Probabilistic-assured resource provisioning with customizable hybrid isolation for vertical industrial slicing
Guo, Qize; Gu, Rentao; Yu, Hao; Taleb, Tarik; Ji, Yuefeng (2022-11-07)
Q. Guo, R. Gu, H. Yu, T. Taleb and Y. Ji, "Probabilistic-Assured Resource Provisioning With Customizable Hybrid Isolation for Vertical Industrial Slicing," in IEEE Transactions on Network and Service Management, vol. 20, no. 2, pp. 1660-1675, June 2023, doi: 10.1109/TNSM.2022.3219865.
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https://urn.fi/URN:NBN:fi-fe20231009139352
Tiivistelmä
Abstract
With the increasing demand of network slices in vertical industries, slice resource provisioning in transport networks has encountered two challenges, one is efficient slice resource provisioning in the presence of traffic uncertainty of slices, and another is flexible slice resource isolation for customizable isolation needs. In this paper, we propose an innovative flexible hybrid isolation model to support any customized resource isolation from complete isolation to full sharing, and solve the slice resource provisioning problem named Hybrid Slicing Minimum Bandwidth (HSMB) by considering traffic prediction error to mitigate the negative impact of traffic uncertainty in the proposed model. After analyzing the HSMB problem, 1) we first try to solve the problem in steps and decompose the HSMB problem into grouping sub-problem and adjusting sub-problem, 2) we then propose a low-complexity dynamic programming grouping algorithm and a fast iterative adjustment algorithm for the two sub-problems based on probabilistic feature-based analysis, 3) we combine the algorithms of the two sub-problems and further propose a linking algorithm for the potential insufficient resource dilemma and high computational complexity dilemma to improve the efficiency of the solution. The numerical results show that the proposed flexible hybrid isolation model with different factors can facilitate flexible slice isolation with customized isolation demands, while the proposed algorithm can realize efficient slice resource provisioning with a probabilistic guarantee. The comparison result shows the proposed algorithms outperform the other benchmark algorithms.
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