Using Logistic Regression to Improve Virtual Machines Management in Cloud Computing Systems

2017 ◽  
Author(s):  
Manar Bani Issa ◽  
Mustafa Daraghmeh ◽  
Yaser Jararweh ◽  
Mahmoud Al-Ayyoub ◽  
Mohammad Alsmirat ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Logistic Regression ◽  
Virtual Machines ◽  
Computing Systems

A simplified reliability analysis method for cloud computing systems considering common-cause failures

2017 ◽  
Vol 231 (3) ◽  
pp. 324-333 ◽  
Author(s):  
Ruiying Li ◽  
Qiong Li ◽  
Ning Huang ◽  
Rui Kang
Keyword(s):  
Cloud Computing ◽  
State Space ◽  
Reliability Analysis ◽  
Virtual Machines ◽  
Single Server ◽  
Analysis Method ◽  
Computing Systems ◽  
Common Cause ◽  
Cloud Computing System ◽  
Common Cause Failures

Virtualization is one of the main features of cloud computing systems, which enables building multiple virtual machines on a single server. However, this feature brings new challenge in reliability modeling, as the failure of the server will make all its co-located virtual machines inoperable, which is a typical common-cause failure. To satisfy the demand of the cloud computing system, the reliability of the system is defined as the probability that at least a given number of virtual machines are operable. State-space enumeration is one method to calculate such reliability; however, due to the large number of combinations, it is time-consuming and impractical. To solve this problem, we propose a simplified reliability analysis method based on fault tree and state-space models. Two illustrative examples are studied to show the process and the effectiveness of our method. State enumeration and Monte Carlo simulation are also used to prove the correctness of our method as back-to-back verifications. Compared to the reliability analysis without considering common-cause failures, our results are quite different, which illustrates the necessity of considering common-cause failures in the reliability of cloud computing systems.

scholarly journals Heuristic-based Approach for Dynamic Consolidation of Software Licenses in Cloud Data Centers

2021 ◽  
Vol 13 (6) ◽  
pp. 1-12
Author(s):  
Leila Helali ◽  
◽  
Mohamed Nazih Omri
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Energy Aware ◽  
Computing Systems ◽  
Cloud Data ◽  
Software Licenses ◽  
Cloud Data Centers ◽  
Distributed Cloud

Since its emergence, cloud computing has continued to evolve thanks to its ability to present computing as consumable services paid by use, and the possibilities of resource scaling that it offers according to client’s needs. Models and appropriate schemes for resource scaling through consolidation service have been considerably investigated,mainly, at the infrastructure level to optimize costs and energy consumption. Consolidation efforts at the SaaS level remain very restrained mostly when proprietary software are in hand. In order to fill this gap and provide software licenses elastically regarding the economic and energy-aware considerations in the context of distributed cloud computing systems, this work deals with dynamic software consolidation in commercial cloud data centers 𝑫𝑺𝟑𝑪. Our solution is based on heuristic algorithms and allows reallocating software licenses at runtime by determining the optimal amount of resources required for their execution and freed unused machines. Simulation results showed the efficiency of our solution in terms of energy by 68.85% savings and costs by 80.01% savings. It allowed to free up to 75% physical machines and 76.5% virtual machines and proved its scalability in terms of average execution time while varying the number of software and the number of licenses alternately.

scholarly journals ENHANCED DYNAMIC RESOURCE ALLOCATION SCHEME BASED ON PACKAGE LEVEL ACCESS IN CLOUD COMPUTING : A REVIEW

2017 ◽  
Vol 16 (2) ◽  
pp. 6207-6212 ◽  
Author(s):  
Manpreet Kaur ◽  
Dr. Rajinder Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Heterogeneous Computing ◽  
Virtual Machines ◽  
Technology Infrastructure ◽  
Computing Systems ◽  
Computing Platform ◽  
Internet Users ◽  
Resource Allocation Scheme ◽  
Heterogeneous Computing Systems

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. On cloud computing platform, load balancing of the entire system can be  dynamically handled  by  using  virtualization  technology through which it  becomes  possible  to  remap  virtual  machine  and physical resources  according  to  the  change  in  load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically.  The  load balancing  with  proper  allocation  of  resources  must  be guaranteed  in  order  to  improve  resource  utility.

scholarly journals An efficient algorithm for monitoring virtual machines in clouds

2019 ◽  
Vol 8 (2) ◽  
pp. 699-705
Author(s):  
Sultan Alshamrani
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Efficient Algorithm ◽  
Virtual Machines ◽  
End Users ◽  
Round Robin ◽  
Computing Systems ◽  
Cloud Systems ◽  
Increasing Demand ◽  
Set Up

Cloud computing systems consist of a pool of Virtual Machines (VMs), which are installed physically on the provider's set up. The main aim of the VMs is to offer the service to the end users. With the current increasing demand for the cloud VMs, there is always a huge requirement to secure the cloud systems. To keep these cloud systems secured, they need a continuous and a proper monitoring. For the purpose of monitoring, several algorithms are available with FVMs. FVM is a forensic virtual machine which monitors the threats among the VMs. Our formulated algorithm runs on FVM. In this paper, we formulate the Random-Start-Round-Robin algorithm for monitoring inside FVM.

scholarly journals A Load Balancing Algorithm for Mobile Devices in Edge Cloud Computing Environments

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 686
Author(s):  
JongBeom Lim ◽  
DaeWon Lee
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Mobile Devices ◽  
Virtual Machines ◽  
Hot Spot ◽  
Mobile User ◽  
Current Data ◽  
Computing Systems ◽  
Computing Environments ◽  
Load Balancing Algorithm

As current data centers and servers are growing in size by orders of magnitude when needed, load balancing is a great concern in scalable computing systems, including mobile edge cloud computing environments. In mobile edge cloud computing systems, a mobile user can offload its tasks to nearby edge servers to support real-time applications. However, when users are located in a hot spot, several edge servers can be overloaded due to suddenly offloaded tasks from mobile users. In this paper, we present a load balancing algorithm for mobile devices in edge cloud computing environments. The proposed load balancing technique features an efficient complexity by a graph coloring-based implementation based on a genetic algorithm. The aim of the proposed load balancing algorithm is to distribute offloaded tasks to nearby edge servers in an efficient way. Performance results show that the proposed load balancing algorithm outperforms previous techniques and increases the average CPU usage of virtual machines, which indicates a high utilization of edge servers.

scholarly journals A Review on Load Balancing In Cloud Environment

2018 ◽  
Vol 17 (1) ◽  
pp. 7120-7125 ◽  
Author(s):  
Amandeep Kaur ◽  
Mr. Pawan Luthra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Heterogeneous Computing ◽  
Virtual Machines ◽  
Technology Infrastructure ◽  
Computing Systems ◽  
Computing Platform ◽  
Internet Users ◽  
Cloud Computing Platform ◽  
Heterogeneous Computing Systems

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. On cloud computing platform, load balancing of the entire system can be  dynamically handled  by  using  virtualization  technology through which it  becomes  possible  to  remap  virtual  machine  and physical resources  according  to  the  change  in  load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically.  The  load balancing  with  proper  allocation  of  resources  must  be guaranteed  in  order  to  improve  resource  utility.

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