東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Improved algorithms for multicast ro...

Cai, Zhipeng.

FindBook

Google Book

Amazon

博客來

Improved algorithms for multicast routing and binary fingerprint vector clustering.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Improved algorithms for multicast routing and binary fingerprint vector clustering./
作者:	Cai, Zhipeng.
面頁冊數:	52 p.
附註:	Source: Masters Abstracts International, Volume: 43-03, page: 0870.
Contained By:	Masters Abstracts International43-03.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ95715
ISBN:	0612957152

Improved algorithms for multicast routing and binary fingerprint vector clustering.
Cai, Zhipeng.

Improved algorithms for multicast routing and binary fingerprint vector clustering. - 52 p.

Source: Masters Abstracts International, Volume: 43-03, page: 0870.

Thesis (M.Sc.)--University of Alberta (Canada), 2004.

Two problems are studied in this thesis. One is multicast routing including multicast k-path routing (kMPR) and multicast k-tree routing (kMTR) for which two approximation algorithms are proposed. The other is the clustering of binary fingerprint vectors with missing values for which an exact search algorithm is proposed.

ISBN: 0612957152Subjects--Topical Terms:

626642
Computer Science.

Improved algorithms for multicast routing and binary fingerprint vector clustering.
LDR:02550nmm 2200289 4500 001 1851758
005 20051215075006.5
008 130614s2004 eng d
020 $a 0612957152
035 $a (UnM)AAIMQ95715
035 $a AAIMQ95715
040 $a UnM $c UnM
100 1 $a Cai, Zhipeng. $3 1939640
245 1 0 $a Improved algorithms for multicast routing and binary fingerprint vector clustering.
300 $a 52 p.
500 $a Source: Masters Abstracts International, Volume: 43-03, page: 0870.
500 $a Adviser: Guohui Lin.
502 $a Thesis (M.Sc.)--University of Alberta (Canada), 2004.
520 $a Two problems are studied in this thesis. One is multicast routing including multicast k-path routing (kMPR) and multicast k-tree routing (kMTR) for which two approximation algorithms are proposed. The other is the clustering of binary fingerprint vectors with missing values for which an exact search algorithm is proposed.
520 $a The problem of kMPR (kMTR) is to find a set of paths (trees) with the minimum total cost in a communication network where a subset of the nodes in the network are specified as the destination nodes to receive data. Data is transmitted from the source node along these paths (trees). Each such path (tree) is constrained to accommodate at most k destination nodes and each destination node can only receive data transmitted along one of the paths (trees). The worst case performance ratios of the proposed approximation algorithms are 3 and (2 + rho), respectively, where rho is the best approximation ratio for the metric Steiner tree problem (which is about 1.55 currently). These algorithms beat the previous best approximations whose worst case performance ratios are 4 and (2.4 + rho), respectively.
520 $a The problem of clustering binarized oligonucleotide fingerprints is to identify the clusters and to resolve the missing values in the fingerprints simultaneously. The clustering is formulated into a combinatorial optimization problem---the Assignment Clustering Problem (ACP). A heuristic search algorithm, A* search, from the Artificial Intelligence community is adopted to solve the ACP problem optimally. The implementation has been tested on two real datasets and the experimental results show that the proposed exact algorithm runs fast.
590 $a School code: 0351.
650 4 $a Computer Science. $3 626642
690 $a 0984
710 2 0 $a University of Alberta (Canada). $3 626651
773 0 $t Masters Abstracts International $g 43-03.
790 1 0 $a Lin, Guohui, $e advisor
790 $a 0351
791 $a M.Sc.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ95715