Flower Pollination and Genetic Algorithm Based Optimization for Node Deployment in Wireless Sensor Networks

Abstract

Wireless sensor network (WSN) most popular area of research where lots of work done in this field. Energy efficiency is one of the most focusing areas because life time of network is most common issue. In the WSN, the node placement is very essential part for the proper communication between the sensor nodes and base station (BS). For better communication nodes should be aware about their own or neighbor node’s location. Better optimization of resources and performance improvement are the main concern for the WSN. Optimal techniques should be utilized to place the nodes at the best possible locations for achieving the desired goal. For node placement, flower pollination optimization and genetic algorithm are useful to generate better result. BS is responsible for the communication of nodes with each other and it should be reachable to nodes. For this Region of Interest (RoI) is helpful to choose the best location. Placement of BS in the middle is suitable place for the static nodes deployment and there should be other strategy for the dynamic environment. Nodes should be connected to each other for the transmission of data from the source to BS properly. From the MATLAB simulation, it has been shown that the proposed methodology improves the network performance in terms of dead nodes, energy remaining and various packets sent to BS.

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

“…In terms of future smart city concepts, it will have new technologies related to the Internet of Things to optimize environmental monitoring methods under smart cities. According to Keswani and Bhaskar for urban environmental pollution, two integer linear planning formulas based on actual pollutant proliferation models are proposed to handle minimal costs for air pollution monitoring WSN deployment [5]. They analyzed the model to actual data (i.e., Nordoham City Street Lights) and have got some effective WSN deployment to conduct air pollution monitoring.…”

Network Security Situational Awareness Based on Genetic Algorithm in Wireless Sensor Networks

“…In addition to a large number of military applications, WSNs have been widely used in civil fields, such as environmental and ecological monitoring, health monitoring, modern precision agriculture, home automation, and intelligent traffic control [15]. As a new information acquisition and processing technology, WSNs have become an attractive high-tech field in recent years due to their low cost, low power consumption, small size, fast deployment, and strong invulnerability [16].…”