.png){kind=icon}
返回
Heterogeneous resource allocation with latency guarantee for computing power network
.png){kind=icon}
OA
AI
DOI：10.1016/j.dcan.2025.03.011.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Computing Power Network (CPN) is a new paradigm that integrates communication, computing, and storage resources to provide services for tasks. However, tasks composed of non-independent subtasks have a preference for the resources required at each stage, which increases the difficulty of heterogeneous resource allocation and reduces the latency performance of CPN services. Motivated by this, this paper jointly optimizes the full-service cycle of tasks, including transmission, task partitioning, and offloading. First, the transmission bandwidth is dynamically configured based on delay sensitivity of tasks. Second, with the real-time information from edge resource clusters and state resource clusters in the network, the optimal partitioning for a computation task is derived. Third, personalized resource allocation schemes are customized for computation and storage tasks respectively. Finally, the impact of resource parameter configuration on the latency violation probability of CPN is revealed. Moreover, compared with the benchmark schemes, our proposed scheme reduces the network latency violation probability by up to 1.17 × in the same network setting.
Keyword:
Latency violation probability
Subtask dependencies
Resource allocation
Computing power network
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
419
被引数:
3.5K
机构
引用论文
Virtual Network Embedding Over Multi-Band Elastic Optical Network Based on Cross-Matching Mechanism and Hypergraph Theory基于交叉匹配机制和超图理论的多带弹性光网络虚拟网络嵌入
.png){kind=icon}
PREAI
分享收藏Multi-Layer Computation Offloading in Distributed Heterogeneous Mobile Edge Computing Networks分布式异构移动边缘计算网络中的多层计算卸载
PREAI
分享收藏分享收藏
查看更多内容