@inproceedings{23fac1639fb54971921bea76fb3bd628,
title = "Non-parametric message important measure: Compressed storage design for big data in wireless communication systems",
abstract = "This paper mainly considers the compressed storage problem for big data in wireless communication systems, where the message importance is taken into account. Similar to Shannon Entropy and Renyi Entropy, we first define a non-parametric message important measure (NMIM) as a measure for message importance. It can characterize the uncertainty of random events. It is proved that it can sufficiently describe the two key characters of big data: rare events finding and large diversities of events. Based on NMIM, we propose an effective compressed encoding mode for data storage in wireless communication systems. Numerical simulation results show that using our developed strategy takes up very little storage space without losing too much message importance.",
keywords = "Big Data, Compressed encoding, Compressed Storage, Non-parametric message important measure",
author = "Shanyun Liu and Rui She and Pingyi Fan and Jiaxun Lu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 23rd Asia-Pacific Conference on Communications, APCC 2017 ; Conference date: 11-12-2017 Through 13-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.23919/APCC.2017.8304050",
language = "英语",
series = "2017 23rd Asia-Pacific Conference on Communications: Bridging the Metropolitan and the Remote, APCC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "2017 23rd Asia-Pacific Conference on Communications",
address = "美国",
}