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- W3189390976 abstract "This paper proposes an optimization model to derive the resilient virtual network function allocation in service function chains aiming to reduce the recovery time during the migrations from the primary functions to backup functions. We consider k-fault-tolerance assurance and satisfy the service requirements under different error patterns in this model. The allocation provided by the proposed model ensures that the processing ability satisfies the requirements even though there are k failed nodes in the network. Diversity splits a single VNF into a pool of replicas with different specifications. The diversity of both primary and backup functions are considered. Redundancy is used for recovering the failed functions. We formulate the proposed model as a mixed integer linear programming problem to select suitable replicas from the pools of replicas and decide the locations of these replicas for both primary and backup functions. The objective of the proposed model is to minimize the sum of the maximum recovery time among functions under all possible failure patterns which have k node failures. The numerical results show that the proposed model reduces the recovery times of VNFs with ensuring the resiliency of the functions compared with baseline models in the examined cases. We give some methods to improve the maximum resiliency at last." @default.
- W3189390976 created "2021-08-16" @default.
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- W3189390976 date "2021-06-01" @default.
- W3189390976 modified "2023-10-17" @default.
- W3189390976 title "Resilient Resource Allocation Model in Service Function Chains with Diversity and Redundancy" @default.
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- W3189390976 doi "https://doi.org/10.1109/icc42927.2021.9500867" @default.
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