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- W4376480910 abstract "Virtual Reality (VR) applications delivered over wireless networks have attracted interest from academia and industry. The delay of VR applications is mainly composed of computing delay and communication delay. Although cloud computing centers have adequate computing power, accessing them requires long communication delay. Mobile edge computing (MEC), which offloads the computing power from the cloud computing center to the edge, is regarded as a feasible way to alleviate communication delay. However, due to the differences in the capability and location of MEC nodes, the selection of MEC nodes will affect both the computing delay and communication delay. In this paper, we focus on the joint representation of computing and communication resources and the selection of the optimal MEC node. First, we adopt graph-based joint computing and communication resources (GCC) model for VR applications routing and formulate the VR routing problem as an ILP problem. Then we design a Computing Nodes Expanded (CNE) algorithm, which allows us to use the Dijkstra algorithm to quickly obtain the optimal computing node and the path of shortest total delay. Finally, we run numerical experiments to evaluate the performance of the proposal algorithm. Simulation shows that the CNE algorithm can reduce the total delay by 42.9% and increase the delay satisfaction ratio by 23.3% compared to other benchmark algorithms." @default.
- W4376480910 created "2023-05-14" @default.
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- W4376480910 date "2023-03-01" @default.
- W4376480910 modified "2023-09-30" @default.
- W4376480910 title "Graph based Joint Computing and Communication Scheduling for Virtual Reality Applications" @default.
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- W4376480910 doi "https://doi.org/10.1109/wcnc55385.2023.10118639" @default.
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