Analyzing live migration energy overhead in cloud computing: A survey

2017 ◽  
Author(s):  
Salma K. Elbay ◽  
Islam Hegazy ◽  
El-Sayed M. El-Horabty
Keyword(s):  
Cloud Computing ◽  
Migration Energy ◽  
Live Migration

Research on Energy-Saving Algorithms with Migration Energy Consumption in Heterogeneous Cloud Environment

2014 ◽  
Vol 986-987 ◽  
pp. 1383-1386
Author(s):  
Zhen Xing Yang ◽  
He Guo ◽  
Yu Long Yu ◽  
Yu Xin Wang
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Large Scale ◽  
Electrical Energy ◽  
Cloud Environment ◽  
Migration Energy ◽  
Live Migration ◽  
Large Scale Data ◽  
Heterogeneous Cloud

Cloud computing is a new emerging paradigm which delivers an infrastructure, platform and software as services in a pay-as-you-go model. However, with the development of cloud computing, the large-scale data centers consume huge amounts of electrical energy resulting in high operational costs and environment problem. Nevertheless, existing energy-saving algorithms based on live migration don’t consider the migration energy consumption, and most of which are designed for homogeneous cloud environment. In this paper, we take the first step to model energy consumption in heterogeneous cloud environment with migration energy consumption. Based on this energy model, we design energy-saving Best fit decreasing (ESBFD) algorithm and energy-saving first fit decreasing (ESFFD) algorithm. We further provide results of several experiments using traces from PlanetLab in CloudSim. The experiments show that the proposed algorithms can effectively reduce the energy consumption of data center in the heterogeneous cloud environment compared to existing algorithms like NEA, DVFS, ST (Single Threshold) and DT (Double Threshold).

Live migration improvements by related dirty memory prediction in cloud computing

2017 ◽  
Vol 90 ◽  
pp. 83-89 ◽  
Author(s):  
Tin-Yu Wu ◽  
Nadra Guizani ◽  
Jhih-Siang Huang
Keyword(s):  
Cloud Computing ◽  
Live Migration ◽  
Memory Prediction

scholarly journals PEMILIHAN DAN MIGRASI VM MENGGUNAKAN MCDM UNTUK PENINGKATAN KINERJA LAYANAN PADA CLOUD COMPUTING

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdullah Fadil ◽  
Waskitho Wibisono
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Data Center ◽  
Response Times ◽  
Multi Criteria Decision Making ◽  
Live Migration ◽  
Vm Placement ◽  
Cloud Data Center ◽  
Cloud Data

Komputasi awan atau cloud computing merupakan lingkungan yang heterogen dan terdistribusi, tersusun atas gugusan jaringan server dengan berbagai kapasitas sumber daya komputasi yang berbeda-beda guna menopang model layanan yang ada di atasnya. Virtual machine (VM) dijadikan sebagai representasi dari ketersediaan sumber daya komputasi dinamis yang dapat dialokasikan dan direalokasikan sesuai dengan permintaan. Mekanisme live migration VM di antara server fisik yang terdapat di dalam data center cloud digunakan untuk mencapai konsolidasi dan memaksimalkan utilisasi VM. Pada prosedur konsoidasi vm, pemilihan dan penempatan VM sering kali menggunakan kriteria tunggal dan statis. Dalam penelitian ini diusulkan pemilihan dan penempatan VM menggunakan multi-criteria decision making (MCDM) pada prosedur konsolidasi VM dinamis di lingkungan cloud data center guna meningkatkan layanan cloud computing. Pendekatan praktis digunakan dalam mengembangkan lingkungan cloud computing berbasis OpenStack Cloud dengan mengintegrasikan VM selection dan VM Placement pada prosedur konsolidasi VM menggunakan OpenStack-Neat. Hasil penelitian menunjukkan bahwa metode pemilihan dan penempatan VM melalui live migration mampu menggantikan kerugian yang disebabkan oleh down-times sebesar 11,994 detik dari waktu responnya. Peningkatan response times terjadi sebesar 6 ms ketika terjadi proses live migration VM dari host asal ke host tujuan. Response times rata-rata setiap vm yang tersebar pada compute node setelah terjadi proses live migration sebesar 67 ms yang menunjukkan keseimbangan beban pada sistem cloud computing.

scholarly journals VM Consolidation and Migration for IAAS In Cloud Storage

2020 ◽  
pp. 552-560
Author(s):  
Saravanan S
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Resource Provisioning ◽  
Live Migration ◽  
Enabling Technology ◽  
Huge Amount ◽  
Physical Infrastructure ◽  
And Migration ◽  
Business Customers ◽  
Vm Consolidation

Cloud computing is capable of handling a huge amount of growing work in a predestined manner for the usage of the business customers. The main enabling technology for cloud computing is virtualization which generalize the physical infrastructure and makes it easy to use and manage. In this project virtualization is used to allocate resources based on their needs and also supports green computing concept. “Skewness” concept is introduced here in which the same is minimized to combine various workloads to improve the utilization of the server. Managing the customer demand creates the challenges of on demand resource allocation. So can implement Virtual Machine (VM) technology has been employed for resource provisioning. It is expected that using virtualized environment will reduce the average job response time as well as executes the task according to the availability of resources. Hence VMs are allocated to the user based on characteristics of the job. The VM live migration technology makes the VM and PM (Physical machine) mapping possible when the execution is running.

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