Incentive Mechanism and Resource Allocation for Collaborative Task Offloading in Energy-Efficient Mobile Edge Computing

Pu, Xumin; Lei, T.C.; Wen, Wanli; Feng, Wenting; Wang, Zhengqiang; Chen, Qianbin; Jin, Shi

doi:10.1109/tvt.2023.3274513

Cited by 13 publications

(1 citation statement)

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“…The massive amount of data generated by the Industrial Internet of Things (IIoT) poses significant challenges to data centers and cloud computing. To address this problem, edge computing [ 7 , 8 , 9 ] emerged. Edge computing shifts the tasks of data processing and analysis from centralized data centers to the edge of the network, enabling time-critical data to be analysed at the source.…”

Section: Introductionmentioning

confidence: 99%

Enhanced FRER Mechanism in Time-Sensitive Networking for Reliable Edge Computing

Hu,

Cai,

Wang

et al. 2024

Sensors

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Time-Sensitive Networking (TSN) and edge computing are promising networking technologies for the future of the Industrial Internet. TSN provides a reliable and deterministic low-latency communication service for edge computing. The Frame Replication and Elimination for Reliability (FRER) mechanism is important for improving the network reliability of TSN. It achieves high reliability by transmitting identical frames in parallel on two disjoint paths, while eliminating duplicated frames at the destination node. However, there are two problems with the FRER mechanism. One problem is that it does not consider the path reliability, and the other one is that it is difficult to find two completely disjoint path pairs in some cases. To solve the above problems, this paper proposes a method to find edge-disjoint path pairs considering path reliability for FRER in TSN. The method includes two parts: one is building a reliability model for paths, and the other one is computing a working path and a redundant path with the Edge-Disjoint Path Pairs Selection (EDPPS) algorithm. Theoretical and simulation results show that the proposed method effectively improves path reliability while reducing the delay jitter of frames. Compared with the traditional FRER mechanism, the proposed method reduces delay jitter by 15.6% when the network load is 0.9.

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Section: Introductionmentioning

confidence: 99%