Systems & networking
Researching and inventing new technologies for next-generation infrastructures and platforms for sensors, devices and the cloud.
Highlights
Researchers seek to simplify the complex in cloud computing
Read more about Researchers seek to simplify the complex in cloud computing
High performance container networking
Read more about High performance container networking
Microsoft Research webinar series presents Project Rocket: Hybrid Edge + Cloud Video Analytics Platform
Read more about Microsoft Research webinar series presents Project Rocket: Hybrid Edge + Cloud Video Analytics Platform
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4,392 results found
Publication
Collage Inference: Using Coded Redundancy for Lowering Latency Variation in Distributed Image Classification Systems
MLaaS (ML-as-a-Service) offerings by cloud computing platforms are becoming increasingly popular. Hosting pre-trained machine learning models in the cloud enables elastic scalability as the demand grows. But providing low latency and reducing the latency variance is a key requirement. Variance is harder to control in a cloud deployment due to uncertainties in resource allocations across many virtual instances. We propose the collage inference technique which uses a novel convolutional neural network model, collage-cnn, to provide…
Publication
A Federated Approach in Training Acoustic Models
In this paper, a novel platform for Acoustic Model training based on Federated Learning (FL) is described. This is the first attempt to introduce Federated Learning techniques in Speech Recognition (SR) tasks. Besides the novelty of the task, the paper describes an easily generalizable FL platform and presents the design decisions used for this task. Amongst the novel algorithms introduced is a hierarchical optimization scheme employing pairs of optimizers and an algorithm for gradient selection,…
Publication
Robust P2P Primitives Using SGX Enclave
Peer-to-peer (P2P) systems such as BitTorrent and Bitcoin are susceptible to serious attacks from byzantine nodes that join as peers. Due to well-known impossibility results for designing P2P primitives in unrestricted byzantine settings, research has explored many adversarial models with additional assumptions, ranging from mild (such as preestablished PKI) to strong (such as the existence of common random coins). One such widely-studied model is the generalomission model, which yields simple protocols with good efficiency, but…
Publication
Robust P2P Primitives Using SGX Enclaves
Peer-to-peer (P2P) systems such as BitTorrent and Bitcoin are susceptible to serious attacks from byzantine nodes that join as peers. Due to well-known impossibility results for designing P2P primitives in unrestricted byzantine settings, research has explored many adversarial models with additional assumptions, ranging from mild (such as pre-established PKI) to strong (such as the existence of common random coins). One such widely-studied model is the general omission model, which yields simple protocols with good efficiency,…
Publication
Pushing Data-Induced Predicates Through Joins in Big-Data Clusters
Using data statistics, we convert predicates on a table into data-induced predicates (diPs) that apply on the joining tables. Doing so substantially speeds up multi-relation queries because the benefits of predicate pushdown can now apply beyond just the tables that have predicates. We use diPs to skip data exclusively during query optimization; i.e., diPs lead to better plans and have no overhead during query execution. We study how to apply diPs for complex query expressions…
Publication
Sirius: A Flat Datacenter Network with Nanosecond Optical Switching
The increasing gap between the growth of datacenter traffic and electrical switch capacity is expected to worsen due to the slowdown of Moore’s law, motivating the need for a new switching technology for the post-Moore’s law era that can meet the increasingly stringent requirements of hardware-driven cloud workloads. We propose Sirius, an optically-switched network for datacenters providing the abstraction of a single, high-radix switch that can connect thousands of nodes—racks or servers—in a datacenter while…
Publication
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Video-analytics-as-a-service is becoming an important offering for cloud providers. A key concern in such services is privacy of the videos being analyzed. While trusted execution environments (TEEs) are promising options for preventing the direct leakage of private video content, they remain vulnerable to side-channel attacks. We present Visor, a system that provides confidentiality for the user’s video stream as well as the ML models in the presence of a compromised cloud platform and untrusted co-tenants.…
Event
Microsoft at SIGCOMM 2020
Microsoft is proud to be a sponsor of the ACM Special Interest Group on Data Communication (SIGCOMM). Join us in one of our many sessions to hear more about our recent research and stop by our virtual booth to chat with our experts and find out about career opportunities with Microsoft.
Event
The 2nd Workshop on Hot Topics in Video Analytics and Intelligent Edges
Cameras are everywhere! Analyzing live videos from these cameras has great potential to impact science and society. Enterprise cameras are deployed for a wide variety of commercial and security reasons. Consumer devices themselves have cameras with users interested in analyzing live videos from these devices. We are all living in the golden era for computer vision and AI that is being fueled by game-changing systemic infrastructure advancements, breakthroughs in machine learning, and copious training data, largely improving…