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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
MEC ½Ã½ºÅÛ¿¡¼ ŽºÅ© ÆÄƼ¼Å´× ±â¹ýÀÇ ¼º´É ºñ±³ |
¿µ¹®Á¦¸ñ(English Title) |
Performance Comparison of Task Partitioning Methods in MEC System |
ÀúÀÚ(Author) |
¹®¼º¿ø
ÀÓÀ¯Áø
Sungwon Moon
Yujin Lim
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 11 NO. 05 PP. 0139 ~ 0146 (2022. 05) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù »ç¹° ÀÎÅͳÝÀÇ ¹ßÀü°ú ÇÔ²² Â÷·®°ú IT ±â¼úÀÇ À¶ÇյǾî ÀÚÀ²ÁÖÇà°ú °°Àº °í¼º´ÉÀÇ ¾îÇø®ÄÉÀ̼ǵéÀÌ µîÀåÇÏ¸é¼ ¸ÖƼ ¾×¼¼½º ¿§Áö ÄÄÇ»ÆÃ(MEC)ÀÌ Â÷¼¼´ë ±â¼ú·Î ºÎ»óÇÏ¿´´Ù. ÀÌ·± °è»ê Áý¾àÀûÀΠŽºÅ©µéÀ» ³·Àº Áö¿¬½Ã°£ ¾È¿¡ Á¦°øÇϱâ À§ÇØ, ¿©·¯ MEC ¼¹ö(MECS)µéÀÌ Çù·ÂÇÏ¿© ÇØ´ç ŽºÅ©¸¦ ¼öÇàÇÒ ¼ö ÀÖµµ·Ï ŽºÅ©¸¦ ÆÄƼ¼Å´×ÇÏ´Â ±â¹ýµéÀÌ ¸¹ÀÌ Á¦¾ÈµÇ°í ÀÖ´Ù. ŽºÅ© ÆÄƼ¼Å´×°ú °ü·ÃµÈ ¿¬±¸µéÀº ¸ð¹ÙÀÏ µð¹ÙÀ̽º¿¡¼ ŽºÅ©¸¦ ÆÄƼ¼Å´×ÇÏ¿© ¿©·¯ MECSµé¿¡°Ô ¿ÀÇÁ·ÎµùÀ» ÇÏ´Â ±â¹ý°ú µð¹ÙÀ̽º¿¡¼ MECS·Î ¿ÀÇÁ·ÎµùÇÑ ÈÄ ÇØ´ç MECS¿¡¼ ÆÄƼ¼Å´×ÇÏ¿© ´Ù¸¥ MECSµé ¿¡°Ô ¸¶À̱׷¹À̼ÇÇÏ´Â ±â¹ýÀ¸·Î ³ª´©¾îº¼ ¼ö ÀÖ´Ù. º» ³í¹®¿¡¼´Â ¿ÀÇÁ·Îµù°ú ¸¶À̱׷¹À̼ÇÀ» ÀÌ¿ëÇÑ ÆÄƼ¼Å´× ±â¹ýµéÀ» ÆÄƼ¼Å´× ´ë»ó ¼±Á¤ ¹æ¹ý ¹× ÆÄƼ¼Å´× °³¼ö º¯È¿¡ µû¸¥ ¼ºñ½º Áö¿¬½Ã°£, °ÅÀý·ü ±×¸®°í Â÷·®ÀÇ ¿¡³ÊÁö ¼Òºñ·® Ãø¸é¿¡¼ÀÇ ¼º´ÉÀ» ºÐ¼®ÇÏ¿´´Ù. ÆÄƼ¼Å´× °³¼ö°¡ Áõ°¡ÇÒ¼ö·Ï Áö¿¬½Ã°£ÀÇ ¼º´ÉÀº Çâ»óÇϳª, °ÅÀý·ü°ú ¿¡³ÊÁö ¼Ò¸ð·®ÀÇ ¼º´ÉÀº °¨¼ÒÇÑ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migratin is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases. |
Å°¿öµå(Keyword) |
MEC
Task Partitioning
Task Offloading
Task Migration
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ŽºÅ© ¸¶À̱׷¹À̼Ç
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