Cylindrical and three-dimensional corner reflector antennas

Two reflector antennas are proposed. The first is constructed by adding a cylindrical reflecting surface of suitable radius to theV-shaped corner reflector antenna. The feeding element is a half-wavelength dipole. The resulting cylindrical corner reflector provided a 2 dB increase in gain, minimum sidelobe level, low input reactance, and uncritical dependence of performance on frequency. The second antenna is constructed by adding a cylindrical surface to the three-dimensional corner reflector. This extension provided an increase in gain of at least 6.5 dB, an input resistance compatible with the commercially available 50- or75-Omegacoaxial cables, low input reactance, and uncritical dependence of performance on frequency. A grid-type cylindrical corner reflector antenna, and a three-dimensional corner reflector antenna with a cylindrical subsurface of finite reflecting surfaces were designed, and the measured input impedances, gains, and field patterns showed excellent agreement with the theoretical results for both antennas.     

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.