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Large-scale carrier networks are fundamental ICT infrastructures that support future 5G/6G services, and their resilience is a primary societal concern. Differently from single-carrier networks (in which one carrier owns multiple networks), in multi-carrier network ecosystems (in which the networks in the fields are operated by different carriers), cooperation among such different carriers is crucial to achieve resilience against large-scale failures. However, such cooperation is challenging since carriers may not disclose confidential information, e.g., detailed resource availability. In this study, we investigate how to perform carrier cooperative recovery in the case of large-scale failures/disasters. We propose two-stage carrier-carrier cooperative recovery planning by incorporating a coordinated scheduling for faster recovery. Through numerical evaluation, we confirm the potential benefit of carrier cooperation in terms of both recovery time and recovery cost reduction.
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This content will become publicly available on May 6, 2025
A Distributed-Ledger-based Multi-Entity Cooperation Platform for Network-Cloud Recovery
Cooperation among telecom carriers and datacenter (DC) providers (DCPs) is essential to ensure resiliency of network-cloud ecosystems. To enable efficient cooperative recovery in case of resource crunch, e.g., due to traffic congestion or network failures, we previously studied several frameworks for cooperative recovery among different stakeholders (e.g., telecom carriers and DCPs). Now, we introduce a novel Multi-entity Cooperation Platform (MCP) for implementing cooperative recovery planning, to achieve efficient use of carriers’ valuable optical-network resources during recovery. We adopt a Distributed Ledger Technology (DLT) that ensures decentralized and tamper-proof information exchange among stakeholders to achieve open and fair cooperation. To support diverse types of cooperation, we develop a state machine representing the MCP operation and define state transitions associated to stakeholders’ cooperation within the state machine. Moreover, we propose a signaling system in MCP to ensure simple and reliable state transitions for stakeholders during the cooperative recovery planning in large ecosystems. We experimentally demonstrate a proof-of-concept DLT-based MCP on a testbed. We showcase a DCP-carrier cooperative planning process, showing the flexibility of the proposed MCP to support diverse types of cooperation.
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- Award ID(s):
- 2210384
- PAR ID:
- 10518559
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- International Conference on Optical Network Design and Modelling
- ISSN:
- 2995-0678
- Format(s):
- Medium: X
- Location:
- Madrid, Spain
- Sponsoring Org:
- National Science Foundation
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