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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) DTN¿¡¼­ Markov ChainÀ» ÀÌ¿ëÇÑ ³ëµåÀÇ À̵¿ ¿¹Ãø ±â¹ý
¿µ¹®Á¦¸ñ(English Title) Prediction method of node movement using Markov Chain in DTN
ÀúÀÚ(Author) ÀüÀϱԠ  ÀÌ°­È¯   Il-kyu Jeon   Kang-whan Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 20 NO. 05 PP. 1013 ~ 1019 (2016. 05)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â Delay Tolerant Network(DTN)¿¡¼­ Markov chainÀ¸·Î ³ëµåÀÇ ¼Ó¼º Á¤º¸¸¦ ºÐ¼®ÇÏ¿© ³ëµåÀÇ À̵¿°æ·Î¸¦ ¿¹ÃøÇÏ´Â ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. ±âÁ¸ DTN¿¡¼­ÀÇ ¿¹Ãø±â¹Ý ¶ó¿ìÆà ±â¹ýÀº ³ëµå°¡ ¹Ì¸® Á¤ÇØÁø ½ºÄÉÁÙ¿¡ µû¶ó À̵¿ÇÏ°Ô µÈ´Ù. ÀÌ·¯ÇÑ ³×Æ®¿öÅ©¿¡¼­´Â ½ºÄÉÁÙÀ» ¿¹ÃøÇÒ ¼ö ¾ø´Â ȯ°æ¿¡¼­ ³ëµåÀÇ ½Å·Ú¼ºÀÌ ³·¾ÆÁö´Â ¹®Á¦°¡ ÀÖ´Ù. º» ³í¹®¿¡¼­´Â ÀÌ·¯ÇÑ ¹®Á¦¸¦ ±Øº¹Çϱâ À§ÇØ ³ëµåÀÇ ¼Ó¼º Á¤º¸¸¦ Markov chainÀ» Àû¿ëÇÏ°í ÀÏÁ¤ ±¸°£¿¡¼­ ½Ã°£¿¡ µû¸¥ ³ëµåÀÇ À̵¿ °æ·Î¸¦ ¿¹ÃøÇÏ´Â CMCP(Context-awareness Markov- Chain Prediction)¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¾Ë°í¸®ÁòÀº ³ëµåÀÇ ¼Ó¼º Á¤º¸ Áß ³ëµåÀÇ ¼Ó·Â°ú ¹æÇ⼺À» ±Ù»çÇÑ ÈÄ Markov chainÀ» ÀÌ¿ëÇÏ¿© Á¦ÇÑµÈ ÁÖ±â¿Í ¹öÆÛÀÇ ¹üÀ§¿¡¼­ È®·üÀüÀÌ ¸ÅÆ®¸¯½º¸¦ »ý¼ºÇÏ¿© ³ëµåÀÇ À̵¿ °æ·Î¸¦ ¿¹ÃøÇÏ´Â ¾Ë°í¸®ÁòÀÌ´Ù. ÁÖ¾îÁø ¸ðÀǽÇÇè ȯ°æ¿¡¼­ ³ëµåÀÇ À̵¿ °æ·Î ¿¹ÃøÀ» ÅëÇØ Áß°è ³ëµå¸¦ ¼±Á¤ÇÏ¿© ¶ó¿ìÆà ÇÔÀ¸·Î½á ¸Þ½ÃÁö Àü¼Û Áö¿¬ ½Ã°£ÀÌ °¨¼ÒÇÏ°í Àü¼Û·üÀÌ Áõ°¡ÇÔ º¸¿©ÁÖ°í ÀÖ´Ù.

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(English Abstract)
This paper describes a novel Context-awareness Markov Chain Prediction (CMCP) algorithm based on movement prediction using Markov chain in Delay Tolerant Network (DTN). The existing prediction models require additional information such as a node¡¯s schedule and delivery predictability. However, network reliability is lowered when additional information is unknown. To solve this problem, we propose a CMCP model based on node behaviour movement that can predict the mobility without requiring additional information such as a node¡¯s schedule or connectivity between nodes in periodic interval node behavior. The main contribution of this paper is the definition of approximate speed and direction for prediction scheme. The prediction of node movement forwarding path is made by manipulating the transition probability matrix based on Markov chain models including buffer availability and given interval time. We present simulation results indicating that such a scheme can be beneficial effects that increased the delivery ratio and decreased the transmission delay time of predicting movement path of the node in DTN.
Å°¿öµå(Keyword) Áö¿¬³»¼º¸Á   ¿¹Ãø   »óȲÀνĠ  ¸¶ÄÚºê üÀΠ  Delay Tolerant Network   Prediction   Context-awareness   Markov chain  
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