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A novel structure for thin-film solar cells is simulated with the purpose of maximizing the absorption of light in the active layer and of reducing the parasitic absorption in other layers. In the proposed structure, the active layer is formed from an amorphous silicon thin film sandwiched between silicon nanowires from above and photonic crystal structures from below. The upper electrical contact consists of an indium tin oxide layer, which serves also as an antireflection coating. A metal backreflector works additionally as the other contact. The simulation was done using a new reliable, efficient and generic optoelectronic approach. The suggested multiscale simulation model integrates the finite-difference time-domain algorithm used in solving Maxwell's equation in three dimensions with a commercial simulation platform based on the finite element method for carrier transport modeling. The absorption profile, the external quantum efficient, and the power conversion efficiency of the suggested solar cell are calculated. A noticeable enhancement is found in all the characteristics of the novel structure with an estimated 32% increase in the total conversion efficiency over a cell without any light trapping mechanisms.

The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.

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