scholarly journals On-demand virtual research environments using microservices

2019 ◽  
Vol 5 ◽  
pp. e232 ◽  
Author(s):  
Marco Capuccini ◽  
Anders Larsson ◽  
Matteo Carone ◽  
Jon Ander Novella ◽  
Noureddin Sadawi ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Open Source ◽  
Scientific Community ◽  
Life Science ◽  
Scientific Applications ◽  
Infrastructure As A Service ◽  
On Demand ◽  
Research Environments ◽  
Cloud Providers

The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying solely on infrastructure as a service does not achieve the degree of flexibility required by the scientific community. Here we present a microservice-oriented methodology, where scientific applications run in a distributed orchestration platform as software containers, referred to as on-demand, virtual research environments. The methodology is vendor agnostic and we provide an open source implementation that supports the major cloud providers, offering scalable management of scientific pipelines. We demonstrate applicability and scalability of our methodology in life science applications, but the methodology is general and can be applied to other scientific domains.

scholarly journals Effectual Resource Allocation using Auction Mechanism in Cloud Computing

2019 ◽  
Vol 9 (2S2) ◽  
pp. 814-819
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Emerging Technology ◽  
Dynamic Resource Allocation ◽  
High Cloud ◽  
Auction Mechanism ◽  
On Demand ◽  
Cloud Providers ◽  
Dynamic Resource

Cloud computing(CC) is one of the fastest emerging technology. As we all know, cloud is a wide pool of resource which provides resources based on the users request. Any service can be provided as a service through cloud. As the cloud contains many resources, there may also wastage of resources. To reduce this wastage, cloud providers enter into auctioning of resources when the demand is high. Cloud computing includes distinct resources. Because of the complementary and supplementary effects between distinct assets, bidders have preferences not for just a single resource but also for a set of resources. Auctioning for a bundle of resources is called mergeable auction (MA). Dynamic resource allocation in on demand for a bundle of resource is proposed by using MA – PROVISION algorithm and the scenarios are simulated using Cloudsim, a simulator meant for cloud computing analysis.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

Resource Allocation in Cloud Computing Environment using AHP Technique

2014 ◽  
Vol 4 (1) ◽  
pp. 33-44 ◽  
Author(s):  
Anil Singh ◽  
Kamlesh Dutta ◽  
Avtar Singh
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Synthesis Methods ◽  
Computing Environment ◽  
Computing Technology ◽  
Method Error ◽  
Cloud Computing Environment ◽  
Mps Method ◽  
On Demand ◽  
Hierarchy Process

Cloud Computing has changed the strategy of the way of providing different services to business and government agent as well as to sole users. Cloud Computing provides scalable and on demand services to users irrespective of their physical area. But this computing technology has many challenges. One of them is on demand resource allocation. In this paper a resource allocation method is proposed based on Analytical Hierarchy Process (AHP) called Multicriteria Preference Synthesis (MPS) method. MPS method combines many AHP synthesis methods (Additive Normalization, EigenVector, Multicriteria Synthesis etc.) to assign the priorities to the users' tasks. In MPS method Error Criteria is used to provide the consistency in providing the priorities to users' tasks if any violation is there.

Efficient Development and Execution of Adaptable Online Games on Clouds

2017 ◽  
pp. 25-66
Author(s):  
Dominik Meiländer ◽  
Sergei Gorlatch
Keyword(s):  
Cloud Computing ◽  
Management System ◽  
Online Games ◽  
System Support ◽  
Infrastructure As A Service ◽  
Resource Management System ◽  
Multiplayer Online Games ◽  
On Demand ◽  
Lifecycle Model ◽  
Cost Efficient

Massively Multiplayer Online Games (MMOG) are a challenging class of applications: they combine high demands on real-time user interactivity and adaptability with the problem of an efficient and economic utilization of resources for the dynamically changing number of users. This chapter studies how MMOG can benefit from Cloud Computing with its Infrastructure-as-a-Service (IaaS) approach to cost-efficient leasing resources on demand. The chapter makes two major contributions: (1) a new lifecycle model for the development of adaptable MMOG expresses major design and execution aspects of Cloud-based MMOG, and (2) a resource management system RTF-RMS implements efficient load balancing for MMOG on Clouds. The authors illustrate how their lifecycle model and RTF-RMS system support the efficient development and execution of adaptable MMOG on Clouds and demonstrate the advantages of their approach in an experimental evaluation.

