当前位置: X-MOL 学术arXiv.cs.CC › 论文详情
Linear-Time Parameterized Algorithms with Limited Local Resources
arXiv - CS - Computational Complexity Pub Date : 2020-03-05 , DOI: arxiv-2003.02866
Jianer Chen; Ying Guo; Qin Huang

We propose a new (theoretical) computational model for the study of massive data processing with limited computational resources. Our model measures the complexity of reading the very large data sets in terms of the data size N and analyzes the computational cost in terms of a parameter k that characterizes the computational power provided by limited local computing resources. We develop new algorithmic techniques that implement algorithms for solving well-known computational problems on the proposed model. In particular, we present an algorithm that finds a k-matching in a general unweighted graph in time O(N + k^{2.5}) and an algorithm that constructs a maximum weighted k-matching in a general weighted graph in time O(N + k^3 log k). Both algorithms have their space complexity bounded by O(k^2).
更新日期:2020-03-09

 

全部期刊列表>>
智控未来
聚焦商业经济政治法律
跟Nature、Science文章学绘图
控制与机器人
招募海内外科研人才,上自然官网
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
湖南大学化学化工学院刘松
上海有机所
李旸
南方科技大学
西湖大学
X-MOL
支志明
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug