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  1. VideoChef: Efficient Approximation for Streaming Video Processing Pipelines

    Ran Xu, Jinkyu Koo, Rakesh Kumar, and Peter Bai, Purdue University; Subrata Mitra, Adobe Research; Sasa Misailovic, University of Illinois Urbana-Champaign; Saurabh Bagchi, Purdue University Many video streaming applications require low-latency processing ...

    admin - December 5, 2021 - 2:30 am

  2. Cavs: An Efficient Runtime System for Dynamic Neural Networks

    this paper, we present ``Cavs'', a runtime system that overcomes these bottlenecks and ...

    admin - December 5, 2021 - 2:30 am

  3. Improving Service Availability of Cloud Systems by Predicting Disk Error

    In this paper, we propose to predict disk errors proactively before they cause more severe damage to ...

    admin - December 5, 2021 - 2:30 am

  4. Pantheon: the training ground for Internet congestion-control research

    Paper! Internet transport algorithms are foundational to the performance of network applications. But ...

    admin - December 5, 2021 - 2:30 am

  5. NanoLog: A Nanosecond Scale Logging System

    Stephen Yang, Seo Jin Park, and John Ousterhout, Stanford University NanoLog is a nanosecond scale logging system that is 1-2 orders of magnitude faster than existing logging systems such as Log4j2, spdlog, Boost log or Event Tracing for Windows. The syst ...

    admin - December 5, 2021 - 2:30 am

  6. DeepCPU: Serving RNN-based Deep Learning Models 10x Faster

    Minjia Zhang, Samyam Rajbhandari, Wenhan Wang, and Yuxiong He, Microsoft AI and Research Recurrent neural networks (RNNs) are an important class of deep learning (DL) models. Existing DL frameworks have unsatisfying performance for online serving: many RN ...

    admin - December 5, 2021 - 3:30 am

  7. KylinX: A Dynamic Library Operating System for Simplified and Efficient Cloud Virtualization

    its monolithic appliance and thus sacrifices flexibility, efficiency, and applicability. This paper ...

    admin - December 5, 2021 - 3:30 am

  8. CGraph: A Correlations-aware Approach for Efficient Concurrent Iterative Graph Processing

    processing of each vertex. Based on this observation, this paper proposes a correlations-aware execution ...

    admin - December 5, 2021 - 3:30 am

  9. Solar: Towards a Shared-Everything Database on Distributed Log-Structured Storage

    performance deteriorates when cross-partition distributed transactions have to be executed. This paper ...

    admin - December 5, 2021 - 3:30 am

  10. Towards IoT-DDoS Prevention Using Edge Computing

    This paper proposes a new approach which leverages edge computing infrastructure to accelerate the ...

    admin - December 5, 2021 - 4:30 am

  11. Mobile Edge Computing Platform Deployment in 4G LTE Networks: A Middlebox Approach

    of low-latency performance in 4G and 5G networks. In this paper, we propose an MEC platform ...

    admin - December 5, 2021 - 4:30 am

  12. Towards a Solution to the Red Wedding Problem

    for edge computing focuses on applications without shared state. In this paper, we present the Red ...

    admin - December 5, 2021 - 4:30 am

  13. An Industrial Robot System Based on Edge Computing: An Early Experience

    Youdong Chen and Qiangguo Feng, School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China; Weisong Shi, Department of Computer Science, Wayne State University, USA As more sensors and actuators are deployed in industrial m ...

    admin - December 5, 2021 - 4:30 am

  14. MODI: Mobile Deep Inference Made Efficient by Edge Computing

    Samuel S. Ogden and Tian Guo, Worcester Polytechnic Institute In this paper, we propose a novel ...

    admin - December 5, 2021 - 4:30 am

  15. ECO: Harmonizing Edge and Cloud with ML/DL Orchestration

    Nisha Talagala, Swaminathan Sundararaman, Vinay Sridhar, Dulcardo Arteaga, Qianmei Luo, Sriram Subramanian, Sindhu Ghanta, Lior Khermosh, and Drew Roselli, ParallelM Nisha Talagala, ParallelM Swaminathan Sundararaman, ParallelM Vinay Sridhar, ParallelM Du ...

    admin - December 5, 2021 - 4:30 am

  16. Paying Less for More? Combo Plans for Edge-Computing Services

    opportunity. In this paper, we examine new pricing plans for edge-computing services that jointly consider ...

    admin - December 5, 2021 - 4:30 am

  17. A Privacy-Preserving Deep Learning Approach for Face Recognition with Edge Computing

    exposes the users' data to curious service providers. In this paper, we utilize the differentially ...

    admin - December 5, 2021 - 5:30 am

  18. Deduplication Analyses of Multimedia System Images

    Tim Süß, Tunahan Kaya, Markus Mäsker, and André Brinkmann, Johannes Gutenberg University Mainz The availability and usage of embedded systems increases permanently and the industry drives the IoT to become more and more relevant in daily life. Factory lin ...

    admin - December 5, 2021 - 5:30 am

  19. Edge Computing Resource Management System: a Critical Building Block! Initiating the debate via OpenStack

    scratch is seen by many as impractical, this paper provides reflections regarding how existing solutions ... fulfils our requirements, and discuss their pros and cons. This paper aims at initiating the discussion in ...

    admin - December 5, 2021 - 5:30 am

  20. SafeShareRide: Edge-based Attack Detection in Ridesharing Services

    during the rides. In this paper, we propose an edge-based attack detection in ridesharing services, ...

    admin - December 5, 2021 - 5:30 am

  21. Store-Edge RippleStream: Versatile Infrastructure for IoT Data Transfer

    streaming data at an application layer. In this paper, we propose to enable streaming of IoT data ...

    admin - December 5, 2021 - 5:30 am

  22. Shadow Puppets: Cloud-level Accurate AI Inference at the Speed and Economy of Edge

    models on edge devices. In this paper, we break this design space duality by proposing the Semantic ...

    admin - December 5, 2021 - 5:30 am

  23. Toward Session Consistency for the Edge

    Seyed Hossein Mortazavi, University of Toronto; Bharath Balasubramanian, AT&T Labs-Research; Eyal de Lara, University of Toronto; Shankaranarayanan Puzhavakath Narayanan, AT&T Labs-Research We describe a distributed datastore tailored for edge com ...

    admin - December 5, 2021 - 5:30 am

  24. An Edge Datastore Architecture For Latency-Critical Distributed Machine Vision Applications

    facilitated by low-latency distributed data stores. In this paper, we take the position that latency ...

    admin - December 5, 2021 - 5:30 am

  25. Mobile Data Repositories at the Edge

    paper, we propose a data-centric communication approach which treats storage and wire the same as far as ...

    admin - December 5, 2021 - 5:30 am

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