful for organizations who use teaching artists and any other education setting that works with and evaluate specials teachers.M.S., Arts Administration -- Drexel University, 201

Laboratory Validation of Vision Based Grasping, Guidance and Control with Two Nanosatellite Models

The goal of this work is to demonstrate the autonomous proximity operation capabilities of a 3U scale cubesat in performing the simulated tasks of docking, charging, relative navigation, and deorbiting of space debris, as a step towards designing a fully robotic cubesat. The experiments were performed on an air-bearing testbed, using an engineering model of a 3U scale cubesat equipped with cold-gas propulsion. An appendage with a gripper is integrated into the model to enable grasping. Onboard vision and control algorithms are employed to perform precise navigation and manipulation tasks. Three experiments incorporating the tasks above have been successfully demonstrated. Hardware: The experimental setup consists of two 3U cubesat engineering models, an air-bearing testbed, and a motion capture system. The current cubesat model is derived from a previous version that has been used to demonstrate autonomous point-to-point navigation and obstacle avoidance tasks. The cubesat model consists of the following main subsystems: 3D printed cold-gas propulsion, sensing and computing, and power. In addition, we developed and integrated an appendage with a multipurpose end effector that is effective in grasping objects, docking to, and charging a second cubesat model. The sensor suite consists of pressure sensors, an inertial measurement unit (IMU), short range IR sensors, and a camera. An Odroid XU4 computer with an octa-core processor was chosen to satisfy the computational, power, and form constraints of the model. Software: The perception and control algorithms used for the proximity operations were developed and implemented using an open source robotics software framework called Robot Operating System (ROS) as a middleware for communication. The perception algorithm estimates the 3D pose and rate of change of the cubesat and objects of interest in its vicinity. The object detection requires a textured 3D model of objects and works by matching SURF features of a given image to those generated from the 3D model. The object tracking employs KLT tracking with outlier detection to obtain robust estimates. The textured 3D model is constructed from multi-view images, however, it can also be generated from CAD models. A state machine is employed to automatically switch between the desired control behaviors. Experiment: The system\u27s performance is validated through three experiments showcasing precise relative navigation, docking, and reconfiguration. The first experiment is a simple docking and reconfiguration maneuver, in which a primary cubesat detects and navigates to the closest face of a passive secondary cubesat, upon which it deploys its appendage and docks. The primary then navigates the joined system to a final goal position. In a variation of this experiment, after docking, the primary transmits power to the secondary which is indicated by an LED. The next experiment explores the scenario of debris deorbiting. Similar to the first experiment, the docking procedure is performed, followed by unlatching and release of the secondary with a desired velocity vector. In the last experiment, the primary and secondary execute relative navigation along a set path while maintaining formation. Additional details can be found here: https://asco.lcsr.jhu.edu/nanosatellite-guidance-navigation-and-contro

QuePaxa: Escaping the tyranny of timeouts in consensus

Leader-based consensus algorithms are fast and efficient under normal conditions, but lack robustness to adverse conditions due to their reliance on timeouts for liveness. We present QuePaxa, the first protocol offering state-of-the-art normal-case efficiency without depending on timeouts. QuePaxa uses a novel randomized asynchronous consensus core to tolerate adverse conditions such as denial-of-service (DoS) attacks, while a one-round-trip fast path preserves the normal-case efficiency of Multi-Paxos or Raft. By allowing simultaneous proposers without destructive interference, and using short hedging delays instead of conservative timeouts to limit redundant effort, QuePaxa permits rapid recovery after leader failure without risking costly view changes due to false timeouts. By treating leader choice and hedging delay as a multi-armed-bandit optimization, QuePaxa achieves responsiveness to prevalent conditions, and can choose the best leader even if the current one has not failed. Experiments with a prototype confirm that QuePaxa achieves normal-case LAN and WAN performance of 584k and 250k cmd/sec in throughput, respectively, comparable to Multi-Paxos. Under conditions such as DoS attacks, misconfigurations, or slow leaders that severely impact existing protocols, we find that QuePaxa remains live with median latency under 380ms in WAN experiments