Grid-based directed diffusion for wireless sensor networks

Directed diffusion is a data dissemination protocol for wireless sensor networks. In directed diffusion, flooding is used for dissemination of interest and exploratory data, which will bring broadcast storm resulting in substantial energy consumption of networks. A grid-based directed diffusion is presented to improve the energy efficiency of directed diffusion. Virtual geographic grid clusters are constructed by self-organization of nodes using geographic location information. The flooding of interest and exploratory data of original directed diffusion is limited in cluster head nodes. The simulation results and testbed experiments show that the method effectively reduces the network energy consumption. This gain is not achieved at the cost of either delivery ratio or the delay. Importantly, the decreased load also leads to a better delivery ratio and lower delay.

Aware Diffusion: A Semi-Holistic Routing Protocol for Wireless Sensor Networks

Routing is a challenging task in Wireless Sensor Networks (WSNs) due to the limitation in energy and hardware capabilities in WSN nodes. This challenge prompted researchers to develop routing protocols that satisfy WSNs needs. The main design objectives are reliable delivery, low energy consumption, and prolonging network lifetime. In WSNs, routing is based on local information among neighboring nodes. Routing decisions are made locally;each node will select the next hop without any clue about the other nodes on the path. Although a full knowledge about the network yields better routing, that is not feasible in WSNs due to memory limitation and to the high traffic needed to collect the needed data about all the nodes in the network. As an effort to try to overcome this disadvantage, we are proposing in this paper aware diffusion routing protocol. Aware diffusion follows a semi-holistic approach by collecting data about the available paths and uses these data to enforce healthier paths using machine learning. The data gathering is done by adding a new stage called data collection stage. In this stage, the protocol designer can determine which parameters to collect then use these parameters in enforcing the best path according to certain criteria. In our implementation of this paradigm, we are collecting total energy on the path, lowest energy level on the path, and hop count. Again, the data collected is designer and application specific. The collected data will be used to compare available paths using non-incremental learning, and the outcome will be preferring paths that meet the designer criteria. In our case, healthier and shorter paths are preferred, which will result in less power consumption, higher delivery rate, and longer network life since healthier and fewer nodes will be doing the work.

Energy Balance Routing Protocol for Wireless Sensor Networks Based on Fuzzy Next-Hop Selection

The implementation of energy balanced routing is an effective way to prolong the lifetime of wireless sensor networks （WSNs）. To balance energy consumption, fuzzy next-hop selecting strategy was designed： nodes of different gradients are fuzzily classified into relevant levels; each level has a chance to provide a node with maximum residual energy as the next-hop. Based on the above strategy and directed diffusion （DD）, fuzzy next-hop selection based energy balance （FNSEB） routing protocol was proposed. The simulation results showed that FNSEB utilized the limited energy more thoroughly and rationally, decreased the average energy consumption and prolonged the lifetime of WSNs.

A unified model of bidirectional reflectance distribution function for the vegetation canopy

An accurate and operational bidirectional reflectance distribution function （BDRF） canopy model is the basis of quantitative vegetation remote sensing. The canopy reflectance should be approximated as the sum of the single scattering reflectance arising from the sun, pl, and the multiple scattering reflectance arising from the canopy, fin, as their directional characteristics are dramatically different. Based on the existing BRDF model, we obtain a new analytical expression of ρ1 and ρm in this paper, which is suitable for different illumination conditions and different vegetation canopies. According to the geometrical optic model at the leaf scale, the anisotropy of ρ1 can be ascribed to the geometry of the object, sun and the sensor, multiple scale clumping, and the fraction of direct solar radiation and diffuse sky radiation. Then, we parameterize the area ratios of four components： the sunlit foliage, sunlit ground, shadow foliage and shadow ground based on a Poisson distribution, and develop a new approximate analytical single scattering reflectance model. Assuming G=0.5, a recollision probability theory based scattering model is developed which considers the effects of diffuse sky radiation, scattering inside the canopy and rebounds between the canopy and soil. Validation using ground measurements of maize and black spruce forest proves the reliability of the model.

Distortion correction for the elemental images of integral imaging by introducing the directional diffuser

A distortion correction method for the elemental images of integral imaging（Ⅱ） by utilizing the directional diffuser is demonstrated. In the traditional Ⅱ, the distortion originating from lens aberration wraps elemental images and degrades the image quality severely. According to the theoretical analysis and experiments, it can be proved that the farther the three-dimensional image is displayed from the lens array, the more serious the distortion is. To analyze the process of eliminating lens distortion, one lens and its corresponding elemental image are separated from the traditional Ⅱ. By introducing the directional diffuser, the aperture stop of the separated optical system changes from the eye＇s pupil to the lens. In terms of contrast experiments, the distortion of the improved display system is corrected effectively. In the experiment, when the distance between the reconstructed image and lens array is equal to 120 mm, the largest lens distortion is decreased from 46.6% to 3.3%.