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We present the design, implementation, and evaluation of B4, a private WAN connecting Google's data centers across the planet. B4 has a number of unique characteristics: i) massive bandwidth requirements deployed to a modest number of sites, ii) elastic traffic demand that seeks to maximize average bandwidth, and iii) full control over the edge servers and(More)
Fig. 1: The PR2 with a pair of pants in a crumpled initial configuration. Abstract— We consider the problem of autonomously bringing an article of clothing into a desired configuration using a general-purpose two-armed robot. We propose a hidden Markov model (HMM) for estimating the identity of the article and tracking the article's configuration throughout(More)
We introduce a load-balanced adaptive routing algorithm for torus networks, GOAL - Globally Oblivious Adaptive Locally - that provides high throughput on adversarial traffic patterns, matching or exceeding fully randomized routing and exceeding the worst-case performance of Chaos [2], RLB [14], and minimal routing [8] by more than 40%. GOAL also preserves(More)
— We introduce a new method of adaptive routing on k-ary n-cubes, Globally Adaptive Load-Balance (GAL). GAL makes global routing decisions using global information. In contrast, most previous adaptive routing algorithms make local routing decisions using local information (typically channel queue depth). GAL senses global congestion using segmented(More)
Data Center topologies employ multiple paths among servers to deliver scalable, cost-effective network capacity. The simplest and the most widely deployed approach for load balancing among these paths, Equal Cost Multipath (ECMP), hashes flows among the shortest paths toward a destination. ECMP leverages uniform hashing of balanced flow sizes to achieve(More)
— The state of the art in computer vision has rapidly advanced over the past decade largely aided by shared image datasets. However, most of these datasets tend to consist of assorted collections of images from the web that do not include 3D information or pose information. Furthermore, they target the problem of object category recognition—whereas solving(More)
We present our approach for overcoming the cost, operational complexity, and limited scale endemic to datacenter networks a decade ago. Three themes unify the five generations of datacenter networks detailed in this paper. First, multi-stage Clos topologies built from commodity switch silicon can support cost-effective deployment of building-scale networks.(More)
We introduce <i>Randomized Local Balance</i> (RLB), a routing algorithm that strikes a balance between locality and load balance in torus networks, and analyze RLB's performance for benign and adversarial traffic permutations. Our results show that RLB outperforms deterministic algorithms (25% more bandwidth than Dimension Order Routing) and minimal(More)
This paper introduces a new adaptive method, Channel Queue Routing (CQR), for load-balanced routing on k-ary n-cube interconnection networks. CQR estimates global congestion in the network from its channel queues while relying on the implicit network backpressure to transfer congestion information to these queues. It uses this estimate to decide the(More)
— Many robotic control tasks involve complex dynamics that are hard to model. Hand-specifying trajectories that satisfy a system's dynamics can be very time-consuming and often exceedingly difficult. We present an algorithm for automatically generating large classes of trajectories for difficult control tasks by learning parameterized versions of desired(More)