Abdulaziz Almalaq

Free Space Optical Communication (FSO) is a promising technology to address wired Data Center Network (DCN) challenges like power consumption, low scalability and flexibility, congestion and cabling. Scholars have developed indirect line-of-sight (LoS) FSO schemes by reflecting the FSO beams via switchable mirrors. These schemes have introduced extra overhead delay to establish indirect LoS links, defined herein as the rack-to-rack FSO link setup process. The purpose of this work is to study and model this setup process with the consideration of the DC workloads. We found that the process involves a sequence of i.i.d random variables that contribute differently to its delay. Also, the process shows a statistical characteristic close to M/M/K. However, the number of FSO links, K, is random with time, which necessitates careful modeling. Finally, the PDF of the process total response time is close to the hypoexponential distribution, and it maintains its main characteristics even with different distributions for the service time.

The economic emission dispatch problem (EEDP) is a nonconvex and nonsmooth multiobjective optimization problem in the power system field. Generally, fuel cost and total emissions of harmful gases are the problem objective functions. The EEDP decision variables are output powers of thermal generating units (TGUs). To make the EEDP problem more practical, valve point loading effects (VPLEs), prohibited operation zones (POZs), and power balance constraints should be included in the problem constraints. In order to solve this complex and constrained EEDP, a new multiobjective optimization technique combining the differential evolution (DE) algorithm and chaos theory is proposed in this study. In this new multiobjective optimization technique, a nondomination sorting principle and a crowding distance calculation are employed to extract an accurate Pareto front. To avoid being trapped in local optima and enhance the conventional DE algorithm, two different chaotic maps are used in its initialization, crossover, and mutation phases instead of random numbers. To overcome difficulties caused by the equality constraint describing the power balance constraint, a slack TGU is defined to compensate for the gap between the total generation and the sum of the system load and total power losses. Then, the optimal power outputs of all thermal units except the slack unit are determined by the suggested optimization technique. To assess the effectiveness and applicability of the proposed method for solving the EEDP, the six-unit and ten-unit systems are used. Moreover, obtained results are compared with other new optimization techniques already developed and tested for the same purpose. The superior performance of the ChMODE is also evaluated by using various metrics such as inverted generational distance (IGD), hyper-volume (HV), spacing metric (SM), and the average satisfactory degree (ASD).