A cloud computing framework for real-time rural and remote service of critical care

2011 ◽  
Author(s):  
Carolyn McGregor
Keyword(s):  
Cloud Computing ◽  
Critical Care ◽  
Real Time ◽  
Rural And Remote ◽  
Computing Framework

scholarly journals Integration of Fog and IoT with Multiensor Data Gathering

2019 ◽  
Vol 8 (4) ◽  
pp. 11785-11787
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Fog Computing ◽  
Data Gathering ◽  
Low Latency ◽  
Computing Paradigm ◽  
City System ◽  
Computing Framework ◽  
The City

In the already existing system number of internet connected devices rapidly increase, this increased demand real-time, for the standard cloud computing framework, low latency services proving to be always a challenge. While In the proposed System, fog computing paradigm serves the demands of the latency sensitive applications in the context of IOT. The IOT is rely on cloud computing by passing information about sensor. This is a decentralized process to gather the information from each and every region of the city. System will check the energy and location of every server. Because whenever server uploads the sensor details it can degrade their energy on every time. So we have to migrate the data by allocating another server which contains the energy to send

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 

scholarly journals On the Design of Efficient Hierarchic Architecture for Software Defined Vehicular Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1400
Author(s):  
Muhammad Adnan ◽  
Jawaid Iqbal ◽  
Abdul Waheed ◽  
Noor Ul Amin ◽  
Mahdi Zareei ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Traffic Management ◽  
Vehicular Networks ◽  
Scheduling Algorithm ◽  
Main Research ◽  
First Come First Serve ◽  
Computing Framework ◽  
Simulation Results

Modern vehicles are equipped with various sensors, onboard units, and devices such as Application Unit (AU) that support routing and communication. In VANETs, traffic management and Quality of Service (QoS) are the main research dimensions to be considered while designing VANETs architectures. To cope with the issues of QoS faced by the VANETs, we design an efficient SDN-based architecture where we focus on the QoS of VANETs. In this paper, QoS is achieved by a priority-based scheduling algorithm in which we prioritize traffic flow messages in the safety queue and non-safety queue. In the safety queue, the messages are prioritized based on deadline and size using the New Deadline and Size of data method (NDS) with constrained location and deadline. In contrast, the non-safety queue is prioritized based on First Come First Serve (FCFS) method. For the simulation of our proposed scheduling algorithm, we use a well-known cloud computing framework CloudSim toolkit. The simulation results of safety messages show better performance than non-safety messages in terms of execution time.

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