Network survivability endeavors to ensure the uninterrupted provisioning of services by the network operators in case of a disaster event. Studies and news reports show that network failures caused by physical attacks and natural disasters have significant impacts on the optical networks. Such network failures may lead to a section of a network to cease to function, resulting in non-availability of services and may increase the congestion within the rest of the network. Therefore, fault tolerant and disaster-resilient optical networks have grasped the attention of the research community and have been a critical concern in network studies during the last decade. Several studies on protection and restoration techniques have been conducted to address the network component failures. This study reviews related previous research studies to critically discuss the issues regarding protection, restoration, cascading failures, disaster-based failures, and congestion-aware routing. We have also focused on the problem of simultaneous cascading failures (which may disturb the data traffic within a layer or disrupt the services at upper layers) along with their mitigating techniques, and disaster-aware network survivability. Since traffic floods and network congestion are pertinent problems, they have therefore been discussed in a separate section. In the end, we have highlighted some open issues in the disaster-resilient network survivability for research challenges and discussed them along with their possible solutions.

A supervised machine learning (ML) algorithm is proposed for measuring refractive index (RI) values both below and above the RI of the fiber material using a multimode interference (MMI) fiber sensor. The sensor is constructed by splicing a coreless multimode fiber (CMF) segment between two single-mode fiber (SMF) leads. Measurement of low and high RI regimes is accomplished through the Decision Tree (DT) regression algorithm. The trained model algorithm demonstrates a wide dynamic range in RI measurement, covering the ranges of 1.30 to 1.39 (low RI regime) and 1.46 to 1.55 (high RI regime) without any RI ambiguity, achieving model accuracy of 99.77%. The guided and leaky modes mechanisms within the all-silica-based structure of the CMF are fundamentally insensitive to temperature, making it highly practical for deployment in conditions with varying temperatures without the need for any compensating scheme.

Sub-terahertz (sub-THz) waves, operating in the 0.1-1 THz band, offer significant potential for next-generation 6G systems. These systems stand to benefit from photonic technologies that enable terabits-per-second communication with low latency and high throughput. This paper introduced, for the first time, a semiconductor optical amplifier (SOA) as a fast and reliable photonic-based technique for sub-THz wavelength conversion in fiber-based networks. The wavelength conversion leveraged nonlinear phenomena in the SOA, including cross-gain modulation, self-phase modulation, and four-wave mixing effects. Numerical simulations demonstrated an all-optical wavelength conversion capable of handling 100-GHz sub-THz signals with 16-ary quadrature amplitude modulation formats, achieving a data rate switching of 5 Gbps. Key system parameters were optimized, resulting in a 28.7 dB suppression ratio for the generated optical single sideband (OSSB) signal. Additionally, a proof-of-concept laboratory experiment validated the THz signal-switching concept. The proposed system incorporated a hybrid fiber/wireless channel and utilized various measures for performance evaluation.