A novel hybrid plasmonic waveguide based on a guided Bloch surface polariton structure is proposed and investigated.This hybrid waveguide overcomes the weak confinement in the Bloch surface polariton structure caused by the diffraction limitation.By introducing a metal stripe near the dielectric ridge located on the periodic multilayer structure that is designed to support a TM polarized Bloch surface polariton,a sub-wavelength scale electric field confinement is realized.The coupling of the Bloch surface polariton and the surface plasmon polariton results in a strong field distribution within the gap between the metal stripe and the dielectric ridge.The variation of the characteristic of the hybrid mode is revealed via tuning the height of the ridge and the coupling distance.Sub-wavelength scale mode size is realized as well as a propagation length of about 100μm.
WAN YuHangZHENG ZhengSHI XiaoGangBIAN YuShengLIU JianSheng
With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network （ARN）, we propose an effective local dynamic routing strategy in this paper. Several factors, such as the rout- ing distance, the geographical distance and the real-time local traffic, are taken into consideration. When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing （SPR） strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network （CARN） is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.
In this paper, a four-dimensional coordinated path planning algorithm for multiple UAVs is proposed, in which time variable is taken into account for each UAV as well as collision free and obstacle avoidance. A Spatial Refined Voting Mechanism(SRVM) is designed for standard Particle Swarm Optimization(PSO) to overcome the defects of local optimal and slow convergence.For each generation candidate particle positions are recorded and an adaptive cube is formed with own adaptive side length to indicate occupied regions. Then space voting begins and is sorted based on voting results, whose centers with bigger voting counts are seen as sub-optimal positions. The average of all particles of corresponding dimensions are calculated as the refined solutions. A time coordination method is developed by generating specified candidate paths for every UAV, making them arrive the same destination with the same time consumption. A spatial-temporal collision avoidance technique is introduced to make collision free. Distance to destination is constructed to improve the searching accuracy and velocity of particles. In addition, the objective function is redesigned by considering the obstacle and threat avoidance, Estimated Time of Arrival(ETA), separation maintenance and UAV self-constraints. Experimental results prove the effectiveness and efficiency of the algorithm.