Intercloud

2020 ◽  
pp. 1750-1769
Author(s):  
Alexandru Aurel Costan ◽  
Bogdan Iancu ◽  
Petru Cosmin Rasa ◽  
Alexandru Radu ◽  
Adrian Peculea ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Future Internet ◽  
Cloud Services ◽  
The Internet ◽  
On Demand ◽  
Heterogeneous Services ◽  
Business Opportunities ◽  
Cloud Providers ◽  
Almost All

Cloud computing is considered the next step in the evolution of technological applications, services and products development, in the Future Internet and Internet of Things context. The permanent connection of users to the Internet has become widespread, so almost all available resources (data, software) can be placed on the Internet, shared between users - sometimes completely independently of others, and brought from the Internet to the user's computer on demand. The chapter highlights the benefits of using hybrid technology with a focus towards entrepreneurs and business innovators. Intercloud systems are built of heterogeneous services, offered by different providers of cloud computing. To emphasize the business opportunities offered by innovative Intercloud approaches, an architecture for the interconnection of cloud services offered by multiple cloud providers, with applications to e-health, is presented. The main concepts and business benefits of using Intercloud systems and an architecture for interconnecting cloud services from multiple cloud providers is described.

scholarly journals Taxonomy of resource allocation algorithms for inner IaaS cloud data centres

2013 ◽  
Author(s):  
Dang Minh Quan
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machines ◽  
Computer Hardware ◽  
Infrastructure As A Service ◽  
Cloud Data ◽  
Cloud Infrastructures ◽  
Allocation Algorithms ◽  
Data Centres ◽  
Cloud User

Cloud computing has become more and more popular  with  the  widely  deployment  of  several  cloud infrastructures.  Infrastructure-as-a-service  (IaaS) Cloud  computing  replaces  bare  computer hardware. The cloud user  will use the virtual  machines (VMs)  to  fullfil  their  computing  requirements.  Among the  components  of  IaaS  cloud  software  stack,  the resource  allocation  module  is  very  important  as  it selects suitable VMs and the place to execute VMs. This paper  focuses  on  studying  and  classifying  algorithms used  in  the  resource  allocation  module.  The  issues  of how to apply those algorithms are also discussed.

Model-Based Application Deployment on Cloud Computing

2019 ◽  
Vol 10 (2) ◽  
pp. 110-127 ◽  
Author(s):  
Aouat Asmaa ◽  
Deba El Abbassia ◽  
Benyamina Abou EL Hassan ◽  
Benhamamouch Djilali
Keyword(s):  
Cloud Computing ◽  
The Internet ◽  
Cloud Environment ◽  
Model Driven Engineering ◽  
Model Driven ◽  
On Demand ◽  
Model Based ◽  
Cloud Providers ◽  
Application Deployment ◽  
Scientific Challenge

Cloud Computing refers to a set of technologies and systems that provide various types of resources (computing, storage, software, etc.) on demand, through the Internet or Intranet. Thanks to these advantages many Cloud providers are available and is increasing. These cloud providers offer different PaaS platforms that must each be configured in its own appropriate way to deploy applications in the cloud. Cloud Computing is based on heterogeneity principles, which allows many configurations and sizing choices. This implies that the developer must master all deployment methods in order to benefit from all suppliers. The development and deployment of applications in the Cloud offers a new scientific challenge in terms of expression and taking into account variability. The purpose of the author's work is to propose a deployment method and implement it to automate the process of deploying applications in a cloud environment based on model-driven engineering, to configure and provision applications to be deployed in the cloud.

Cloud Federations

2016 ◽  
pp. 1-41 ◽  
Author(s):  
Marcio R. M. Assis ◽  
Luiz Fernando Bittencourt ◽  
Rafael Tolosana-Calasanz ◽  
Craig A. Lee
Keyword(s):  
Cloud Computing ◽  
Scientific Community ◽  
Quality Of Services ◽  
Cloud Federation ◽  
Cloud Providers ◽  
Multiple Clouds ◽  
Lock In

With the maturation of the Cloud Computing, the eyes of the scientific community and specialized commercial institutions have turned to research related to the use of multiple clouds. The main reason for this interest is the limitations that many cloud providers individually face to meet all the inherent characteristics of this paradigm. Therefore, using multiple cloud organizations opens the opportunity for the providers to consume resources with more attractive prices, increase the resilience as well as to monetize their own idle resources. When considering customers, problems as interruption of services, lack of interoperability that lead to lock-in and loss of quality of services due to locality are presented as limiting to the adoption of Cloud Computing. This chapter presents an introduction to conceptual characterization of Cloud Federation. Moreover, it presents the challenges in implementing federation architectures, requirements for the development of this type of organization and the relevant architecture proposals.

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