| LDR | | 01776nam u200385 4500 |
| 001 | | 000000421288 |
| 005 | | 20190215165207 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438154421 |
| 035 | |
▼a (MiAaPQ)AAI10791983 |
| 035 | |
▼a (MiAaPQ)purdue:22521 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Li, Yimei. |
| 245 | 10 |
▼a Data Compression in Multi-hop Large-scale Wireless Sensor Networks. |
| 260 | |
▼a [S.l.]:
▼b Purdue University.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 125 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Advisers: Yao Liang |
| 502 | 1 |
▼a Thesis (Ph.D.)--Purdue University, 2018. |
| 520 | |
▼a Data collection from a multi-hop large-scale outdoor WSN deployment for environmental monitoring is full of challenges due to the severe resource constraints on small battery-operated motes (e.g., bandwidth, memory, power, and computing capacity |
| 520 | |
▼a For some WSN scenarios, CS may not be applicable. Therefore we also design a generalized predictive coding framework for unified lossless and lossy data compression. In addition, we devise a novel algorithm for lossless compression to significan |
| 590 | |
▼a School code: 0183. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a Purdue University.
▼b Computer Sciences. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0183 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997675
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |