scholarly journals G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Rongdong Hu ◽  
Guangming Liu ◽  
Jingfei Jiang ◽  
Lixin Wang
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Resource Utilization ◽  
Scientific Discovery ◽  
Resource Provisioning ◽  
Experimental Results ◽  
Real Sequence ◽  
Application Performance ◽  
Data Volume ◽  
Speed Up

Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%.

A Secured Real Time Scheduling Model for Cloud Hypervisor

2016 ◽  
Vol 6 (4) ◽  
pp. 97-110
Author(s):  
Rekha Kashyap ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Cloud Computing ◽  
Success Rate ◽  
Real Time ◽  
Virtual Machines ◽  
Resource Provisioning ◽  
Real Time Scheduling ◽  
Scheduling Model ◽  
Physical Resources ◽  
Time Scheduling ◽  
Deadline Constraints

Virtualization is critical to cloud computing and is possible through hypervisors, which maps the Virtual machines((VMs) to physical resources but poses security concerns as users relinquish physical possession of their computation and data. Good amount of research is initiated for resource provisioning on hypervisors, still many issues need to be addressed for security demanding and real time VMs. First work SRT-CreditScheduler (Secured and Real-time), maximizes the success rate by dynamically prioritizing the urgency and the workload of VMs but ensures highest security for all. Another work, SA-RT-CreditScheduler (Security-aware and Real-time) is a dual objective scheduler, which maximizes the success rate of VMs in best possible security range as specified by the VM owner. Though the algorithms can be used by any hypervisor, for the current work they have been implemented on Xen hypervisor. Their effectiveness is validated by comparing it with Xen's, Credit and SEDF scheduler, for security demanding tasks with stringent deadline constraints.

scholarly journals A review on various optimization techniques of resource provisioning in cloud computing

2019 ◽  
Vol 9 (1) ◽  
pp. 629
Author(s):  
K. Sumalatha ◽  
M. S. Anbarasi
Keyword(s):  
Cloud Computing ◽  
Resource Provisioning ◽  
Optimization Techniques ◽  
Application Performance ◽  
On Demand ◽  
Wide Range ◽  
Go Model ◽  
Uncertainty Parameters ◽  
The Cost ◽  
Research Avenue

<span lang="EN-US">Cloud computing is </span><span lang="EN-AU">the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet</span><span lang="EN-US">.It is a</span><span lang="EN-AU"> broad and deep platform that helps customers builds sophisticated, scalable applications.</span><span lang="EN-US"> To get the full benefits, research on a wide range of topics is needed. While resource over-provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning.</span>

A Secured Real Time Scheduling Model for Cloud Hypervisor

2019 ◽  
pp. 507-522
Author(s):  
Rekha Kashyap ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Cloud Computing ◽  
Success Rate ◽  
Real Time ◽  
Virtual Machines ◽  
Resource Provisioning ◽  
Real Time Scheduling ◽  
Scheduling Model ◽  
Physical Resources ◽  
Time Scheduling ◽  
Deadline Constraints

Virtualization is critical to cloud computing and is possible through hypervisors, which maps the Virtual machines((VMs) to physical resources but poses security concerns as users relinquish physical possession of their computation and data. Good amount of research is initiated for resource provisioning on hypervisors, still many issues need to be addressed for security demanding and real time VMs. First work SRT-CreditScheduler (Secured and Real-time), maximizes the success rate by dynamically prioritizing the urgency and the workload of VMs but ensures highest security for all. Another work, SA-RT-CreditScheduler (Security-aware and Real-time) is a dual objective scheduler, which maximizes the success rate of VMs in best possible security range as specified by the VM owner. Though the algorithms can be used by any hypervisor, for the current work they have been implemented on Xen hypervisor. Their effectiveness is validated by comparing it with Xen's, Credit and SEDF scheduler, for security demanding tasks with stringent deadline constraints.

scholarly journals A New Resources Provisioning Method Based on QoS Differentiation and VM Resizing in IaaS

