no code implementations • 6 Feb 2024 • Md Ferdous Pervej, Andreas F. Molisch
Based on this bound, we minimize a weighted utility function for jointly configuring the controllable parameters to train the RawHFL energy efficiently under practical resource constraints.
no code implementations • 12 Nov 2023 • Md Ferdous Pervej, Andreas F Molisch
Video caching can significantly improve backhaul traffic congestion by locally storing the popular content that users frequently request.
no code implementations • 3 Aug 2023 • 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 powers, and the serving base station (BS) has a fixed bandwidth.
no code implementations • 27 Oct 2022 • 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 (CPUs) and local datasets to train a global model.
no code implementations • 17 May 2022 • Md Ferdous Pervej, Jianlin Guo, Kyeong Jin Kim, Kieran Parsons, Philip Orlik, Stefano Di Cairano, Marcel Menner, Karl Berntorp, Yukimasa Nagai, Huaiyu Dai
To take the high mobility of vehicles into account, we consider the delay as a learning parameter and restrict it to be less than a tolerable threshold.
no code implementations • 31 Dec 2020 • Md Ferdous Pervej, Shih-Chun Lin
To that end, considering practical location-aware node associations, a joint radio and power resource allocation non-cooperative stochastic game is formulated.
Networking and Internet Architecture Distributed, Parallel, and Cluster Computing Multiagent Systems Systems and Control Signal Processing Systems and Control
no code implementations • 16 May 2020 • Md Ferdous Pervej, Le Thanh Tan, Rose Qingyang Hu
Unlike these legacy modeling paradigms, this paper considers heterogeneous content preference of the users with heterogeneous caching models at the edge nodes.