Enhancing live virtual machine migration process via optimized resource allocation in next generation mobile edge network: A hybrid evolutionary approach

2020 ◽  
Vol 33 (12) ◽  
pp. e4442
Author(s):  
Asmita Roy ◽  
Sadip Midya ◽  
Koushik Majumder ◽  
Santanu Phadikar
Keyword(s):  
Resource Allocation ◽  
Virtual Machine ◽  
Evolutionary Approach ◽  
Next Generation ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Edge Network

scholarly journals QoS Guaranteed Resource Allocation for Live Virtual Machine Migration in Edge Clouds

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 78441-78451
Author(s):  
Lei Yang ◽  
Doudou Yang ◽  
Jiannong Cao ◽  
Yuvraj Sahni ◽  
Xiaohua Xu
Keyword(s):  
Resource Allocation ◽  
Virtual Machine ◽  
Virtual Machine Migration

Three Misuse Patterns for Cloud Computing

2013 ◽  
pp. 36-53 ◽  
Author(s):  
Keiko Hashizume ◽  
Nobukazu Yoshioka ◽  
Eduardo B. Fernandez
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Point Of View ◽  
Resource Usage ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
On Demand ◽  
Computing Model ◽  
Is Security

Cloud computing is a new computing model that allows providers to deliver services on demand by means of virtualization. One of the main concerns in cloud computing is security. In particular, the authors describe some attacks in the form of misuse patterns, where a misuse pattern describes how an attack is performed from the point of view of the attacker. Specially, they describe three misuse patterns: Resource Usage Monitoring Inference, Malicious Virtual Machine Creation, and Malicious Virtual Machine Migration Process.

Research on Trigger Strategy of Virtual Machine Dynamic Migration in Cloud Computing

2014 ◽  
Vol 926-930 ◽  
pp. 2084-2087
Author(s):  
Chun Ling An ◽  
Chun Lin Li ◽  
You Long Luo ◽  
Su Jie He
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Historical Data ◽  
Experimental Results ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Trigger Strategy ◽  
Double Threshold

According to the trigger strategy of virtual machine dynamic migration based on features closed in the process of dynamic migration of virtual machines in the cloud computing, this paper puts forward a double threshold trigger strategy using timing prediction based on historical data (DTS Algorithms). Then simulation on the CloudSim platform, and analyze the results of the experiment. Experimental results showed that in the system virtual machine migration using DTS algorithm can reduce the number of migration and the energy consumption during the migration process.

scholarly journals Energy Efficient VM Migration in Cloud Datacenter using Dolphin Echolocation Optimization with Tchebycheff Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 86-94 ◽  
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
System Performance ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Vm Migration ◽  
Multi Objective ◽  
Cloud Datacenter ◽  
Single Objective

The workload in cloud computing surroundings changes progressively delivering unwanted circumstances, for example, load unbalancing and minor usage. Virtual machine migration is an impressive plan in such circumstances inorder to improve system performance. With a specific end goal to give productive energy virtual machine migration is essential that migrates a running virtual machine without disconnecting the client or application. In any case, an algorithm in view of a single objective is generally familiar with to coordinate the migration process. Unexpectedly, there stay alive unconsidered variables affecting the migration process, for example, burden capacity, power utilization and resource wastage. We offer a multi-objective algorithm for obtaining VM migration by evaluating the multi objectives that are responsible for migration overhead. In this manner, we suggest a narrative relocation approach united by a Multi objective Dolphin Echolocation Optimization Algorithm (MO-DEOA) to assess several objectives. The aim is to efficiently obtain improved migration that concurrently diminishes power consumption by guaranteeing the performance of the system.

A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

2017 ◽  
Vol 7 (9) ◽  
pp. 30 ◽  
Author(s):  
Ramandeep Kaur
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Heuristic Algorithms ◽  
Hybrid Approach ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Bee Colony ◽  
Effective Manner ◽  
Effective Performance

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

A virtual machine migration scheme toward Green Cloud

2014 ◽  
Author(s):  
Liu-Mei Zhang ◽  
Jian-Feng Ma ◽  
Di Lu ◽  
Yi-Chuan Wang
Keyword(s):  
Virtual Machine ◽  
Virtual Machine Migration ◽  
Green Cloud

A Virtual Machine Migration Approach in Cloud to Optimize Resource Utilization

2018 ◽  
Vol 9 (4) ◽  
pp. 309-317
Author(s):  
Damodar Tiwari ◽  
Shailendra Singh ◽  
Sanjeev Sharma
Keyword(s):  
Resource Utilization ◽  
Virtual Machine ◽  
Virtual Machine Migration

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Sign in / Sign up

Export Citation Format

Share Document