Publications (27)
RASC: Enhancing Observability & Programmability in Smart Spaces
Anna Karanika, Kai-Siang Wang, Han-Ting Liang +2
While RPCs form the bedrock of systems stacks, we posit that IoT device collections in smart spaces like homes, warehouses, and office buildings--which are all "user-facing"--requi…
Banyan: A Scoped Dataflow Engine for Graph Query Service
Li Su, Xiaoming Qin, Zichao Zhang +6
Graph query services (GQS) are widely used today to interactively answer graph traversal queries on large-scale graph data. Existing graph query engines focus largely on optimizing…
Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo
Le Xu, Shivaram Venkataraman, Indranil Gupta +2
Resource provisioning in multi-tenant stream processing systems faces the dual challenges of keeping resource utilization high (without over-provisioning), and ensuring performance…
Baechi: Fast Device Placement of Machine Learning Graphs
Beomyeol Jeon, Linda Cai, Chirag Shetty +6
Machine Learning graphs (or models) can be challenging or impossible to train when either devices have limited memory, or models are large. To split the model across devices, learn…
Henge: Intent-driven Multi-Tenant Stream Processing
Faria Kalim, Le Xu, Sharanya Bathey +2
We present Henge, a system to support intent-based multi-tenancy in modern stream processing applications. Henge supports multi-tenancy as a first-class citizen: everyone inside an…
Zeno++: Robust Fully Asynchronous SGD
Cong Xie, Sanmi Koyejo, Indranil Gupta
We propose Zeno++, a new robust asynchronous Stochastic Gradient Descent~(SGD) procedure which tolerates Byzantine failures of the workers. In contrast to previous work, Zeno++ rem…
Counting How the Seconds Count: Understanding Algorithm-User Interplay in TikTok via ML-driven Analysis of Video Content
Maleeha Masood, Shreya Kannan, Zikun Liu +2
Short video streaming systems such as TikTok, YouTube Shorts, Instagram Reels, etc., have reached billions of active users worldwide. At the core of such systems are (proprietary)…
CoMesh: Fully-Decentralized Control for Sense-Trigger-Actuate Routines in Edge Meshes
Anna Karanika, Rui Yang, Xiaojuan Ma +3
While mesh networking for edge settings (e.g., smart buildings, farms, battlefields, etc.) has received much attention, the layer of control over such meshes remains largely centra…
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta
We present Zeno, a technique to make distributed machine learning, particularly Stochastic Gradient Descent (SGD), tolerant to an arbitrary number of faulty workers. Zeno generaliz…
Dirigo: Self-scaling Stateful Actors For Serverless Real-time Data Processing
Le Xu, Divyanshu Saxena, Neeraja J. Yadwadkar +2
We propose Dirigo, a distributed stream processing service built atop virtual actors. Dirigo achieves both a high level of resource efficiency and performance isolation driven by u…
Transactional Panorama: A Conceptual Framework for User Perception in Analytical Visual Interfaces
Dixin Tang, Alan Fekete, Indranil Gupta +1
Many tools empower analysts and data scientists to consume analysis results in a visual interface, such as a dashboard. When the underlying data changes, these results need to be u…
Generalized Byzantine-tolerant SGD
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta
We propose three new robust aggregation rules for distributed synchronous Stochastic Gradient Descent~(SGD) under a general Byzantine failure model. The attackers can arbitrarily m…
Home, SafeHome: Smart Home Reliability with Visibility and Atomicity
Shegufta Bakht Ahsan, Rui Yang, Shadi A. Noghabi +1
Smart environments (homes, factories, hospitals, buildings) contain an increasing number of IoT devices, making them complex to manage. Today, in smart homes where users or trigger…
Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta +1
When scaling distributed training, the communication overhead is often the bottleneck. In this paper, we propose a novel SGD variant with reduced communication and adaptive learnin…
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Sanmi Koyejo, Indranil Gupta
Recently, new defense techniques have been developed to tolerate Byzantine failures for distributed machine learning. The Byzantine model captures workers that behave arbitrarily,…
Generative Caching for Structurally Similar Prompts and Responses
Sarthak Chakraborty, Suman Nath, Xuchao Zhang +2
Large Language Models (LLMs) are increasingly being used to plan, reason, and execute tasks across diverse scenarios. In use cases like repeatable workflows and agentic settings, p…
Characterizing and Adapting the Consistency-Latency Tradeoff in Distributed Key-value Stores
Muntasir Raihan Rahman, Lewis Tseng, Son Nguyen +2
The CAP theorem is a fundamental result that applies to distributed storage systems. In this paper, we first present and prove two CAP-like impossibility theorems. To state these t…
CPU-Limits kill Performance: Time to rethink Resource Control
Chirag Shetty, Sarthak Chakraborty, Hubertus Franke +4
Research in compute resource management for cloud-native applications is dominated by the problem of setting optimal CPU limits -- a fundamental OS mechanism that strictly restrict…
Leveraging Social-Network Infrastructure to Improve Peer-to-Peer Overlay Performance: Results from Orkut
Zahid Anwar, William Yurcik, Vivek Pandey +3
Application-level peer-to-peer (P2P) network overlays are an emerging paradigm that facilitates decentralization and flexibility in the scalable deployment of applications such as…
Knox: Fortifying Smart Spaces With Safety Guarantees
Rishabh Menezes, Jadon T. Schuler, Kaimeng Zhu +2
Internet of Things (IoT) devices in smart spaces and buildings are an emerging class of distributed systems with critical safety requirements. This paper presents Knox, the first s…
Inferring Formal Properties of Production Key-Value Stores
Edgar Pek, Pranav Garg, Muntasir Raihan Rahman +3
Production distributed systems are challenging to formally verify, in particular when they are based on distributed protocols that are not rigorously described or fully understood.…
A House United Within Itself: SLO-Awareness for On-Premises Containerized ML Inference Clusters via Faro
Beomyeol Jeon, Chen Wang, Diana Arroyo +2
This paper tackles the challenge of running multiple ML inference jobs (models) under time-varying workloads, on a constrained on-premises production cluster. Our system Faro takes…
SLSGD: Secure and Efficient Distributed On-device Machine Learning
Cong Xie, Sanmi Koyejo, Indranil Gupta
We consider distributed on-device learning with limited communication and security requirements. We propose a new robust distributed optimization algorithm with efficient communica…
CSER: Communication-efficient SGD with Error Reset
Cong Xie, Shuai Zheng, Oluwasanmi Koyejo +3
The scalability of Distributed Stochastic Gradient Descent (SGD) is today limited by communication bottlenecks. We propose a novel SGD variant: Communication-efficient SGD with Err…
Phocas: dimensional Byzantine-resilient stochastic gradient descent
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta
We propose a novel robust aggregation rule for distributed synchronous Stochastic Gradient Descent~(SGD) under a general Byzantine failure model. The attackers can arbitrarily mani…
Asynchronous Federated Optimization
Cong Xie, Sanmi Koyejo, Indranil Gupta
Federated learning enables training on a massive number of edge devices. To improve flexibility and scalability, we propose a new asynchronous federated optimization algorithm. We…
SILC: Lookahead Caching for Short-form Video Delivery Systems
Maleeha Masood, Shreya Kannan, Om Chabra +2
Short video platforms like TikTok, Instagram Reels, and YouTube Shorts have gained immense popularity in the last few years and are responsible for a large and growing fraction of…