Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Pervej, Md Ferdous"'
While FL is a widely popular distributed ML strategy that protects data privacy, time-varying wireless network parameters and heterogeneous system configurations of the wireless device pose significant challenges. Although the limited radio and compu
Externí odkaz:
http://arxiv.org/abs/2408.05886
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 networks. Typically, content service providers (CSPs) own the content,
Externí odkaz:
http://arxiv.org/abs/2402.04216
Autor:
Pervej, Md Ferdous, Molisch, Andreas F
Video caching can significantly improve backhaul traffic congestion by locally storing the popular content that users frequently request. A privacy-preserving method is desirable to learn how users' demands change over time. As such, this paper propo
Externí odkaz:
http://arxiv.org/abs/2311.06918
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. Owing to t
Externí odkaz:
http://arxiv.org/abs/2308.01562
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. Convergence analysis
Externí odkaz:
http://arxiv.org/abs/2210.15496
Autor:
Pervej, Md Ferdous, Guo, Jianlin, Kim, Kyeong Jin, Parsons, Kieran, Orlik, Philip, Di Cairano, Stefano, Menner, Marcel, Berntorp, Karl, Nagai, Yukimasa, Dai, Huaiyu
While privacy concerns entice connected and automated vehicles to incorporate on-board federated learning (FL) solutions, an integrated vehicle-to-everything communication with heterogeneous computation power aware learning platform is urgently neces
Externí odkaz:
http://arxiv.org/abs/2205.09529
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 fully delivered to the requester CVs within stringent deadlines that
Externí odkaz:
http://arxiv.org/abs/2202.07792
Autor:
Pervej, Md Ferdous, Lin, Shih-Chun
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 an extra burden in vehicular edge networks (VENs), bolstering the des
Externí odkaz:
http://arxiv.org/abs/2012.15545
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 existing caching solutions only consider homogeneous caching placement du
Externí odkaz:
http://arxiv.org/abs/2005.07941
While next-generation wireless communication networks intend leveraging edge caching for enhanced spectral efficiency, quality of service, end-to-end latency, content sharing cost, etc., several aspects of it are yet to be addressed to make it a real
Externí odkaz:
http://arxiv.org/abs/2005.07942