Risk Link Group Research Articles

Robust QoT Assured Resource Allocation in Shared Backup Path Protection Based EONs

Survivability is mission-critical for elastic optical networks (EONs) as they are expected to carry an enormous amount of data. In this paper, we consider the problem of designing shared backup path protection (SBPP) based EON that facilitates the minimum quality-of-transmission (QoT) assured allocation against physical layer impairments (PLIs) under any single link/shared risk link group (SRLG) failure for static and dynamic traffic scenarios. In general, the effect of PLIs on lightpath varies based on the location of failure of a link as it introduces different active working and backup paths. To address these issues in the design of SBPP EON, we formulate a mixed integer linear programming (MILP) based robust optimization framework for static traffic with the objective of minimizing overall fragmentation. In this process, we use the efficient robust bitloading technique for spectrum allocation where each frequency slot of a request is assigned with different modulation format. In addition, we propose novel SBPP-impairment aware (SBPP-IA) algorithm considering the limitations of MILP for larger networks. For this purpose, we introduce a novel sorting technique named most congested working-least congested backup first (MCW-LCBF) to sort the given set of requests. Next, we employ our SBPP-IA algorithm for dynamic traffic scenario and compare it with existing algorithms in terms of different QoT parameters. Further, we guarantee the QoT of existing requests while allocating each new request without reserving any margin. We demonstrated through simulations that our study provides 33.94-41.02% more QoT guaranteed requests compared to existing ones at 70 Tbps traffic load.

Risk propagation analysis of urban rail transit based on network model

Drawing on theories of complex network and accident causality, this paper explores the generation and propagation of urban rail transit (URT) risks, and predicts the propagation path and law of URT risks, aiming to prevent and control operational accidents. Specifically, the URT risks were defined and classified based on the records of accidents and faults. The risk analysis network for the URT was constructed in the light of global safety behavior. Then, state transition measure and coupling measure for risk nodes were proposed. Inspired by the classic dynamics model of infectious disease, the propagation and evolution of risks in the URT were simulated, and the risk link group with high propagation risks was deduced by using the two proposed measures. The proposed risk network was verified through MATLAB simulations on the bogie system of a train and the related risk nodes. The risk link group with high probabilities of risk propagation was successfully derived for the bogie system, an evidence of the feasibility of our dynamics model for URT risks. The research findings lay the basis for risk management and control of the URT systems.