2 citations · 8 across the 17 of their papers we have counts for
17 papers
Revenue Optimization in Wireless Video Caching Networks: A Privacy-Preserving Two-Stage Solution
Yijing Zhang, Md-Ferdous Pervej, Andreas F. Molisch
Video caching can significantly improve delivery efficiency and enhance quality of video streaming, which constitutes the majority of wireless communication traffic. Due to limited…
Computation- and Communication-Efficient Online FL for Resource-Constrained Aerial Vehicles
Ferdous Pervej, Richeng Jin, Md Moin Uddin Chowdhury +3
Privacy-preserving distributed machine learning (ML) and aerial connected vehicle (ACV)-assisted edge computing have drawn significant attention lately. Since the onboard sensors o…
Revenue Optimization in Video Caching Networks with Privacy-Preserving Demand Predictions
Yijing Zhang, Ferdous Pervej, Andreas F. Molisch
Performance of video streaming, which accounts for most of the traffic in wireless communication, can be significantly improved by caching popular videos at the wireless edge. Dete…
Double Directional Wireless Channel Generation: A Statistics-Informed Generative Approach
Md-Ferdous Pervej, Patel Pratik, Koushik Manjunatha +2
Channel models that represent various operating conditions a communication system might experience are important for design and standardization of any communication system. While s…
Personalized Hierarchical Split Federated Learning in Wireless Networks
Md-Ferdous Pervej, Andreas F. Molisch
Extreme resource constraints make large-scale machine learning (ML) with distributed clients challenging in wireless networks. On the one hand, large-scale ML requires massive info…
Online-Score-Aided Federated Learning for Resource-Constrained Wireless Clients with Continual Data Arrival
Ferdous Pervej, Minseok Choi, Andreas F. Molisch
Heterogeneous system configurations of distributed clients connected to the central server (CS) via a time-varying wireless network pose significant challenges for popular distribu…
Resource-Aware Hierarchical Federated Learning in Wireless Video Caching Networks
Md Ferdous Pervej, Andreas F. Molisch
Backhaul traffic congestion caused by the video traffic of a few popular files can be alleviated by storing the to-be-requested content at various levels in wireless video caching…
Resource-Aware Hierarchical Federated Learning for Video Caching in Wireless Networks
Md Ferdous Pervej, Andreas F Molisch
Video caching can significantly improve backhaul traffic congestion by locally storing the popular content that users frequently request. A privacy-preserving method is desirable t…
Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity
Md Ferdous Pervej, Richeng Jin, Huaiyu Dai
While a practical wireless network has many tiers where end users do not directly communicate with the central server, the users' devices have limited computation and battery power…
Resource Constrained Vehicular Edge Federated Learning with Highly Mobile Connected Vehicles
Md Ferdous Pervej, Richeng Jin, Huaiyu Dai
This paper proposes a vehicular edge federated learning (VEFL) solution, where an edge server leverages highly mobile connected vehicles' (CVs') onboard central processing units (C…
Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles
Md Ferdous Pervej, Jianlin Guo, Kyeong Jin Kim +7
While privacy concerns entice connected and automated vehicles to incorporate on-board federated learning (FL) solutions, an integrated vehicle-to-everything communication with het…
Efficient Content Delivery in User-Centric and Cache-Enabled Vehicular Edge Networks with Deadline-Constrained Heterogeneous Demands
Md Ferdous Pervej, Richeng Jin, Shih-Chun Lin +1
Modern connected vehicles (CVs) frequently require diverse types of content for mission-critical decision-making and onboard users' entertainment. These contents are required to be…
Vehicular Network Slicing for Reliable Access and Deadline-Constrained Data Offloading: A Multi-Agent On-Device Learning Approach
Md Ferdous Pervej, Shih-Chun Lin
Efficient data offloading plays a pivotal role in computational-intensive platforms as data rate over wireless channels is fundamentally limited. On top of that, high mobility adds…
User Preference Learning-Aided Collaborative Edge Caching for Small Cell Networks
Md Ferdous Pervej, Le Thanh Tan, Rose Qingyang Hu
While next-generation wireless communication networks intend leveraging edge caching for enhanced spectral efficiency, quality of service, end-to-end latency, content sharing cost,…
Artificial Intelligence Assisted Collaborative Edge Caching in Small Cell Networks
Md Ferdous Pervej, Le Thanh Tan, Rose Qingyang Hu
Edge caching is a new paradigm that has been exploited over the past several years to reduce the load for the core network and to enhance the content delivery performance. Many exi…
Dynamic Power Allocation and Virtual Cell Formation for Throughput-Optimal Vehicular Edge Networks in Highway Transportation
Md Ferdous Pervej, Shih-Chun Lin
This paper investigates highly mobile vehicular networks from users' perspectives in highway transportation. Particularly, a centralized software-defined architecture is introduced…
Eco-Vehicular Edge Networks for Connected Transportation: A Distributed Multi-Agent Reinforcement Learning Approach
Md Ferdous Pervej, Shih-Chun Lin
This paper introduces an energy-efficient, software-defined vehicular edge network for the growing intelligent connected transportation system. A joint user-centric virtual cell fo…