GoS-Aware Optimization of a Multi-Layered Network for Cost Effectiveness and Fault Tolerance

This paper introduces two new algorithms for fault-tolerant design of multi-layered networks, both of which extend the previously published multi-layered market algorithm (MMA), by including provision of additional resources to be used during network failure events. The new algorithms are called resilient MMA (RMMA) and failure-traffic MMA (FTMMA). RMMA runs MMA iteratively and independently for each failure scenario. FTMMA treats each failure event as a type of traffic, which enables more efficient sharing of network resources. Both RMMA and FTMMA consider a range of single physical link failures and aim to maximize earnings before interest and tax (EBIT). The costs considered in the EBIT evaluation include amortized capital and operational expenditures and penalties (compensation to the customers when the service is degraded). They both focus on optimizing resource provisioning, in particular, capacity assignment, for fault-tolerant and cost-effective design of multi-layered networks. The novel aspects of RMMA and FTMMA include the incorporation of variable bit rate traffic streams in fault-tolerant multilayered network design, together with the aim to maximize EBIT. RMMA and FTMMA are validated by comparing designs with those produced by an integer linear programming benchmark for small-size networks. Numerical results show that FTMMA can more efficiently allocate capacity for failures by sharing these resources across different failure events.

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Publication Details

Journal
IEEE Transactions on Network and Service Management
Published
2025-06-09
DOI
https://doi.org/10.1109/tnsm.2025.3577567
Citations
1
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
1.49

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article

GoS-Aware Optimization of a Multi-Layered Network for Cost Effectiveness and Fault Tolerance

Moshe Zukerman, Ron Addie, Chang Xing
1 citations
IEEE Transactions on Network and Service Management
Software-Defined Networks and 5G
1.49
article

GoS-Aware Optimization of a Multi-Layered Network for Cost Effectiveness and Fault Tolerance

Moshe Zukerman, Ron Addie, Chang Xing
article en
1 citations

Abstract

This paper introduces two new algorithms for fault-tolerant design of multi-layered networks, both of which extend the previously published multi-layered market algorithm (MMA), by including provision of additional resources to be used during network failure events. The new algorithms are called resilient MMA (RMMA) and failure-traffic MMA (FTMMA). RMMA runs MMA iteratively and independently for each failure scenario. FTMMA treats each failure event as a type of traffic, which enables more efficient sharing of network resources. Both RMMA and FTMMA consider a range of single physical link failures and aim to maximize earnings before interest and tax (EBIT). The costs considered in the EBIT evaluation include amortized capital and operational expenditures and penalties (compensation to the customers when the service is degraded). They both focus on optimizing resource provisioning, in particular, capacity assignment, for fault-tolerant and cost-effective design of multi-layered networks. The novel aspects of RMMA and FTMMA include the incorporation of variable bit rate traffic streams in fault-tolerant multilayered network design, together with the aim to maximize EBIT. RMMA and FTMMA are validated by comparing designs with those produced by an integer linear programming benchmark for small-size networks. Numerical results show that FTMMA can more efficiently allocate capacity for failures by sharing these resources across different failure events.

IEEE Transactions on Network and Service ManagementVol. 22(5)
City University of Hong Kong (HK), University of Southern Queensland (AU)
Research Grants Council, University Grants Committee
Openalex Percentile: Top 16%
Software-Defined Networks and 5G
1.49
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GoS-Aware Optimization of a Multi-Layered Network for Cost Effectiveness and Fault Tolerance — Moshe Zukerman, Ron Addie, et al. · IEEE Transactions on Network and Service Management (2025) | TGRS Research Map | TGRS