Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö ÄÄÇ»ÅÍ ¹× Åë½Å½Ã½ºÅÛ
ÇѱÛÁ¦¸ñ(Korean Title) |
Çù·ÂÀûÀÎ Â÷·® ¿§Áö ÄÄÇ»Æÿ¡¼ÀÇ Å½ºÅ© ¸¶À̱׷¹ÀÌ¼Ç |
¿µ¹®Á¦¸ñ(English Title) |
Task Migration in Cooperative Vehicular Edge Computing |
ÀúÀÚ(Author) |
¹®¼º¿ø
ÀÓÀ¯Áø
Sungwon Moon
Yujin Lim
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 10 NO. 12 PP. 0311 ~ 0318 (2021. 12) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù »ç¹°ÀÎÅͳÝÀÇ ±â¼úÀÌ ºü¸£°Ô ¹ßÀüÇÏ¸é¼ ½Ç½Ã°£ ¹× °í¼º´ÉÀÇ Ã³¸®¸¦ ¿ä±¸ÇÏ´Â ¼ºñ½ºµéÀ» À§ÇØ ¸ÖƼ ¾×¼¼½º ¿§Áö ÄÄÇ»ÆÃ(MEC)ÀÌ Â÷¼¼´ë ±â¼ú·Î ºÎ»óÇÏ°í ÀÖ´Ù. Á¦ÇÑÀûÀÎ ¼ºñ½º ¿µ¿ªÀ» °¡Áö´Â MEC »çÀÌ¿¡¼ »ç¿ëÀÚµéÀÇ ÀæÀº À̵¿¼ºÀº MEC ȯ°æ¿¡¼ ´Ù·ï¾ß ÇÒ ¹®Á¦ Áß ÇϳªÀÌ´Ù. º» ³í¹®¿¡¼´Â À̵¿¼ºÀÌ ¸¹Àº Â÷·® ¿§Áö ÄÄÇ»Æà ȯ°æ(VEC)À» °í·ÁÇÏ¿´À¸¸ç, °È ÇнÀ ±â¹ýÀÇ ÀÏÁ¾ÀÎ DQNÀ» ÀÌ¿ëÇÏ¿© ¸¶À̱׷¹ÀÌ¼Ç ¿©ºÎ¿Í ´ë»óÀ» °áÁ¤Çϴ ŽºÅ© ¸¶À̱׷¹ÀÌ¼Ç ±â¹ýÀ» Á¦¾ÈÇÏ¿´´Ù. Á¦¾ÈÇÑ ±â¹ýÀÇ ¸ñÇ¥´Â Â÷·® ¿§Áö ÄÄÇ»Æà ¼¹ö(VECS)µéÀÇ Å¥À× Áö¿¬½Ã°£ÀÇ Â÷À̸¦ ÀÌ¿ëÇÑ ·Îµå ¹ë·±½ÌÀ» °í·ÁÇÏ¿© QoS ¸¸Á·µµ Çâ»ó°ú ½Ã½ºÅÛÀÇ Ã³¸®·®À» Çâ»ó½ÃÅ°´Â °ÍÀÌ´Ù. Á¦¾ÈÇÑ ±â¹ýÀ» ´Ù¸¥ ±â¹ýµé°úÀÇ ¼º´É ºñ±³¸¦ ÅëÇØ QoS ¸¸Á·µµ Ãø¸é¿¡¼ ¾à 14-49%, ¼ºñ½º °ÅÀý·ü Ãø¸é¿¡¼´Â ¾à 14-38%·Î ´õ ÁÁÀº ¼º´ÉÀ» º¸ÀÓÀ» È®ÀÎÇÏ¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
With the rapid development of the Internet of Things(IoT) technology recently, multi-access edge computing(MEC) is emerged as a next-generation technology for real-time and high-performance services. High mobility of users between MECs with limited service areas is considered one of the issues in the MEC environment. In this paper, we consider a vehicle edge computing(VEC) environment which has a high mobility, and propose a task migration algorithm to decide whether or not to migrate and where to migrate using DQN, as a reinforcement learning method. The objective of the proposed algorithm is to improve the system throughput while satisfying QoS(Quality of Service) requirements by minimizing the difference between queueing delays in vehicle edge computing servers(VECSs). The results show that compared to other algorithms, the proposed algorithm achieves approximately 14-49% better QoS satisfaction and approximately 14–38% lower service blocking rate. |
Å°¿öµå(Keyword) |
ŽºÅ© ¸¶À̱׷¹À̼Ç
Â÷·® ¿§Áö ÄÄÇ»ÆÃ
°È ÇнÀ
DQN
Task Migration
Vehicular Edge Computing
Reinforcement Learning
DQN
|
ÆÄÀÏ÷ºÎ |
PDF ´Ù¿î·Îµå
|