A Review on Multi-objective Optimization in Wireless Sensor Networks Using Nature Inspired Meta-heuristic Algorithms

Gunjan,

doi:10.1007/s11063-022-10851-4

Cited by 7 publications

(1 citation statement)

References 71 publications

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“…For wireless sensor networks (WSNs), where several challenges involve poten conflicting objectives, satisfying one objective leads to degradation in the other's pe mance (if we focus on increasing network lifetime, latency may also increase, which i desired). So, multi-objective optimization methods are applied to solve this challeng ing nature-inspired meta-heuristic algorithms [15]. This method remains more com cated in comparison with the optimization method applied to the sensor in this st Another study, presented by Wioletta Trzpil et al [16], proposes a new concept of ph acoustic gas sensing based on capacitive transduction.…”

Section: Sensor Principlementioning

confidence: 99%

Optimizing Algorithm for Existing Fiber-Optic Displacement Sensor Performance

Elrawashdeh,

Prelle,

Lamarque

et al. 2024

Sensors

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This paper describes the optimal design of a miniature fiber-optic linear displacement sensor. It is characterized by its ability to measure displacements along a millimetric range with sub-micrometric resolution. The sensor consists of a triangular reflective grating and two fiber-optic probes. The measurement principle of the sensor is presented. The design of the sensor’s triangular grating has been geometrically optimized by considering the step angle of the grating to enhance the sensor’s resolution. The optimization method revealed a global optimum at which the highest resolution is obtained.

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Section: Sensor Principlementioning

confidence: 99%