## 2 Related Works  
The C+L-EONs have gained popularity due to the significant surge in network traffic. The related work is summarized in three aspects: (1) ISRS-based QoT estimation, (2) spectrum fragmentation awareness, and (3) network survivability. Exploring the impact of ISRS on QoT estimation is a crucial research issue in C+L-EONs. Several studies focused on the QoT estimation under the influence of NLI jointly with the ISRS, and they demonstrated the significant role played by transmission power and ISRS in multi-band (MB) systems [11, 12, 13]. [PERSON] et al. [14] comprehensively consider the ISRS, self-phase modulation (SPM), cross-phase modulation (XPM), and amplified spontaneous emission (ASE) noise in the QoT estimation process and establish the optical signal-to-noise ratio (OSNR) measurement model. The authors investigate the influence of various modulation formats on the QoT assessment process within the MB system and propose assessment methods that consider modulation formats dependently [15, 16]. [PERSON] et al. [17] demonstrate that as network load and resource utilization increase, the accuracy of the Gaussian noise (GN), and generalized Gaussian noise (GGN) models decreases. Utilizing a triangular approximation of the Raman gain, [PERSON] et al. [18] develop an enhanced Christodoulides-Zirngibl (ECZ) SRS model and apply it within the GN model framework. The findings reveal that OSNR can serve as a primary QoT parameter for accurate assessment. Then, [PERSON] et al. [19] address the physical layer impairment issue in multi-band elastic optical networks from the perspectives of routing selection and spectrum allocation, proposing a resource allocation algorithm for impairment reduction. The results demonstrate that, compared to other studies, this work effectively alleviates the impact of physical layer impairments on signal transmission quality. The aforementioned work only takes into account the impact of physical layer impairments on signal quality in the network without addressing the spectrum fragmentation and the network survivability issue. Spectrum fragmentation-aware algorithms have been extensively studied in recent years. [PERSON] et al. [20] propose an impairment and fragmentation-aware dynamic resource allocation algorithm for C+L-EONs using Q-learning, which integrates the effects of network fragmentation and link availability. [PERSON] et al. [21] apply a machine learning approach to propose a preventive fragmentation sorting method for C+L-EONs. This not only dramatically improves the network resource utilization but also ensures the QoT of the request. [PERSON] et al. [22] consider the spectrum fragmentation issue and the survivability issue in EONs simultaneously and adopt a path-switching defragmentation scheme, which realizes the route redirection of the backup path by reallocating the backup path FSs. The results show that the scheme can improve network resource utilization while ensuring network survivability. In terms of network survivability, [PERSON] et al. [23] consider the physical layer impairments suffered by the primary and backup paths of requests before and after network failures in EONs and propose a highly robust resource allocation algorithm to guarantee the QoT on the primary and backup paths of requests. In [24], the MB-space division multiplexing (SDM)-EONs scenario is explored, and a band division protection scheme is proposed to enhance OSNR by assigning resources for both primary and backup paths to distinct bands. To mitigate physical layer impairments and enhance the SNR, a band partitioning protection scheme is proposed, allocating resources for the primary and backup paths to distinct bands. [PERSON] et al. [25] consider the survivability issue and the spectrum fragmentation problem in the SDM-EONs jointly and design a fragmentation-aware fragmentation metric to reduce network fragmentation. In addition, a routing strategy utilizing multipath routing is introduced to guarantee the survivability requirements of requests. [PERSON] et al.