Modelling the Live Migration Time of Virtual Machines

2015 ◽  
pp. 575-593 ◽  
Author(s):  
Kateryna Rybina ◽  
Waltenegus Dargie ◽  
Subramanya Umashankar ◽  
Alexander Schill
Keyword(s):  
Virtual Machines ◽  
Migration Time ◽  
Live Migration

Analytical Approach to Estimating Total Migration Time of Virtual Machines With Various Applications

2020 ◽  
Vol 11 (2) ◽  
pp. 58-75
Author(s):  
Andrew Toutov ◽  
Anatoly Vorozhtsov ◽  
Natalia Toutova
Keyword(s):  
Analytical Approach ◽  
Virtual Machines ◽  
Migration Time ◽  
Characteristic Functions ◽  
Live Migration ◽  
File Storage ◽  
Laguerre Series ◽  
Cloud Applications ◽  
Total Migration

Cloud applications and services such as social networks, file sharing services, and file storage have become increasingly popular among users in recent years. This leads to the enlargement of data centers, and an increase in the number of servers and virtual machines. In such systems, live migration is used to move virtual machines from one server to another, which affects the quality of service. Therefore, the problem of finding the total migration time is relevant. This article proposes analytical approach to obtaining analytical expression of the probability density of the total migration time based on the use of the apparatus of characteristic functions. The obtained expression is used to calculate characteristics of migration, taking into account the applications contributing the most randomness to the total migration time. To simplify the calculation of migration characteristics, the use of the Laguerre series can be recommended as giving more reliable results compared to Gram-Charlier series.

ABDM : Agent Based Live Migration of Virtual Machines in Cloud Computing For Multimedia Data

2018 ◽  
pp. 9-17
Author(s):  
K. Syed Ibrahim ◽  
Dr. A. R. Mohamed Shanavas
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Exit Time ◽  
Multimedia Data ◽  
Migration Time ◽  
Source Node ◽  
Destination Node ◽  
Live Migration ◽  
Agent Based ◽  
Total Migration

Migration time is one of the metric to measure the performance of the algorithm for live migration. In this paper we have introduced a new parameter for live migration of virtual machines (VM) called the ‘Exit Time’ which is defined as the time to eject the state of one or more VMs from the source node. Exit Time defines how rapidly the VM can be taken out from the source node and its resources are freed for reallocating other tasks. We present an Agent Based Live Migration which disconnects the source node from the destination node during migration to reduce the exit time if the destination is slow. The source distributes the memory of VMs to multiple intermediate nodes organized by a middleware. Simultaneously, the destination collects and merges the VMs’ memory from the intermediate nodes. Thus exit from the source node is no longer resisted by the receiving speed of the destination. We support simultaneous live exit of multiple VMs and our ABDM implementation in the CloudSim platform reduces the exit time by a considerable amount against the traditional pre-copy and post-copy migration at the same time keeping the total migration time when the destination node is sluggish than the source

Adaptive Downtime for Live Migration of Virtual Machines

2014 ◽  
Author(s):  
Francisco J. Clemente-Castello ◽  
Juan Carlos Fernandez ◽  
Rafael Mayo ◽  
Enrique S. Quintana-Orti
Keyword(s):  
Virtual Machines ◽  
Live Migration

scholarly journals Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

2022 ◽  
Vol 71 (2) ◽  
pp. 3019-3033
Author(s):  
Tahir Alyas ◽  
Iqra Javed ◽  
Abdallah Namoun ◽  
Ali Tufail ◽  
Sami Alshmrany ◽  
...  
Keyword(s):  
Fuzzy Inference System ◽  
Virtual Machines ◽  
Fuzzy Inference ◽  
Live Migration ◽  
Inference System ◽  
Mamdani Fuzzy Inference System
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