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Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2017³â Ãá°èÇмú´ëȸ

2017³â Ãá°èÇмú´ëȸ

Current Result Document : 5 / 105 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) ¹«¼± ¾Öµå Ȥ ³×Æ®¿öÅ©¿¡¼­ ³ëµå Ŭ·¯½ºÅ͸µÀ» À§ÇÑ À¯Àü ¾Ë°í¸®Áò
¿µ¹®Á¦¸ñ(English Title) A Genetic Algorithm for Clustering Nodes in Wireless Ad-hoc Networks
ÀúÀÚ(Author) Àå±æ¿õ   Kil-woong Jang  
¿ø¹®¼ö·Ïó(Citation) VOL 21 NO. 01 PP. 0649 ~ 0651 (2017. 06)
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(Korean Abstract)
Ŭ·¯½ºÅ͸µ ¹®Á¦´Â ¹«¼± ¾Öµå Ȥ ³×Æ®¿öÅ©ÀÇ ³×Æ®¿öÅ© ¼ö¸í°ú È®À强À» Çâ»ó½ÃÅ°´Â ¹®Á¦ Áß ÇϳªÀÌ´Ù. ÀÌ ¹®Á¦´Â ¹«¼± ¾Öµå Ȥ ³×Æ®¿öÅ©ÀÇ ¼³°è ¹× ¿î¿µ°ú °ü·ÃµÈ ¾î·Á¿î Á¶ÇÕ ÃÖÀûÈ­ ¹®Á¦ÀÌ´Ù. º» ³í¹®¿¡¼­´Â ³×Æ®¿öÅ© ¼ö¸íÀ» ÃÖ´ëÈ­ÇÏ°í ¹«¼± ¾Öµå Ȥ ³×Æ®¿öÅ©ÀÇ È®À强À» °í·ÁÇÑ È¿À²ÀûÀΠŬ·¯½ºÅ͸µ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. Ŭ·¯½ºÅ͸µ ¹®Á¦´Â NP-hard ¹®Á¦·Î ¾Ë·ÁÁ® ÀÖ½À´Ï´Ù. µû¶ó¼­ º» ³í¹®¿¡¼­´Â ³ëµåÀÇ ¼ö°¡ ¸¹Àº ³×Æ®¿öÅ©¿¡¼­ ÇÕ¸®ÀûÀÎ ½Ã°£ ³»¿¡ ÃÖÀûÀÇ Çظ¦ È¿À²ÀûÀ¸·Î ¾òÀ» ¼ö ÀÖ´Â ÃÖÀûÈ­ ¹æ½ÄÀ» »ç¿ëÇÏ¿© ¹®Á¦¸¦ ÇØ°áÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº ³ëµåÀÇ Àü·Â°ú Ŭ·¯½ºÅ͸µ ºñ¿ëÀ» °í·ÁÇÏ¿© Ŭ·¯½ºÅÍ Çìµå¸¦ ¼±ÅÃÇÏ°í Ŭ·¯½ºÅ͸¦ ±¸¼ºÇÑ´Ù. ¿ì¸®´Â ³ëµåÀÇ Àü¼Û¿¡³ÊÁö Ãø¸é¿¡¼­ ½Ã¹Ä·¹À̼ÇÀ» ÅëÇØ ¼º´ÉÀ» Æò°¡ÇÑ´Ù. ½Ã¹Ä·¹ÀÌ¼Ç °á°ú´Â Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀÌ ±âÁ¸ÀÇ ¾Ë°í¸®Áòº¸´Ù ¼º´ÉÀÌ ¿ì¼öÇÔÀ» º¸¿© ÁØ´Ù.
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(English Abstract)
A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes¡¯ power and the clustering cost. We evaluate this performance through some experiments in terms of nodes¡¯ transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.
Å°¿öµå(Keyword) Wireless ad-hoc networks   clustering   genetic algorithm   optimization  
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