Optimal data collection of multi-radio multi-channel multi-power wireless sensor networks for structural monitoring applications: A simulation study

Abstract

Summary Structural health monitoring (SHM) is a kind of data‐intensive applications for wireless sensors network (WSN), which usually requires a high network capacity. However, the bandwidth of traditional single‐radio single‐channel (SR‐SC) WSN is quite limited. In order to meet the requirement of structural monitoring, we investigate the multi‐radio multi‐channel multi‐power (MR‐MC‐MP) communication to improve the data collection performance of SHM‐oriented WSNs in terms of network capacity and power consumption. First, the data collection problem in MR‐MC‐MP WSNs is modeled as an optimization problem under the constraint of available time slots, radios, channels, and power levels. And then, combining the fast convergence of the particle swarm optimization (PSO) algorithm and high exploration performance of flower pollination optimization (FPA) algorithm, we propose a novel binary hybrid meta‐heuristic algorithm named BFPA‐PSO to solve the problem. In order to verify the advantage of the proposed BFPA‐PSO, some other meta‐heuristic algorithms are tested for the problem as well. Finally, several simulation experiments are carried out to test and compare the performance of different algorithms. Experiment results demonstrate that the proposed BFPA‐PSO algorithm has superior performance in terms of network capacity and energy consumption.

Optimal Energy Consumption Tasks Scheduling Strategy for Multi-Radio WSNs

“…Li et al [12] formulated the routing, scheduling, channel assignment and power control problem in multi-power-level multi-radio WSNs as an integer linear programming problem, and then designed a distributed routing protocol which could significantly reduce energy consumption. In order to meet the data-intensive requirements of the structural health monitoring (SHM) field, a novel binary hybrid meta-heuristic algorithm was proposed for multi-radio multi-channel multi-power WSNs [13,14]. Elshrkawey et al [15] improved the cluster head selection method and then proposed an enhanced schedule approach based on the modified Time Division Multiple Access (TDMA) scheme in order to minimize the energy dissipation during network communications.…”

Energy‐aware versatile wireless sensor network configuration for structural health monitoring

“…In recent years, wireless sensor networks have been widely used in structural health monitoring of civil engineering infrastructures due to their advantages of deployment convenience, installation efficiency, arrangement flexibility, and onboard computation. [22][23][24][25][26][27] In contrast to wired sensors, wireless sensors are commonly battery powered. 28,29 To improve the energy efficiency of the network, various wireless sensor network optimization methods have been proposed.…”

“…Previous techniques mainly focused on the information effectiveness of the sensor placement, which are suitable for wired sensor configurations. In recent years, wireless sensor networks have been widely used in structural health monitoring of civil engineering infrastructures due to their advantages of deployment convenience, installation efficiency, arrangement flexibility, and onboard computation 22–27 . In contrast to wired sensors, wireless sensors are commonly battery powered 28,29 .…”

Separable Online System of Dike Monitoring Based on a Parallel-Serial Mode of Signal Measurement

“…Studies need to be conducted to address the question of which method is more suitable for dike monitoring. In such areas as civil engineering, water conservancy, traffic, and agriculture engineering, several new technologies have been introduced into the monitoring system, including but not limited to GIS ( [29]), human-computer interaction technology ( [30], [31]), parallel computing ( [32], [33]), cloud computing ( [34], [35]), wireless networks ( [36]- [39]) and APP ( [40]), which have also found applications in dike monitoring to some extent ( [29], [34]). It is thus particularly necessary to use advanced technologies to improve the performance of the dike monitoring system.…”

“…The monitoring systems can be developed by leveraging the technologies of embedded human-computer interaction ( [30], [40]) and online communication ( [36]). For instance, the acquisition apparatus for slope monitoring is developed with multiple functions, which features human-computer interaction [30].…”