Temporal-spatial aggregation for cache-enabled wireless multicasting networks with asynchronous content requests

2017年2月7日·
Jeff XING
Jeff XING
,
Ying Cui
,
Vincent Lau
· 0 分钟阅读时长
摘要
Existing multicasting schemes for massive content delivery do not fully utilize multicasting opportunities in delay tolerant content-oriented applications. In this paper, we propose a novel temporal-spatial aggregation-based multicasting scheme in a large-scale cache-enabled wireless network. The proposed scheme can efficiently exploit multicasting opportunities in asynchronous content requests to improve spectral efficiency. By making use of the delay tolerance of elastic services, the proposed scheme achieves a better energy-throughput-delay tradeoff. Utilizing tools from stochastic geometry, we derive a tractable expression for the successful transmission probability in the general region. Using asymptotic approximations, we derive closed form successful transmission probabilities in the large delay region as well as the large and small user density regions. The asymptotic results reveal that the successful transmission probability increases and the energy consumption decreases at the cost of delay increase in these asymptotic regions. The analysis in this paper provides a new understanding of the energy-throughput-delay tradeoff for massive content delivery in large-scale cache-enabled wireless networks.
类型
publications
Jeff XING
Authors
Engineer in AI
Jeff XING is an Engineer in AI at AMD. He builds high-performance LLM and multimodal inference systems for agentic AI applications. His broader work spans distributed serving, computer vision, robotics, and image processing, with a focus on turning research ideas into reliable products.
Authors