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Rongdong Hu ◽  
Guangming Liu ◽  
Jingfei Jiang ◽  
Lixin Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Resource Provisioning ◽  
Application Performance ◽  
Qos Differentiation ◽  
Different Types ◽  
Speed Up ◽  
Google Cluster Trace ◽  
Real Time Application ◽  
Host Resource

In order to improve the host energy efficiency in IaaS, we proposed an adaptive host resource provisioning method, CoST, which is based on QoS differentiation and VM resizing. The control model can adaptively adjust control parameters according to real time application performance, in order to cope with changes in load. CoST takes advantage of the fact that different types of applications have different sensitivity degrees to performance and cost. It places two different types of VMs on the same host and dynamically adjusts their sizes based on the load forecasting and QoS feedback. It not only guarantees the performance defined in SLA, but also keeps the host running in energy-efficient state. Real Google cluster trace and host power data are used to evaluate the proposed method. Experimental results show that CoST can provide performance-sensitive application with a steady QoS and simultaneously speed up the overall processing of performance-tolerant application by 20~66%. The host energy efficiency is significantly improved by 7~23%.

Virtualization as the Enabling Technology of Cloud Computing

2018 ◽  
pp. 1174-1184
Author(s):  
Mohamed Fazil Mohamed Firdhous
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Resource Utilization ◽  
Operating Systems ◽  
Service Providers ◽  
Resource Provisioning ◽  
Enabling Technology ◽  
Server Virtualization ◽  
The Way

Cloud computing is the newest paradigm in computing that turned upside down the way of resource provisioning and payment. Cloud computing improves the resource utilization through virtualization enabling both customers as well as service providers to reap the benefits. Thus virtualization is the enabling technology that made this revolution possible. Through virtualization, it is possible to host multiple independent systems on a single hardware without interfering with each other. Server virtualization techniques can be grouped based how the underlying hardware and operating systems are presented to the users. In this chapter, the author takes an in depth look at how different virtualization has been implemented along with their security and quality of service issues.

Virtualization as the Enabling Technology of Cloud Computing

2019 ◽  
pp. 285-297
Author(s):  
Mohamed Fazil Mohamed Firdhous
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Resource Utilization ◽  
Operating Systems ◽  
Service Providers ◽  
Resource Provisioning ◽  
Enabling Technology ◽  
Server Virtualization ◽  
The Way

Cloud computing is the newest paradigm in computing that turned upside down the way of resource provisioning and payment. Cloud computing improves the resource utilization through virtualization enabling both customers as well as service providers to reap the benefits. Thus, virtualization is the enabling technology that made this revolution possible. Through virtualization, it is possible to host multiple independent systems on a single hardware without interfering with each other. Server virtualization techniques can be grouped based how the underlying hardware and operating systems are presented to the users. In this chapter, the author takes an in depth look at how different virtualization has been implemented along with their security and quality of service issues.

Enhancing the use of Object Based Contents Addressable Storage

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Simab Hasan Rizvi
Keyword(s):  
File System ◽  
Application Performance ◽  
Shared Storage ◽  
Data Intensive ◽  
Network Bandwidth ◽  
Storage Performance ◽  
Efficient Management ◽  
Object Based ◽  
Data Volume ◽  
Potential Benefits

In Today's age of Tetra Scale computing, the application has become more data intensive than ever. The increased data volume from applications, in now tackling larger and larger problems, and has fuelled the need for efficient management of this data. In this paper, a technique called Content Addressable Storage or CAS, for managing large volume of data is evaluated. This evaluation focuses on the benefits and demerits of using CAS it focuses, i) improved application performance via lockless and lightweight synchronization ofaccess to shared storage data, ii) improved cache performance, iii) increase in storage capacity and, iv) increase network bandwidth. The presented design of a CAS-Based file store significantly improves the storage performance that provides lightweight lock less user defined consistency semantics. As a result, this file system shows a 28% increase in read bandwidth and 13% increase in write bandwidth, over a popular file system in common use. In this paper the potential benefits of using CAS for a virtual machine are estimated. The study also explains mobility application for active use and public deployment.

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