Publications

Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices

Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite …
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Sage: Leveraging ML To Diagnose Unpredictable Performance in Cloud Microservices

Cloud applications are increasingly shifting from large monolithic services, to complex graphs of loosely-coupled microservices. …
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Unveiling the Hardware and Software Implications of Microservices in Cloud and Edge Systems

Cloud services progressively shift from monolithic applications to complex graphs of loosely-coupled microservices. This article aims …
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Leveraging Deep Learning to Improve Performance Predictability in Cloud Microservices with Seer

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. …
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Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. …
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An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud and Edge Systems

Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds of loosely-coupled …
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μqSim: Enabling Accurate and Scalable Simulation for Interactive Microservices

Current cloud services are moving away from monolithic designs and towards graphs of many looselycoupled, single-concerned …
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The Architectural Implications of Cloud Microservices

Cloud services have recently undergone a shift from monolithic applications to microservices, with hundreds or thousands of …
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Seer: Leveraging Big Data to Navigate the Increasing Complexity of Cloud Debugging

Performance unpredictability in cloud services leads to poor user experience, degraded availability, and has revenue ramifications. …
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Secure Collaborative Spectrum Sensing: A Peer-Prediction Method

Collaborative spectrum sensing is an effective method to improve detection rates in cognitive radio networks. However, it is vulnerable …
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Incentive Attack Prevention for Collaborative Spectrum Sensing: A Peer-Prediction Method

Collaborative spectrum sensing is an effective method to improve the detection rate in cognitive radio. However, it is vulnerable to …
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