Analisis Kinerja Load Balancing Pada Cloud environment Menggunakan Algoritma Honey Bee Behavior

Rosfandy, Bagus Ridho (2024) Analisis Kinerja Load Balancing Pada Cloud environment Menggunakan Algoritma Honey Bee Behavior. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kebutuhan akan teknologi cloud yang terus meningkat menimbulkan tantangan baru dalam pengelolaan sumber daya pada lingkungan komputasi awan. Load balancing menjadi faktor krusial dalam pengoptimalan pengelolaan sumber daya pada lingkungan cloud, terutama dalam mengatasi masalah overloading yang dapat menyebabkan penurunan kinerja sistem dan bahkan kegagalan layanan. Dalam paper ini, diusulkan metode algoritma load balancing menggunakan Honey Bee Behaviour (HBB), sebuah algoritma dinamis berbasis Swarm Intelligence yang meniru perilaku lebah madu dalam mencari makanan. Metode ini bertujuan untuk mendistribusikan beban kerja yang dinamis secara merata dalam sebuah sistem cloud computing. Algoritma Honey Bee Behavior (HBB) akan dibandingkan dengan alogirtma Ant Colony Optimization (ACO) dalam uji coba load balancing menggunakan CloudSim sebagai simulator. Pengujian ini menunjukkan hasil bahwa HBB unggul dalam penyeimbangan beban pada dataset Random dan SDSC.
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The growing demand for cloud technology brings new challenges in managing resources in cloud computing environments. Load balancing emerges as a critical factor in optimizing resource management, especially in tackling issues of overloading that can degrade system performance and potentially lead to service failures. This paper introduces a load balancing method using the Honey Bee Behaviour (HBB) algorithm, a dynamic approach inspired by swarm intelligence that emulates the foraging behavior of honey bees. This method is designed to evenly distribute dynamic workloads within a cloud computing system. The Honey Bee Behaviour (HBB) algorithm is compared with the Ant Colony Optimization (ACO) algorithm in load balancing trials using CloudSim as the simulator. The results demonstrate that HBB is superior in managing load balance across the Random and SDSC datasets.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Cloudsim, Honey Bee, Komputasi Awan, Load Balancing, Swarm Intelligent ============================================================= Cloudsim, Cloud Computing, Honey Bee, Load Balancing, Swarm Intelligent
Subjects:	Q Science > QA Mathematics > QA76.585 Cloud computing. Mobile computing. Q Science > QA Mathematics > QA76.9 Computer algorithms. Virtual Reality. Computer simulation.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis
Depositing User:	Bagus Ridho Rosfandy
Date Deposited:	29 Jul 2024 02:29
Last Modified:	29 Jul 2024 02:29
URI:	http://repository.its.ac.id/id/eprint/109426

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