Á¤º¸°úÇÐȸ ÄÄÇ»ÆÃÀÇ ½ÇÁ¦ ³í¹®Áö (KIISE Transactions on Computing Practices)
Current Result Document : 4 / 4
ÇѱÛÁ¦¸ñ(Korean Title) |
MEC Áö¿ø Â÷·® ³×Æ®¿öÅ©¿¡¼ÀÇ °ÔÀÓ ÀÌ·Ð ±â¹Ý µ¿Àû °è»ê ¿ÀÇÁ·Îµù ¹æ¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Game Theory Based Dynamic Computation Offloading in MEC-Enabled Vehicular Networks |
ÀúÀÚ(Author) |
¿ÍÄ«½º ¿ì¸£ ¶ó¸¸
ÀÌ°¡¿ø
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È£¾À ¿¥µð µô·Î¿Í¸£
ÅÏÁö³ª ¼Öź¾Æ
Md. Delowar Hossain
Tangina Sultana
Waqas ur Rahman
Ga-Won Lee
Eui-Nam Huh
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¿ø¹®¼ö·Ïó(Citation) |
VOL 49 NO. 05 PP. 0216 ~ 0224 (2022. 05) |
Çѱ۳»¿ë (Korean Abstract) |
Â÷·® ¿§Áö ÄÄÇ»ÆÃ(VEC)Àº Â÷·® ³×Æ®¿öÅ©(VN)¿¡ ±ÙÁ¢ÇÑ ¼ºñ½º¸¦ °¡Á®¿À±â À§ÇÑ »õ·Î¿î Æз¯´ÙÀÓÀ¸·Î °¢±¤¹Þ°í ÀÖÀ¸³ª, °úºÎÇÏ ¹®Á¦¿Í Â÷·®ÀÇ °íÀ̵¿¼ºÀ¸·Î ÀÎÇØ ¿ÀÇÁ·Îµå µÈ ÀÛ¾÷À» ó¸®ÇÒ À§Ä¡ ½Äº°¿¡ ÀÖ¾î ¸¹Àº ¾î·Á¿òÀÌ ÀÖ¾î ´Ù¾çÇÑ ¹æ¹ýÀÌ ¿¬±¸µÇ°í ÀÖ´Ù. ÀÌ·¯ÇÑ ¹®Á¦¸¦ ÇØ°áÇϱâ À§ÇØ º» ³í¹®¿¡¼´Â ´ÙÁß Á¢¼Ó ¿¡Áö ÄÄÇ»ÆÃ(MEC) Áö¿ø Â÷·® ³×Æ®¿öÅ©¿¡¼ °ÔÀÓ ÀÌ·Ð ±â¹ÝÀÇ µ¿Àû °è»ê ¿ÀÇÁ·Îµù (GDCO) ¹æ¹ýÀ» Á¦¾ÈÇÏ°íÀÚ ÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ¹ýÀº °¢ Â÷·®ÀÇ È¿À²À» ±Ø´ëÈÇÒ ¼ö ÀÖµµ·Ï ƯÁ¤ Á¶°Ç¿¡¼ ÀÛ¾÷ ¿ÀÇÁ·Îµù È®·üÀ» µ¿ÀûÀ¸·Î Á¶Á¤ÇÏ´Â °ÍÀ¸·Î, Â÷·®ÀÇ ´Ù¾çÇÑ ¼Óµµ¸¦ °í·ÁÇÏ¿© À̵¿¼º ¸ðµ¨ ¼³°è¿¡ ¹Ý¿µÇÏ¿´´Ù. ½Ã¹Ä·¹ÀÌ¼Ç °á°ú, Á¦¾È ¹æ½ÄÀÌ LRC(Áö¿ª ³ëº¯±âÁö±¹ ÄÄÇ»ÆÃ) ¹× ¹«ÀÛÀ§ ¿ÀÇÁ·Îµù¿¡ ºñÇØ 76.5%¿Í 79.3%ÀÇ ÀÛ¾÷ ½ÇÆÐÀ²À» ÁÙ¿© ¼º´ÉÀÌ Çâ»óµÊÀ» È®ÀÎÇÏ¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
Vehicular edge computing (VEC) provides a new paradigm for fetching services in close proximity to vehicular networks (VNs). However, due to the problem of overloading and the high mobility of vehicles, VEC experiences many challenges in identifying the location for processing the offloaded task. Therefore, to tackle these issues, we proposed a game theory-based dynamic computation offloading (GDCO) scheme in multi-access edge computing (MEC)-enabled vehicular networks. Our proposed strategy can dynamically adjust the task off loading probability to maximize the utility for each vehicle under certain conditions. Moreover, for real-life scenarios, we considered vehicle movements at various speeds when designing the mobility model. The simulation results confirmed that our proposed scheme fulfilled the performance gurarantees to reduce the task failure rates by almost 76.5% and 79.3% compared to local road-side unit computing (LRC) and random offloading schemes, respectively. |
Å°¿öµå(Keyword) |
°è»ê ¿ÀÇÁ·Îµù
Â÷·® ³×Æ®¿öÅ©
°ÔÀÓ ÀÌ·Ð
Â÷·® ¿§Áö ÄÄÇ»ÆÃ
computation offloading
vehicular networks
game theory
vehicular edge computing
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