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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
Áö¿À¼¾¼ ³×Æ®¿öÅ©ÀÇ ´ÙÁß °ø°£ÁúÀÇ ÃÖÀûȸ¦ À§ÇÑ °ø°£ÁúÀÇ󸮺ñ¿ë ¿¹Ãø ¾Ë°í¸®Áò ¿¬±¸ |
¿µ¹®Á¦¸ñ(English Title) |
A Study on Cost Estimation of Spatial Query Processing for Multiple Spatial Query Optimization in GeoSensor Networks |
ÀúÀÚ(Author) |
±è¹Î¼ö
ÀåÀμº
À̱âÁØ
Min Soo Kim
In Sung Jang
Ki Joune Li
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¿ø¹®¼ö·Ïó(Citation) |
VOL 21 NO. 02 PP. 0023 ~ 0033 (2013. 04) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù IoT (Internet of Things) ±â¼úÀÇ ¹ßÀü°ú ´õºÒ¾î ¹«¼± ȯ°æ¿¡¼ ƯÁ¤ ¿µ¿ª¿¡ À§Ä¡ÇÏ´Â ¼¾¼³ëµåÀÇ À§Ä¡-¼¾¼Á¤º¸¸¦ ¿¡³ÊÁö È¿À²ÀûÀ¸·Î ¼öÁýÇÏ´Â ¼¾¼ ³×Æ®¿öÅ© ±â¹Ý °ø°£ÁúÀÇ󸮿¡ ´ëÇÑ °ü½ÉÀÌ Å©°Ô Áõ°¡ÇÏ°í ÀÖ´Ù. ±×¸®ÇÏ¿© ¼¾¼³ëµå¿¡¼ °ø°£ ÇÊÅ͸µÀ» Á÷Á¢ ¼öÇàÇÏ¿© ¼¾¼³ëµåµé °£ÀÇ Åë½Å Ƚ¼ö¸¦ °¨¼Ò½ÃÄÑ ¿¡³ÊÁö ¼Ò¸ð¸¦ ÃÖ¼ÒÈÇÏ´Â ´Ù¾çÇÑ °ø°£ÁúÀÇó¸® ¾Ë°í¸®Áò ¹× ºÐ»ê °ø°£»öÀιæ¹ýµéÀÌ Á¦¾ÈµÇ¾î ¿Ô´Ù. ±×·¯³ª ´ÜÀÏ °ø°£ÁúÀÇó¸® ÃÖÀûÈ¿¡ ÁßÁ¡À» µÎ¾ú´ø ±âÁ¸ °ø°£»öÀιæ¹ý ¹× ¾Ë°í¸®ÁòµéÀº IoT ȯ°æ¿¡¼ ´Ù¼ö »ç¿ëÀÚ¿¡ ÀÇÇÏ¿© ¿äûµÇ´Â ´ÙÁß °ø°£ÁúÀǸ¦ ÃÖÀûÈÇÏ¿© ¼öÇàÇϱ⿡´Â ÇÑ°è°¡ ÀÖ¾ú´Ù. ÀÌ¿¡ º» ³í¹®¿¡¼´Â ¼¾¼ ³×Æ®¿öÅ©¿¡¼ ´ÙÁß °ø°£ÁúÀǸ¦ ¿¡³ÊÁö È¿À²ÀûÀ¸·Î ó¸®ÇÒ ¼ö ÀÖ´Â ÃÖÀûÈ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÏ°í ÀÖ´Ù. Á¦¾ÈµÈ ´ÙÁß °ø°£ÁúÀÇ ÃÖÀûÈ ¾Ë°í¸®ÁòÀº ÀÎÁ¢ ¿µ¿ª¿¡ ÁÖ¾îÁö´Â °ø°£ÁúÀǵéÀ» ÅëÇÕÇÏ¿© ¼öÇàÇÏ´Â ¡®ÁúÀÇÅëÇÕ¡¯ °³³äÀ» ±âº»À¸·Î ÇÏ°í ÀÖ´Ù. ÃÖÀûÈ °úÁ¤¿¡¼ ÁúÀǵéÀÇ ÅëÇÕ ¶Ç´Â °³º° ¼öÇà¿¡ ´ëÇÑ ÆÇ´ÜÀº °¢ ¼öÇàºñ¿ëÀ» ¿¹ÃøÇÏ¿© °áÁ¤Çϸç, º» ³í¹®¿¡¼´Â ÁúÀÇó¸® ºñ¿ë ¿¹Ãø ¹æ¹ýÀ» Ãß°¡ÀûÀ¸·Î Á¦¾ÈÇÏ°í ÀÖ´Ù. ³¡À¸·Î, ¼º´ÉÆò°¡¿¡¼´Â GR-tree, SPIX, CPSÀÇ °ø°£»öÀιæ¹ý¿¡ ´ëÇÑ ºñ±³ ½ÇÇèÀ» ÅëÇÏ¿© Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀÇ ¼º´É ºÐ¼®°á°ú¸¦ Á¦½ÃÇÏ°í ÀÖ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
With the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of ¡®query merging¡¯ that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm¡¯s distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS. |
Å°¿öµå(Keyword) |
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°ø°£ÁúÀÇ ÃÖÀûÈ
°ø°£ÁúÀÇó¸® ºñ¿ë ¿¹Ãø
Geosensor
Distributed Spatial Index
Spatial Query Optimization
Cost Estimation
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