Programming Models for Cloud Computing

2014 ◽  
pp. 212-237
Keyword(s):  
Cloud Computing ◽  
Programming Models

An API for Development of User-Defined Scheduling Algorithms in Aneka PaaS Cloud Software

2019 ◽  
pp. 170-187 ◽  
Author(s):  
Rajinder Sandhu ◽  
Adel Nadjaran Toosi ◽  
Rajkumar Buyya
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Scheduling Algorithms ◽  
Research Area ◽  
Programming Models ◽  
Hybrid Cloud ◽  
Main Research ◽  
Cloud Application ◽  
Cloud Environments ◽  
Cloud Infrastructures

Cloud computing provides resources using multitenant architecture where infrastructure is created from one or more distributed datacenters. Scheduling of applications in cloud infrastructures is one of the main research area in cloud computing. Researchers have developed many scheduling algorithms and evaluated them using simulators such as CloudSim. Their performance needs to be validated in real-time cloud environments to improve their usefulness. Aneka is one of the prominent PaaS software which allows users to develop cloud application using various programming models and underline infrastructure. This chapter presents a scheduling API developed for the Aneka software platform. Users can develop their own scheduling algorithms using this API and integrate it with Aneka to test their scheduling algorithms in real cloud environments. The proposed API provides all the required functionalities to integrate and schedule private, public, or hybrid cloud with the Aneka software.

Secure Health Monitoring in the Cloud Using Homomorphic Encryption

2020 ◽  
pp. 56-92
Author(s):  
Scott Ames ◽  
Muthuramakrishnan Venkitasubramaniam ◽  
Alex Page ◽  
Ovunc Kocabas ◽  
Tolga Soyata
Keyword(s):  
Cloud Computing ◽  
Health Monitoring ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Programming Models ◽  
Privacy Concerns ◽  
Medical Software ◽  
Speed Up ◽  
Data Elements

Extending cloud computing to medical software, where the hospitals rent the software from the provider sounds like a natural evolution for cloud computing. One problem with cloud computing, though, is ensuring the medical data privacy in applications such as long term health monitoring. Previously proposed solutions based on Fully Homomorphic Encryption (FHE) completely eliminate privacy concerns, but are extremely slow to be practical. Our key proposition in this paper is a new approach to applying FHE into the data that is stored in the cloud. Instead of using the existing circuit-based programming models, we propose a solution based on Branching Programs. While this restricts the type of data elements that FHE can be applied to, it achieves dramatic speed-up as compared to traditional circuit-based methods. Our claims are proven with simulations applied to real ECG data.

scholarly journals Implementing cloud-based parallel metaheuristics: an overview

2018 ◽  
Vol 18 (03) ◽  
pp. e26
Author(s):  
Patricia González ◽  
Xoán Carlos Pardo Martínez ◽  
Ramón Doallo ◽  
Julio Banga
Keyword(s):  
Cloud Computing ◽  
Global Optimization ◽  
Optimization Problems ◽  
Programming Models ◽  
Interested Reader ◽  
Science And Engineering ◽  
Parallel Metaheuristics ◽  
Available Resources

Metaheuristics are among the most popular methods for solving hard global optimization problems in many areas of science and engineering. Their parallel im- plementation applying HPC techniques is a common approach for efficiently using available resources to re- duce the time needed to get a good enough solution to hard-to-solve problems. Paradigms like MPI or OMP are the usual choice when executing them in clusters or supercomputers. Moreover, the pervasive presence of cloud computing and the emergence of programming models like MapReduce or Spark have given rise to an increasing interest in porting HPC workloads to the cloud, as is the case with parallel metaheuristics. In this paper we give an overview of our experience with different alternatives for porting parallel metaheuris- tics to the cloud, providing some useful insights to the interested reader that we have acquired through extensive experimentation.

Secure Health Monitoring in the Cloud Using Homomorphic Encryption

2015 ◽  
pp. 116-152 ◽  
Author(s):  
Scott Ames ◽  
Muthuramakrishnan Venkitasubramaniam ◽  
Alex Page ◽  
Ovunc Kocabas ◽  
Tolga Soyata
Keyword(s):  
Cloud Computing ◽  
Health Monitoring ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Programming Models ◽  
Privacy Concerns ◽  
Medical Software ◽  
Speed Up ◽  
Data Elements

Extending cloud computing to medical software, where the hospitals rent the software from the provider sounds like a natural evolution for cloud computing. One problem with cloud computing, though, is ensuring the medical data privacy in applications such as long term health monitoring. Previously proposed solutions based on Fully Homomorphic Encryption (FHE) completely eliminate privacy concerns, but are extremely slow to be practical. Our key proposition in this paper is a new approach to applying FHE into the data that is stored in the cloud. Instead of using the existing circuit-based programming models, we propose a solution based on Branching Programs. While this restricts the type of data elements that FHE can be applied to, it achieves dramatic speed-up as compared to traditional circuit-based methods. Our claims are proven with simulations applied to real ECG data.

Introduction to Cloud Computing

2014 ◽  
Vol 13 (8) ◽  
pp. 4747-4752
Author(s):  
Alka Bansal ◽  
Money Sethi ◽  
Pooja Rani ◽  
Deepika Sharma
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Programming Models ◽  
The Internet ◽  
It Industry ◽  
Software Failures ◽  
Computer Resources

The Cloud computing is a fastest growing area in IT industry, computing and research industry. Cloud is a pool of virtualized computer resources .A cloud can support self-redundant, self-recovering and scalable programming models that allow data to recover from any hardware/software failures. With the advent of this new technology, you can access the data online if you have an access to the internet. The intent of this paper is to have a review on cloud computing, how it works, services of cloud computing and its deployment models, benefits and challenges.

Cloud-Computing: eHealth aus der Wolke

2018 ◽  
Vol 23 (11) ◽  
pp. 38-41
Author(s):  
Sebastian Krolop ◽  
Florian Benthin ◽  
Constanze Knahl
Keyword(s):  
Cloud Computing ◽  
Point Of Care

Cloud-Computing gewinnt auch in Kliniken zunehmend an Bedeutung. Über das Internet bereitgestellte Lösungen verändern nicht nur Verwaltung und Logistik – im klinischen Bereich geht es zum Beispiel um die Nutzung elektronischer Patientenakten am Point-of-Care.

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