Rhosady, Achmadaniar Anindya (2021) Mobility-Aware Offloading Decision Method For Energy Efficient And Low Latency Delay On Heterogent Simulation Environment. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Mobile Cloud Computing (MCC) adalah salah satu teknologi yang dapat mengatasi permasalahan komputasi tinggi dan keterbatasan sumber daya yang dimiliki oleh mobile device. Tetapi pada praktiknya MCC memiliki jarak transmisi yang sangat jauh dengan mobile device sehingga timbul latency yang besar pula. Mobile Edge Computing (MEC) merupakan teknologi yang hadir untuk mengatasi permasalahan ini. Namun demikian timbul permasalahan baru dari kehadiran MEC ini.
Salah satu permasalahan yang timbul adalah pemilihan keputusan offloading dari mobile device. Beberapa penelitian mempertimbangkan efisiensi energi / besar latency ataupun keduanya dalam menentukan keputusan offloading. Namun demikian belum banyak penelitian yang mempertimbangkan pergerakan dari mobile device dalam menentukan keputusan offloading. Padahal pergerakan mobile device ini juga sangat berpengaruh besar terhadap latency karena task perlu dimigrasi ke edge server lain saat suatu mobile device telah bergerak. Beberapa penelitian yang telah mengatasi hal ini menerapkan solusinya kepada lingkungan simulasi yang kecil dan kurang heterogen.
Pada penelitian ini digunakan sebuah metode baru dalam pengambilan keputusan offloading yang memperhatikan pergerakan dari mobile device pada lingkungan yang heterogen. Metode yang diusulkan ini menggunakan Black Widow Optimization dalam menyelesaikan permasalahan pemilihan keputusan saat oflloading. Dari hasil simulasi yang dilakukan performa dari metode yang diusulkan lebih baik daripada metode pembandingnya dari segi besarnya konsumsi energy dan delay latency.
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problems of high computing and limited re-sources owned by mobile devices. However, in practice, MCC has a very long transmission distance from the mobile de-vice, resulting in a large latency. Mobile Edge Computing (MEC) is a technology that exists to overcome this problem. However, new problems arise from the presence of this MEC.
One of the problems that arise is the selection of offloading decisions from mobile devices. Several studies consider en-ergy efficiency / large latency or both in determining offloading decisions. However, there are not many studies that con-sider the movement of mobile devices in determining offloading decisions. Even though the movement of mobile devices is also very influential on latency because tasks need to be migrated to another edge server when a mobile device has moved. Several studies that have addressed this issue apply the solution to smaller, less heterogeneous simulation environments.
This study used a new method of offloading decision-making that pays attention to the movement of mobile devices in a heterogeneous environment. This proposed method uses Black Widow Optimization in solving the problem of decision selection when offloading. From the simulation results, the performance of the proposed method is better than the comparison method in terms of the amount of energy consumption and delay latency.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Offloading, Mobile Edge Computing, Black Widow Optimization Offloading, Mobile Edge Computing, Black Widow Optimization |
| Subjects: | Q Science > QA Mathematics > QA76.585 Cloud computing. Mobile computing. Q Science > QA Mathematics > QA76.6 Computer programming. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55101-(S2) Master Thesis |
| Depositing User: | Achmadaniar Anindya Rhosady |
| Date Deposited: | 13 Aug 2021 21:49 |
| Last Modified: | 13 Aug 2021 21:49 |
| URI: | http://repository.its.ac.id/id/eprint/86044 |
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