- Volume 6 Issue 4
DOI QR Code
Delayed offloading scheme for IoT tasks considering opportunistic fog computing environment
기회적 포그 컴퓨팅 환경을 고려한 IoT 테스크의 지연된 오프로딩 제공 방안
- Kyung, Yeunwoong (Division of Computer Engineering, Hanshin University)
- 경연웅 (한신대학교 컴퓨터공학부)
- Received : 2020.11.14
- Accepted : 2020.12.18
- Published : 2020.12.31
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.
- D.W.Lee, K.Cho, and S.H.Lee, "Analysis on Smart Factory in IoT Environment," Journal of The Korea Internet of Things Society, Vol.5, No.2, pp.1-5, 2019. https://doi.org/10.1016/j.iot.2018.11.001
- K.B.Jan,g, "A study on IoT platform for private electrical facilities management," Journal of The Korea Internet of Things Society, Vol.5, No.2, pp.103-110, 2019. https://doi.org/10.20465/KIOTS.2019.5.2.103
- Y.W.Kyung and T.K.Kim, "Flow Handover Management Scheme based on QoS in SDN Considering IoT," Journal of The Korea Internet of Things Society, Vol.6, No.2, pp.45-50 2020 https://doi.org/10.20465/KIOTS.2020.6.2.045
- P.Mach and Z.Becvar, "Mobile Edge Computing: A Survey on Architecture and Computation Offloading," IEEE Communications Surveys & Tutorials, Vol.19, No.3, pp.1628-1656, 2017. https://doi.org/10.1109/COMST.2017.2682318
- M.Mukherjee, S.Kumar, C.X.Mavromoustakis, G.Mastorakis, R.Matam, V.Kumar, and Q.Zhang, "Latency-driven Parallel Task Data Offloading in Fog Computing Networks for Industrial Applications," IEEE Transactions on Industrial Informatics, Vol.16, No.9, pp.6050-6058, 2020. https://doi.org/10.1109/TII.2019.2957129
- Y.Jiang and D.H.K.Tsang, "Delay-Aware Task Offloading in Shared Fog Networks," IEEE Internet of Things Journal, Vol.5, No.6, pp.4945-4956, 2018. https://doi.org/10.1109/JIOT.2018.2880250
- A.Yousefpour, G.Ishigaki, R.Gour, and J.P.Jue, "On Reducing IoT Service Delay via Fog Offloading," IEEE Internet of Things Journal, Vol.5, No.2, pp.998-1010, 2018. https://doi.org/10.1109/JIOT.2017.2788802
- J.Ren, G.Yu, Y.He, and G.Y.Li, "Collaborative Cloud and Edge Computing for Latency Minimization," IEEE Transactions on Vehicular Technology, Vol.68, No.5, pp.5031-5044, 2019. https://doi.org/10.1109/TVT.2019.2904244
- N.Fernando, S.W.Loke, I.Avazpour, F.Chen, A.B.Abkenar, and A.Ibrahim, "Opportunistic Fog for IoT: Challenges and Opportunities," IEEE Internet of Things Journal, Vol.6, No.5, pp.8897-8910, 2019. https://doi.org/10.1109/JIOT.2019.2924182
- Y.Liu, S.Wang, Q.Zhao, S.Du, A.Zhou, X.Ma, and F.Yang, "Dependency-Aware Task Scheduling in Vehicular Edge Computing," IEEE Internet of Things Journal, Vol.7, No.6, pp.4961-4971, 2020. https://doi.org/10.1109/JIOT.2020.2972041
- Z.Ning, J.Juang, X.Wang, J.J.P.C.Rodrigues, and L.Guo, "Mobile Edge Computing-Enabled Internet of Vehicles: Toward Energy-Efficient Scheduling," IEEE Network, Vol.33, No.5, pp.198-205, 2019. https://doi.org/10.1109/MNET.2019.1800309
- X.Wang, Z.Ning, and L.Wang, "Offloading in Internet of Vehicles: A Fog-enabled Real-time Traffic Management System," IEEE Transactions on Industrial Informatics" Vol.14, No.10, pp.4568-4578, 2018. https://doi.org/10.1109/TII.2018.2816590
- Z.Ning, P.Dong, X.Wang, J.J.P.C.Rodrigues, and F.Xia, "Deep Reinforcement Learning for Vehicular Edge Computing: An Intelligent Offloading System," ACM Transactions on Intelligent Systems and Technology, Vol.10, No.6, pp.1-24, 2019.
- M.Li, P.Si, and Y.Zhang, "Delay-Tolerant Data Traffic to Software-Defined Vehicular Networks with Mobile Edge Computing in Smart City," IEEE Transactions on Vehicular Technology, Vol.67, No.10, pp.9073-9086, 2018. https://doi.org/10.1109/TVT.2018.2865211
- Y.Liu, W.Wang, Y.Ma, Z.Yang, and F.Yu, "Distributed Task Offloading in Heterogeneous Vehicular Crowd Sensing," MDPI Sensors, Vo.16, No.7, 2016.
- J.Lee, G.Lee, and S.Pack, "Pseudonyms in IPv6 ITS Communications: Use of Pseudonyms, Performance Degradation, and Optimal Pseudonyms Change," International Journal of Distributed Sensor Networks, Vol.11, No.5, pp.1-7, 2015.
- Q.Fan and N.Ansari, "Towards Workload Balancing in Fog Computing Empowered IoT," IEEE Transactions on Network Service and Engineering, Vol.7, No.1, pp.253-262, 2018.