Next-generation optical metro-access networks are
expected to support end-to-end virtual network slices for critical
5G services. However, disasters affecting physical infrastructures
upon which network slices are mapped can cause significant
disruption in these services. Operators can deploy recovery units
or trucks to restore services based on slice requirements. In
this study, we investigate the problem of slice-aware service
restoration in metro-access networks with specialized recovery
trucks to restore services after a disaster failure. We model
the problem based on classical vehicle-routing problem to find
optimal routes for recovery trucks to failure sites to provide
temporary backup service until the network components are repaired.
Our proposed slice-aware service-restoration approach is
formulated as a mixed integer linear program with the objective
to minimize penalty of service disruption across different network
slices.We compare our slice-aware approach with a slice-unaware
approach and show that our proposed approach can achieve
significant reduction in service-disruption penalty
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Population-Aware Relay Placement for Wireless Multi-Hop Based Network Disaster Recovery
Network disaster recovery is one of the greatest concerns for Mobile Network Operators (MNOs) and first responders during large-scale natural disasters such as earth- quakes. In many recent studies, wireless multi-hop networking has been demonstrated as an effective technique to quickly and efficiently extend the network coverage during disasters. In this paper, we specifically address the network deployment problem by proposing the Population-Aware Relay Placement (PARP) solution, which seeks the efficient deployment of a limited number of relays such that population coverage is maximized in the scenario of network disaster recovery. We provide a graph-based modeling and prove its NP-hardness accordingly. In order to efficiently solve this problem, we propose a heuristic solution, which is constructed in two steps. We first design a simple algorithm based on a disk graph to determine the Steiner locations, which is the biggest challenge in this problem. Then, we formulate the problem as an integer programming problem, which is inspired by the formulation of Prize-Collecting Steiner Tree (PCST). Thus, the integer problem is solved by exploring the similarity of the existing algorithm for PCST. To evaluate the proposed solution extensively, we present numerical results on both real-world and random scenarios, which validate the effectiveness of the proposed solution and show substantial improvement by comparing to the previous one.
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- Award ID(s):
- 1461886
- NSF-PAR ID:
- 10098763
- Date Published:
- Journal Name:
- GLOBECOM 2017 - 2017 IEEE Global Communications Conference
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/GLOCOM.2017.8253922
