Optimal Scheduling of IoT Tasks in Cloud-Fog Computing Networks

2020 ◽  
pp. 103-112
Author(s):  
Zhiming He ◽  
Qiang Zhao ◽  
Haoran Mei ◽  
Limei Peng
Keyword(s):  
Fog Computing ◽  
Optimal Scheduling

Aplikasi Metode Hungarian Dalam Optimalisasi Waktu Penugasan Karyawan dan Keuntungan Produksi Home Industry

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Empya Charlie ◽  
Siti Rusdiana ◽  
Rini Oktavia
Keyword(s):  
Sensitivity Analysis ◽  
Optimal Solution ◽  
Optimal Scheduling ◽  
Total Work ◽  
Work Time ◽  
Hungarian Method ◽  
Total Work Time

Penelitian ini bertujuan untuk mengoptimalkan penjadwalan karyawan di CV. Karya Indah Bordir dalam melakukan tugas-tugas tertentu menggunakan metode Hungaria, serta menganalisis sensitivitas solusi optimal jika ada pengurangan waktu karyawan untuk menyelesaikan tugas-tugas. Metode Hongaria diterapkan pada proses bordir yang melibatkan 11 karyawan dan 10 tugas. Hasil penjadwalan yang optimal meminimalkan waktu produksi bordir perusahaan. Hasil penjadwalan optimal yang ditemukan adalah: karyawan 1 mengerjakan tas Mambo, karyawan 2 mengerjakan tas Elli, karyawan 3 mengerjakan tas Lonjong, karyawan 4 mengerjakan tas Tampang bunga, karyawan 6 mengerjakan tas Ransel, karyawan 7 mengerjakan tas Tima, karyawan 8 mengerjakan tas Keong, karyawan 9 mengerjakan tas Alexa, karyawan 10 mengerjakan tas Luna, dan karyawan 11 mengerjakan tas Mikha, dengan total waktu kerja adalah 13,7 jam. Setelah metode Hongaria diterapkan, CV. Karya Indah Bordir mendapat peningkatan pendapatan sebanyak 9,09%. Analisis sensitivitas dilakukan dengan mengurangi waktu karyawan dalam menyulam tas. Hasil analisis sensitivitas adalah beberapa batasan untuk variabel basis dan non basis untuk mempertahankan solusi optimal.   This research has a purpose to optimize the scheduling of employees in CV. Karya Indah Bordir in doing certain tasks using Hungarian method, as well as analyzing the sensitivity of the optimal solution if there is a reduction on the employees time to finish the tasks. The Hungarian method was applied on the embroidery process involving 11 employees and 10 tasks. The optimal scheduling result minimize the time of the embroidery production of the company. The optimal scheduling result found is: employee 1 does the Mambo bag, employee 2 does the Elli bag, employee 3 does the Lonjong bag, employee 4 does the Tampang bunga bag, employee 6 does the Ransel, employee 7 does the Tima bag, employee 8 does the Keong bag, employee 9 does the Alexa bag, employees 10 does the Luna bag, and employee 11 does the Mikha bag, with the total work time is 13,7 hours. After the Hungarian method was applied, CV. Karya Indah Bordir got the increasing revenue as much as 9,09 %. The sensitivity analysis was conducted by reducing the time of the employees take in embroidery the bags. The results of the sensitivity analysis are some boundaries for basis and non basis variables to maintain the optimal solution. 

Optimal Scheduling and Control of Ingot Handling in a Steelmaking Environment

1983 ◽  
Author(s):  
Stanley F. Bullington ◽  
Yong-Zai Lu ◽  
Colin L. Moodie ◽  
Theodore J. Williams
Keyword(s):  
Optimal Scheduling ◽  
And Control

Virtualized Fog Network with Load Balancing for IoT based Fog-to-Cloud

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary
Keyword(s):  
Load Balancing ◽  
Packet Loss ◽  
Fog Computing ◽  
Transport Protocol ◽  
Network Simulator ◽  
Huge Number ◽  
Message Queue ◽  
Limited Bandwidth ◽  
Cloud Architecture ◽  
Fog Network

Fog Computing is a new concept made by Cisco to provide same functionalities of Cloud Computing but near to Things to enhance performance such as reduce delay and response time. Packet loss may occur on single Fog server over a huge number of messages from Things because of several factors like limited bandwidth and capacity of queues in server. In this paper, Internet of Things based Fog-to-Cloud architecture is proposed to solve the problem of packet loss on Fog server using Load Balancing and virtualization. The architecture consists of 5 layers, namely: Things, gateway, Fog, Cloud, and application. Fog layer is virtualized to specified number of Fog servers using Graphical Network Simulator-3 and VirtualBox on local physical server. Server Load Balancing router is configured to distribute the huge traffic in Weighted Round Robin technique using Message Queue Telemetry Transport protocol. Then, maximum message from Fog layer are selected and sent to Cloud layer and the rest of messages are deleted within 1 hour using our proposed Data-in-Motion technique for storage, processing, and monitoring of messages. Thus, improving the performance of the Fog layer for storage and processing of messages, as well as reducing the packet loss to half and increasing throughput to 4 times than using single Fog server.

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