Zobrazeno 1 - 10
of 102
pro vyhledávání: '"LI Mushu"'
Autor:
Manjunath, Yoga Suhas Kuruba, Wissborn, Austin, Szymanowski, Mathew, Li, Mushu, Zhao, Lian, Zhang, Xiao-Ping
In this paper, we design an exclusive Metaverse network traffic classifier, named Discern-XR, to help Internet service providers (ISP) and router manufacturers enhance the quality of Metaverse services. Leveraging segmented learning, the Frame Vector
Externí odkaz:
http://arxiv.org/abs/2411.05184
Publikováno v:
IEEE Internet Things J. (Volume: 11, Issue: 7, 01 April 2024)
Device-edge collaboration on deep neural network (DNN) inference is a promising approach to efficiently utilizing network resources for supporting artificial intelligence of things (AIoT) applications. In this paper, we propose a novel digital twin (
Externí odkaz:
http://arxiv.org/abs/2405.17664
In this paper, we propose a novel efficient digital twin (DT) data processing scheme to reduce service latency for multicast short video streaming. Particularly, DT is constructed to emulate and analyze user status for multicast group update and swip
Externí odkaz:
http://arxiv.org/abs/2404.13749
In this paper, we propose a digital twin (DT)-based user-centric approach for processing sensing data in an integrated sensing and communication (ISAC) system with high accuracy and efficient resource utilization. The considered scenario involves an
Externí odkaz:
http://arxiv.org/abs/2311.12223
Publikováno v:
in IEEE Journal of Selected Topics in Signal Processing, vol. 17, no. 5, pp. 1131-1146, Sept. 2023
In this paper, we present a novel content caching and delivery approach for mobile virtual reality (VR) video streaming. The proposed approach aims to maximize VR video streaming performance, i.e., minimizing video frame missing rate, by proactively
Externí odkaz:
http://arxiv.org/abs/2311.10645
Edge-device collaboration has the potential to facilitate compute-intensive device pose tracking for resource-constrained mobile augmented reality (MAR) devices. In this paper, we devise a 3D map management scheme for edge-assisted MAR, wherein an ed
Externí odkaz:
http://arxiv.org/abs/2311.04997
While network slicing has become a prevalent approach to service differentiation, radio access network (RAN) slicing remains challenging due to the need of substantial adaptivity and flexibility to cope with the highly dynamic network environment in
Externí odkaz:
http://arxiv.org/abs/2308.10961
Multicast short video streaming (MSVS) can effectively reduce network traffic load by delivering identical video sequences to multiple users simultaneously. The existing MSVS schemes mainly rely on the aggregated video requests to reserve bandwidth a
Externí odkaz:
http://arxiv.org/abs/2308.08995
In this paper, we design a 3D map management scheme for edge-assisted mobile augmented reality (MAR) to support the pose estimation of individual MAR device, which uploads camera frames to an edge server. Our objective is to minimize the pose estimat
Externí odkaz:
http://arxiv.org/abs/2305.16571