Computation Offloading with MQTT Protocol on a Fog-Mist Computing Framework

2019 ◽  
pp. 140-147
Author(s):  
Pietro Battistoni ◽  
Monica Sebillo ◽  
Giuliana Vitiello
Keyword(s):  
Computation Offloading ◽  
Computing Framework

ANALISIS EFEKTIFITAS FRAMEWOK ERP CLOUD COMPUTING UNTUK USAHA KECIL MENENGAH

2018 ◽  
Vol 3 (1) ◽  
pp. 19 ◽  
Author(s):  
Matheus Alvian Wikanargo ◽  
Novian Adi Prasetyo ◽  
Angelina Pramana Thenata
Keyword(s):  
Cloud Computing ◽  
Human Resource ◽  
Software As A Service ◽  
Infrastructure As A Service ◽  
Computing Framework

AbstrakTeknologi cloud computing pada era sekarang berkembang pesat. Penerapan teknologi cloud computing sudah merambah ke berbagai industri, mulai dari perusahaan besar hingga perusahaan kecil dan menengah. Perambahan cloud computing di perindustrian berupa implementasi ke dalam sistem ERP. Namun, penetrasi teknologi ini dalam lingkup perusahaan kecil dan menengah (UKM) masih belum sekuat perusahaan besar. Penerapan ERP berbasis cloud computing yang masih tergolong baru tentu memiliki keuntungan dan penghambat yang mempengaruhi kinerja perusahaan. Hal tersebut menjadi salah satu pertimbangan UKM masih enggan menggunakan teknologi ini. Penelitian ini akan menganalisis framework yang paling sesuai untuk UKM dalam menerapkan sistem ERP berbasis cloud computing. Framework yang dianalisa yaitu Software as a Service (SaaS), Infrastructure as a Service (IaaS), dan Platform as as Service (PaaS). Ketiga framework ini akan dibandingkan menggunakan metode studi literatur. Tolak ukur yang menjadi acuan untuk perbandingan adalah Compatibility, Cost, Flexibility, Human Resource, Implementation, Maintenance, Security, dan Usability. Faktor-faktor tersebut akan diukur keuntungan dan penghambatnya jika diterapkan dalam SME. Hasil dari penilitian ini adalah Framework SaaS yang paling cocok untuk diterapkan pada perusahaan kecil dan menengah. Kata kunci— Cloud Computing, UKM, SaaS, IaaS, PaaS 

A Digital Currency for Computation offloading

2019 ◽  
Vol 7 (6) ◽  
pp. 135-139
Author(s):  
Farheen Sultana ◽  
Mohd Tajuddin
Keyword(s):  
Computation Offloading ◽  
Digital Currency

Computation Offloading Game in Multiple UAV-Enabled Mobile Edge Computing Networks

2020 ◽  
Author(s):  
Yanling Ren ◽  
Zhibin Xie ◽  
Zhenfeng Ding ◽  
xiyuan sun ◽  
Jie Xia ◽  
...  
Keyword(s):  
Edge Computing ◽  
Computation Offloading ◽  
Mobile Edge Computing

Leveraging Intelligent Computation Offloading with Fog/Edge Computing for Tactile Internet: Advantages and Limitations

IEEE Network ◽  
2020 ◽  
Vol 34 (5) ◽  
pp. 322-329
Author(s):  
Mithun Mukherjee ◽  
Mian Guo ◽  
Jaime Lloret ◽  
Qi Zhang
Keyword(s):  
Edge Computing ◽  
Computation Offloading

On the Design of Computation Offloading in Fog Radio Access Networks

2019 ◽  
Vol 68 (7) ◽  
pp. 7136-7149 ◽  
Author(s):  
Zhongyuan Zhao ◽  
Shuqing Bu ◽  
Tiezhu Zhao ◽  
Zhenping Yin ◽  
Mugen Peng ◽  
...  
Keyword(s):  
Access Networks ◽  
Computation Offloading ◽  
Radio Access Networks ◽  
Radio Access

scholarly journals Multi-Objective Whale Optimization Algorithm for Computation Offloading Optimization in Mobile Edge Computing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2628
Author(s):  
Mengxing Huang ◽  
Qianhao Zhai ◽  
Yinjie Chen ◽  
Siling Feng ◽  
Feng Shu
Keyword(s):  
Optimization Algorithm ◽  
Edge Computing ◽  
Solution Set ◽  
Whale Optimization Algorithm ◽  
Computation Offloading ◽  
Mobile Edge Computing ◽  
Multi Objective ◽  
Whale Optimization ◽  
Artificial Immune System Algorithm

Computation offloading is one of the most important problems in edge computing. Devices can transmit computation tasks to servers to be executed through computation offloading. However, not all the computation tasks can be offloaded to servers with the limitation of network conditions. Therefore, it is very important to decide quickly how many tasks should be executed on servers and how many should be executed locally. Only computation tasks that are properly offloaded can improve the Quality of Service (QoS). Some existing methods only focus on a single objection, and of the others some have high computational complexity. There still have no method that could balance the targets and complexity for universal application. In this study, a Multi-Objective Whale Optimization Algorithm (MOWOA) based on time and energy consumption is proposed to solve the optimal offloading mechanism of computation offloading in mobile edge computing. It is the first time that MOWOA has been applied in this area. For improving the quality of the solution set, crowding degrees are introduced and all solutions are sorted by crowding degrees. Additionally, an improved MOWOA (MOWOA2) by using the gravity reference point method is proposed to obtain better diversity of the solution set. Compared with some typical approaches, such as the Grid-Based Evolutionary Algorithm (GrEA), Cluster-Gradient-based Artificial Immune System Algorithm (CGbAIS), Non-dominated Sorting Genetic Algorithm III (NSGA-III), etc., the MOWOA2 performs better in terms of the quality of the final solutions.

scholarly journals Vehicular Computation Offloading for Industrial Mobile Edge Computing

2021 ◽  
pp. 1-1
Author(s):  
Liang Zhao ◽  
Kaiqi Yang ◽  
Zhiyuan Tan ◽  
Houbing Song ◽  
Ahmed Al-Dubai ◽  
...  
Keyword(s):  
Edge Computing ◽  
Computation Offloading ◽  
Mobile Edge Computing
Sign in / Sign up

Export Citation Format

Share Document