Dynamic accelerator provisioning for SSH tunnels in NFV environments

In this demonstration, we present dynamic allocation of accelerator resources to SSH tunnels in an NFV environment. In order to accelerate a VNF, its compute-intensive operations are offloaded to hardware cores running on an FPGA. The CPU utilization information of VNFs is continuously processed by a service management component to dynamically decide the suitable target to run VNF's crypto-operations. We also demonstrate switching between the non-accelerated and hardware-accelerated SSH-tunnels triggered by a change in the nature of the data traffic flowing through the tunnel and indicate throughput gains obtainable in dynamically switching contexts

Exploring Convolutional Networks for End-to-End Visual Servoing

Present image based visual servoing approaches rely on extracting hand crafted visual features from an image. Choosing the right set of features is important as it directly affects the performance of any approach. Motivated by recent breakthroughs in performance of data driven methods on recognition and localization tasks, we aim to learn visual feature representations suitable for servoing tasks in unstructured and unknown environments. In this paper, we present an end-to-end learning based approach for visual servoing in diverse scenes where the knowledge of camera parameters and scene geometry is not available a priori. This is achieved by training a convolutional neural network over color images with synchronised camera poses. Through experiments performed in simulation and on a quadrotor, we demonstrate the efficacy and robustness of our approach for a wide range of camera poses in both indoor as well as outdoor environments.Comment: IEEE ICRA 201

Leveling the playing field for Visually Impaired using Transport Assistant

Visually impaired people face numerous challenges when it comes to transportation. Not only must they circumvent obstacles while navigating, but they also need access to essential information related to available public transport, up-to-date weather forecast, and convenient method for booking private taxis. In this paper we introduce Transport Assistant - a voice based assistive technology prototype, built with a goal of leveling the playing field for the visually impaired to solve these problems that they face in their day to day life. Being voice enabled makes it seamlessly integrate into the environment, and can be invoked by saying a hotword - hello assistant. The paper explores this research question, followed by investigating existing technologies, explains the methodology and design, then concludes by presenting the prototype and results.Comment: 8 pages, 7 figures, ubiquitous computin

Hardware-accelerator aware VNF-chain recovery

Hardware-accelerators in Network Function Virtualization (NFV) environments have aided telecommunications companies (telcos) to reduce their expenditures by offloading compute-intensive VNFs to hardware-accelerators. To fully utilize the benefits of hardware-accelerators, VNF-chain recovery models need to be adapted. In this paper, we present an ILP model for optimizing prioritized recovery of VNF-chains in heterogeneous NFV environments following node failures. We also propose an accelerator-aware heuristic for solving prioritized VNF-chain recovery problems of large-size in a reasonable time. Evaluation results show that the performance of heuristic matches with that of ILP in regard to restoration of high and medium priority VNF-chains and a small penalty occurs only for low-priority VNF-chains