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      기회적 포그 컴퓨팅 환경을 고려한 IoT 테스크의 지연된 오프로딩 제공 방안 = Delayed offloading scheme for IoT tasks considering opportunistic fog computing environment

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      https://www.riss.kr/link?id=A107183573

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      다국어 초록 (Multilingual Abstract)

      According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.
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      According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog c...

      According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

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      참고문헌 (Reference)

      1 장경배, "수용가 전력설비 관리를 위한 사물인터넷 플랫폼 연구" 한국사물인터넷학회 5 (5): 103-110, 2019

      2 이동우, "사물인터넷 환경에서의 스마트 공장 추진 분석" 한국사물인터넷학회 5 (5): 1-5, 2019

      3 Q. Fan, "Towards Workload Balancing in Fog Computing Empowered IoT" 7 (7): 253-262, 2018

      4 J. Lee, "Pseudonyms in IPv6 ITS Communications : Use of Pseudonyms, Performance Degradation, and Optimal Pseudonyms Change" 11 (11): 1-7, 2015

      5 N. Fernando, "Opportunistic Fog for IoT : Challenges and Opportunities" 6 (6): 8897-8910, 2019

      6 A. Yousefpour, "On Reducing IoT Service Delay via Fog Offloading" 5 (5): 998-1010, 2018

      7 X. Wang, "Offloading in Internet of Vehicles : A Fog-enabled Real-time Traffic Management System" 14 (14): 4568-4578, 2018

      8 Z. Ning, "Mobile Edge Computing-Enabled Internet of Vehicles : Toward Energy-Efficient Scheduling" 33 (33): 198-205, 2019

      9 P. Mach, "Mobile Edge Computing : A Survey on Architecture and Computation Offloading" 19 (19): 1628-1656, 2017

      10 M. Mukherjee, "Latency-driven Parallel Task Data Offloading in Fog Computing Networks for Industrial Applications" 16 (16): 6050-6058, 2020

      1 장경배, "수용가 전력설비 관리를 위한 사물인터넷 플랫폼 연구" 한국사물인터넷학회 5 (5): 103-110, 2019

      2 이동우, "사물인터넷 환경에서의 스마트 공장 추진 분석" 한국사물인터넷학회 5 (5): 1-5, 2019

      3 Q. Fan, "Towards Workload Balancing in Fog Computing Empowered IoT" 7 (7): 253-262, 2018

      4 J. Lee, "Pseudonyms in IPv6 ITS Communications : Use of Pseudonyms, Performance Degradation, and Optimal Pseudonyms Change" 11 (11): 1-7, 2015

      5 N. Fernando, "Opportunistic Fog for IoT : Challenges and Opportunities" 6 (6): 8897-8910, 2019

      6 A. Yousefpour, "On Reducing IoT Service Delay via Fog Offloading" 5 (5): 998-1010, 2018

      7 X. Wang, "Offloading in Internet of Vehicles : A Fog-enabled Real-time Traffic Management System" 14 (14): 4568-4578, 2018

      8 Z. Ning, "Mobile Edge Computing-Enabled Internet of Vehicles : Toward Energy-Efficient Scheduling" 33 (33): 198-205, 2019

      9 P. Mach, "Mobile Edge Computing : A Survey on Architecture and Computation Offloading" 19 (19): 1628-1656, 2017

      10 M. Mukherjee, "Latency-driven Parallel Task Data Offloading in Fog Computing Networks for Industrial Applications" 16 (16): 6050-6058, 2020

      11 경연웅, "IoT를 고려한 SDN에서 QoS 기반 플로우 핸드오버 관리 방법" 한국사물인터넷학회 6 (6): 45-50, 2020

      12 Y. Liu, "Distributed Task Offloading in Heterogeneous Vehicular Crowd Sensing" 16 (16): 2016

      13 Y. Liu, "Dependency-Aware Task Scheduling in Vehicular Edge Computing" 7 (7): 4961-4971, 2020

      14 M. Li, "Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks with Mobile Edge Computing in Smart City" 67 (67): 9073-9086, 2018

      15 Y. Jiang, "Delay-Aware Task Offloading in Shared Fog Networks" 5 (5): 4945-4956, 2018

      16 Z. Ning, "Deep Reinforcement Learning for Vehicular Edge Computing : An Intelligent Offloading System" 10 (10): 1-24, 2019

      17 J. Ren, "Collaborative Cloud and Edge Computing for Latency Minimization" 68 (68): 5031-5044, 2019

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2024 평가예정 재인증평가 신청대상 (재인증)
      2021-09-27 학술지명변경 한글명 : 한국사물인터넷학회논문지 -> 사물인터넷융복합논문지
      외국어명 : Journal of The Korea Internet of Things Society -> Journal of Internet of Things and Convergence
      KCI등재
      2021-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2019-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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