Rosyadi, Fuad Dary (2021) Metode Penjadwalan Sleep Wakeup Dengan Efisiensi Energi Untuk Jaringan Sensor Nirkabel Berbasis Target Dengan Model P-Coverage Dan Q-Connectivity. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Keterbatasan energi menjadi permasalahan yang paling banyak mendapat perhatian dalam dunia Wireless Sensor Network (WSN). Metode penjadwalan sleep wakeup merupakan salah satu teknik yang paling efisien untuk meningkatkan waktu operasional sensor node pada WSN. Namun pada lingkungan target based WSN dengan model p-coverage dan q-connenctivity, penggunaan sleep wakeup scheduling harus memperhatikan batasan jumlah konektivitas pada sensor dan coverage pada target. Genetic Algorithm menjadi solusi permasalahan dari sleep wakeup scheduling dengan permasalahan multi objectif. Penelitian ini mengusulkan sebuah metode baru sleep wakeup scheduling berbasis Genetic Algorithm untuk efisiensi energi pada target based WSN dengan model p-coverage dan q-connectivity. Metode baru ini menggunakan faktor coverage cost, connectivity cost dan sisa energi sebagai fungsi objektif pada fitness function dalam Genetic Algorithm. Dengan adanya faktor energi sebagai salah satu fungsi objektif, metode ini dapat meningkatkan efisiensi energi pada target based WSN dengan model p-coverage dan q-connectivity
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Energy limitations are the problem that gets the most attention in the term of Wireless Sensor Networks (WSN). Sleep wakeup scheduling method is one of the most efficient techniques to increase sensor node operational time on WSN. How-ever, in the target based WSN environment with p-coverage and q-connectivity models, the use of wake-up scheduling has to consider the constraints on the number of connectivity on the sensor and coverage on the target. Genetic Algorithm is a solution to the problem of sleep-wake scheduling with multi-objective problems. This study proposes a new method of sleep wakeup scheduling based on Genetic Algorithm for energy efficiency in target based WSN with p-coverage and q-connectivity models. This method uses coverage cost, connectivity cost and residual energy as the objective factors of the fitness function in the Genetic Algorithm. With the presence of energy as a factor of the objective function can increase energy efficiency in target based WSN with p-coverage and q-connectivity models.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Genetic Algorithm, P-Coverage, Q-Connectivity, Sleep wakeup scheduling, Wireless Sensor Network. |
| Subjects: | T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T57.84 Heuristic algorithms. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55101-(S2) Master Thesis |
| Depositing User: | fuad dary rosyadi |
| Date Deposited: | 16 Aug 2021 05:44 |
| Last Modified: | 16 Aug 2021 05:44 |
| URI: | http://repository.its.ac.id/id/eprint/86051 |
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