Fault-Tolerant Embedding Algorithm for Node Failure in Airborne Tactical Network Virtualization

Autor: Jingcheng Miao, Na Lv, Qi Gao, Kefan Chen, Xiang Wang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: IEEE Access, Vol 10, Pp 60558-60571 (2022)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2022.3180744
Popis: Airborne tactical networks (ATNs) are driving the promising development of Internet of battle Things (IoBT) by enabling efficient information sharing, which is impeded by the network ossification problem due to the tightly coupled network architecture. As a solution, network virtualization (NV) can solve the ossification problem by breaking the tight coupling between applications and network infrastructure for ATNs. With complex interference and malicious attacks, the application of NV is challenged by network failures when instantiating virtual networks on a shared substrate network, which is known as survivable virtual network embedding (SVNE). However, existing SVNE algorithms, mostly designed for wired networks, are not necessarily optimal for the virtualization of ATNs due to the complex wireless interference. To this end, a fault-tolerant SVNE algorithm, termed SVNE-FT, is proposed to recover virtual networks from single node failure (end or switching node failure) under the complex wireless interference. To end node failure, SVNE-FT adopts a novel node ranking approach to select reliable substrate nodes for virtual nodes and remaps the failed virtual nodes by releasing part of the substrate paths to improve the resource utilization. In addition, to switching node failure, it adopts the improved pre-configured cycle (p-Cycle) technology to augment the reliable link mapping with differentiated p-Cycles that protect switching node and reduce the resource consumption of backups. Numerical simulation results reveal that SVNE-FT outperforms typical and latest heuristic SVNE algorithms under the complex interference of ATNs. For instance, average acceptance ratio of virtual networks improves at least 12%.
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