Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm.

We demonstrate a damascene process for fabricating amorphous silicon (a-Si), single-mode optical channel waveguides and high-Q racetrack resonators. This process is compatible with thermal budget limitations for a-Si phase stability. It offers improved optical transmission and facilitates hydrogen encapsulation for process integration of a-Si waveguide cores. At $1550\mathrm{nm}$, the average measured transmission loss coefficient is $2.5\pm 0.1\mathrm{dB}∕\mathrm{cm}$ for the TE mode, comparable with high-quality single crystalline silicon counterparts. The racetrack resonators have mid-${10}^4$ to ${10}^5$ quality factors (Q) and extinction ratios as high as $25\mathrm{dB}$.

Accurate location information is essential for various emerging applications in wireless sensor network (WSN). In order to improve localization accuracy, it is of paramount importance to reduce the effects of noisy distance measurements. This paper proposes an anchor node selection scheme for Received Signal Strength- (RSS-) based localization in WSN. In the proposed approach, the nodes are sorted firstly to select anchor nodes reasonably, and to further reduce the influence of range error, the weight is assigned to each selected anchor node. Finally, an effective modified cuckoo search algorithm is used to compute the coordinates of unknown nodes. Extensive experiments are conducted to study the effects of anchor node ratio, ranging error factor and node density on the localization accuracy performance of the proposed method. The experimental results demonstrate that the proposed method performs better in improving localization accuracy compared with the localization technique without special anchor selection scheme which selects all anchors information received and the localization technique selecting nearest anchors.