11 citations · 14 across the 14 of their papers we have counts for
17 papers
AI or Real: Detecting Partially Altered Videos Under Resource-Constrained Environments
Tamoghna Chakraborty, Md Nurul Absur, Sourya Saha +1
The proliferation of generative video models has shifted the practical detection threat from fully fabricated clips to partially manipulated footages. Although modern detectors ach…
Round Trip Time: A Benign Signal or an Indirect Window into Datacenter Workloads?
Sourya Saha, Md Nurul Absur, Saptarshi Debroy
Multi-tenant datacenter networks increasingly rely on shared leaf-spine fabrics, where traffic from multiple tenants traverses common network resources. While logical isolation mec…
ProFlow: RL-Driven and Performance-Aware Proactive Flow Placement in Datacenter Networks
Sourya Saha, Md Nurul Absur, Saptarshi Debroy
In datacenter fabrics composed of leaf and aggregation switches, competing flows may become co-located on shared aggregation switches, creating congestion that can significantly de…
Noise-Aware Misclassification Attack Detection in Collaborative DNN Inference
Shima Yousefi, Saptarshi Debroy
Collaborative inference of object classification Deep neural Networks (DNNs) where resource-constrained end-devices offload partially processed data to remote edge servers to compl…
Deep Reinforcement Learning-driven Edge Offloading for Latency-constrained XR pipelines
Sourya Saha, Saptarshi Debroy
Immersive extended reality (XR) applications introduce latency-critical workloads that must satisfy stringent real-time responsiveness while operating on energy- and battery-constr…
Reinforcement Learning-Driven Edge Management for Reliable Multi-view 3D Reconstruction
Motahare Mounesan, Sourya Saha, Houchao Gan +2
Real-time multi-view 3D reconstruction is a mission-critical application for key edge-native use cases, such as fire rescue, where timely and accurate 3D scene modeling enables sit…
Detection of Misreporting Attacks on Software-Defined Immersive Environments
Sourya Saha, Md Nurul Absur, Shima Yousefi +1
The ability to centrally control network infrastructure using a programmable middleware has made Software-Defined Networking (SDN) ideal for emerging applications, such as immersiv…
Detection and Recovery of Adversarial Slow-Pose Drift in Offloaded Visual-Inertial Odometry
Soruya Saha, Md Nurul Absur, Saptarshi Debroy
Visual-Inertial Odometry (VIO) supports immersive Virtual Reality (VR) by fusing camera and Inertial Measurement Unit (IMU) data for real-time pose. However, current trend of offlo…
Reliable Multi-view 3D Reconstruction for `Just-in-time' Edge Environments
Md. Nurul Absur, Abhinav Kumar, Swastik Brahma +1
Multi-view 3D reconstruction applications are revolutionizing critical use cases that require rapid situational-awareness, such as emergency response, tactical scenarios, and publi…
Variational Autoencoder-Based Black-Box Adversarial Attack on Collaborative DNN Inference
Shima Yousefi, Motahare Mounesan, Saptarshi Debroy
In recent years, Deep Neural Networks (DNNs) have become increasingly integral to IoT-based environments, enabling realtime visual computing. However, the limited computational cap…
Infer-EDGE: Dynamic DNN Inference Optimization in 'Just-in-time' Edge-AI Implementations
Motahare Mounesan, Xiaojie Zhang, Saptarshi Debroy
Balancing mutually diverging performance metrics, such as end-to-end latency, accuracy, and device energy consumption, is a challenging undertaking for deep neural network (DNN) in…
Poster: Reliable 3D Reconstruction for Ad-hoc Edge Implementations
Md Nurul Absur, Swastik Brahma, Saptarshi Debroy
Ad-hoc edge deployments to support real-time complex video processing applications such as, multi-view 3D reconstruction often suffer from spatio-temporal system disruptions that g…
EdgeRL: Reinforcement Learning-driven Deep Learning Model Inference Optimization at Edge
Motahare Mounesan, Xiaojie Zhang, Saptarshi Debroy
Balancing mutually diverging performance metrics, such as, processing latency, outcome accuracy, and end device energy consumption is a challenging undertaking for deep learning mo…
VECA: Reliable and Confidential Resource Clustering for Volunteer Edge-Cloud Computing
Hemanth Sai Yeddulapalli, Mauro Lemus Alarcon, Upasana Roy +5
Volunteer Edge-Cloud (VEC) computing has a significant potential to support scientific workflows in user communities contributing volunteer edge nodes. However, managing heterogene…
Reinforcement Learning-driven Data-intensive Workflow Scheduling for Volunteer Edge-Cloud
Motahare Mounesan, Mauro Lemus, Hemanth Yeddulapalli +2
In recent times, Volunteer Edge-Cloud (VEC) has gained traction as a cost-effective, community computing paradigm to support data-intensive scientific workflows. However, due to th…
End-to-End Latency Optimization of Multi-view 3D Reconstruction for Disaster Response
Xiaojie Zhang, Mingjun Li, Andrew Hilton +3
In order to plan rapid response during disasters, first responder agencies often adopt `bring your own device' (BYOD) model with inexpensive mobile edge devices (e.g., drones, robo…
DNN-based Denial of Quality of Service Attack on Software-defined Hybrid Edge-Cloud Systems
Minh Nguyen, Jacob Gately, Swati Kar +2
In order to satisfy diverse quality-of-service (QoS) requirements of complex real-time video applications, civilian and tactical use cases are employing software-defined hybrid edg…