Abstract
Following the development of wireless multimedia sensor networks (WMSN), the coverage of the sensors in the network constitutes one of the key technologies that have a significant influence on the monitoring ability, quality of service, and network lifetime. The application environment of WMSN is always a complex surface, such as a hilly surface, that would likely cause monitoring shadowing problems. In this study, a new coverage-enhancing algorithm is presented to achieve an optimal coverage ratio of WMSN based on three-dimensional (3D) complex surfaces. By aiming at the complex surface, the use of a 3D sensing model, including a sensor monitoring model and a surface map calculation algorithm, is proposed to calculate the WMSN coverage information in an accurate manner. The coverage base map allowed the efficient estimation of the degree of monitoring occlusion efficiently and improved the system’s accuracy. To meet the requests of complex 3D surface monitoring tasks for multiple sensors, we propose a modified cuckoo search algorithm that considers the features of the WMSN coverage problem and combines the survival of the fittest, dynamic discovery probability, and the self-adaptation strategy of rotation. The evaluation outcomes demonstrate that the proposed algorithm can describe the 3D covering field but also improve both the coverage quality and efficiency of the WMSN on a complex surface.
Highlights
With the development of embedded systems and communication technology, wireless multimedia sensor networks (WMSN) have assumed a prominent scientific position [1,2]
We propose a modified cuckoo search algorithm (MCSA) to compute the coverage area of the complex surface based on the survival of the fittest, dynamic discovery probability, and the self-adaptation strategy of rotation
We evaluate the construction of the surface map
Summary
With the development of embedded systems and communication technology, wireless multimedia sensor networks (WMSN) have assumed a prominent scientific position [1,2]. Coverage studies for complex surfaces based on 3D sensing models have not been investigated. To address and resolve these challenges, we propose a novel framework for a complex surface coverage model for WMSN which (i) calculates the complex surface coverage and (ii) adjusts the directions of the sensors based on monitoring. Considering the fact that the monitoring area may be obstructed by physical barriers, such as hills or buildings, we propose a coverage-based map to help solve this problem. This model provides an achievable shade rule which quantifies the actual sensing area for each sensor.
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