Unavailability-Aware Backup Allocation Model for Middleboxes with Two-Stage Shared Protection

Nozomi, Kita; He, Fujun; Oki, Eiji

doi:10.1109/netsoft54395.2022.9844095

Cited by 3 publications

(6 citation statements)

References 21 publications

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“…The works in earlier studies [13][14][15][16][17][18][19][20][21][22][23][24] addressed the SFC availability considering the failure of VNF.…”

Section: Availability Of Sfcmentioning

confidence: 99%

“…The availability-aware VNF placement problem was studied in previous work. [13][14][15][16][17][18][19][20] The work in Fan et al 13 presented an optimal SFC mapping problem considering availability and an online algorithm to minimize the consumption of physical resources while guaranteeing high availability requirements through the use redundant models with three pattern backups. The work in Zhang et al 14 studied the resource-aware backup allocation problem considering heterogeneous resource demands for each VNF in two scenarios when adopting dedicated or shared protection.…”

Section: Availability Of Sfcmentioning

confidence: 99%

“…Utilizing a game approach for optimization, the model surpasses two baseline methods and an existing model, in relation to deployment cost, and exhibits scalability as the problem size increased. The work in previous studies 19,20 introduced a shared protection model in which the middleboxes are backed up by two-stage servers and a heuristic algorithm based on simulated annealing to achieve lower unavailability than conventional single-stage backup methods.…”

Section: Availability Of Sfcmentioning

confidence: 99%

“…In this paper, we consider the failure of the physical resources of the server and the failure of the software for virtualization as well as the failure of the VNF instance in our availability calculations. These studies [13][14][15][16][17][18][19][20][21][22][23][24] considered that each VNF instance takes only two states, either active or failed, and a VNF is available when there is at least one corresponding active VNF instance. In contrast, this paper considers that a VNF takes different processing capacities depending on the number of VNF instances in the active state with distributed processing as its background: The processing capacity of a VNF is the sum of the processing capacities of the active VNF instances.…”

Section: Availability Of Sfcmentioning

confidence: 99%

“…jK 0 j is equal to the number of possible processing capacity values of SFC and is less than or equal to jKj. By using the set of pairs ðp k 0 , g SFC,k 0 Þ obtained from terms in u-function (19) and using ( 13), the steady-state availability of SFC, A SFC ðwÞ, can be calculated as follows:…”

Section: Mugf For Sfcmentioning

confidence: 99%

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Availability‐aware virtual network function placement based on multidimensional universal generating functions

Arakawa,

Oki

2023

Int J Network Mgmt

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Network function virtualization (NFV) implements network functions as software, which enables flexible, resource‐efficient, and rapid provision of network services. In NFV, network services are realized by the service function chain (SFC), which is a chain of virtual network functions (VNFs) linked in the proper order. Both availability and deployment cost are key concerns for network operators providing network services as SFC. This paper proposes a flexible VNF placement model on a per‐VNF instance basis that minimizes deployment costs while satisfying availability requirements that may be placed on SFC. This paper uses a multidimensional universal generating function (MUGF) method, which is a multistate system analysis method, to compute the availability of a multistate SFC system with multiple VNFs coexisting on a server. The MUGF method calculates the performance of the entire SFC by combining the performance of servers as determined by applying a continuous‐time Markov chain. To reduce the time to compute the SFC availability, we introduce operators to be applied to MUGF and develop an availability computing method. In addition, a heuristic algorithm for determining VNF placement targeting the lowest deployment cost possible while meeting availability requirements is presented. Numerical results show that the proposed model obtains VNF placement with lower cost than the conventional model in all examined cases. The proposed model achieves VNF placement at 58.5%–75.0% of the deployment cost of the conventional model for the same SFC availability requirements.

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