1 citations · 1 across the 10 of their papers we have counts for
10 papers
Trust-Aware Topology Learning for Dynamic Decentralized Federated Learning under Adversaries
Shubham Vaishnav, Murtaza Rangwala, Ali Beikmohammadi +2
In dynamic mobile decentralized federated learning (DFL), adversaries can poison both model updates and the topology information devices use to choose collaborators. We present DMT…
A Periodic Space of Distributed Computing: Vision & Framework
Mohsen Amini Salehi, Adel N. Tousi, Hai Duc Nguyen +5
Advances in networking and computing technologies throughout the early decades of the 21st century have transformed long-standing dreams of pervasive communication and computation…
Spontaneous Symmetry Breaking and Collective Higgs-Goldstone Dynamics in Solid-State Phononic Frequency Combs
Murtaza Rangwala, Adarsh Ganesan
We investigate the generation of phononic frequency combs arising from nonlinear coupling between Higgs-like and Goldstone-like phonon modes in hexagonal InMnO3. The Higgs-like mod…
Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Decentralized federated learning (DFL) enables collaborative model training across edge devices without centralized coordination, offering resilience against single points of failu…
Differential Privacy for Secure Machine Learning in Healthcare IoT-Cloud Systems
N Mangala, Murtaza Rangwala, S Aishwarya +5
Healthcare has become exceptionally sophisticated, as wearables and connected medical devices revolutionize remote patient monitoring, emergency response, medication management, di…
On the Generation of Phononic Frequency Combs Using Defect Modes of Phononic Crystals
Suhas Suresh Bharadwaj, Murtaza Rangwala, Adarsh Ganesan
This paper proposes a method for generating phononic frequency combs (PFCs) using defect-localized modes in a two-dimensional hexagonal phononic crystal. Localized vibration modes…
Screen Before You Fetch: Compressed Byzantine Screening for Decentralized Learning on the Edge-Cloud Continuum
Murtaza Rangwala, Farag Azzedin, Richard O. Sinnott +1
In decentralized federated learning, Byzantine-robust defenses filter neighbors by model similarity, but only after receiving each neighbor's full model. On constrained edge uplink…
Blockchain-Enabled Federated Learning
Murtaza Rangwala, KR Venugopal, Rajkumar Buyya
Blockchain-enabled federated learning (BCFL) addresses fundamental challenges of trust, privacy, and coordination in collaborative AI systems. This chapter provides comprehensive a…
Topology-Aware Differential Privacy in Hierarchical Federated Learning
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Hierarchical federated learning places regional aggregators between clients and the cloud, so a participant's update is observed only alongside its neighbours'. The concealment thi…
TrustMesh: A Blockchain-Enabled Trusted Distributed Computing Framework for Open Heterogeneous IoT Environments
Murtaza Rangwala, Rajkumar Buyya
The rapid evolution of Internet of Things (IoT) environments has created an urgent need for secure and trustworthy distributed computing systems, particularly when dealing with het…