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Virtualization is becoming more and more important in the science of living things, enabling group of devices made up of smaller parts and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images. In virtualization grid point of view, we discussed about relationship among Application Layer, Grid Middleware and Network Layers and also the limitations of using grids. And for experimantal setup or for practical analysis, we deployed Virtual Machine in NUTSHELL in which the properties of VM and also calculated the perfomacnce metrics based on different constituents like Querying, Copying, Pausing, Unpausing etc… are being discussed. However, virtual machines are very much useful in bio appliactions to abstarct diferent physical resources to enable multiple instances of software to utilize the same resources.
VMM, VMManager, VM Repository, OGSA, OGSI, GRAM, RSL
About Virtual Machines For any virtual machine to work, it has to be emulated. As many people will know, for a machine to work there is need for hardware and software (OS which consists of SHELL and kernel). Hence for hardware we allot some memory and processing power (RAM) to virtual machine we want to run. Now coming to software it can be three types. i.e., Software emulation, Hardware emulation and NO emulation. In case of software emulation, there is one more layer on the top of Host Kernel called Hypervisor. It is like a manager, which would handle all the virtual machines running on it. Each virtual machine would have its own kernel and OS. Example: Virtual Box In Hardware emulation we don’t have Hypervisor, the host kernel is shared by all the virtual machines running on it. As a result of this we have overhead and more number of VMs can be run as compared to software emulation. This emulation is very useful to make virtual network in terms of memory and processing. Example: UML. About Bio-Informatics: Bio-Informatics is concerned with cellular related things. Example: Molecular Biology, Computational Biology etc. It is used to describe the whole larger field of which includes clinical informatics like creating, using data from clinical systems etc. And another thing about bioinformatics dealt with normalization of data. Bio-Informatics people are constantly dealing with hodgepodge of different data structures. The pain one has to undergo when integrating one biological database with another becomes complicated. Some bio informatics services are only accessible with perl, others with java, then again one need R and recently also should be proficient in python too. In short there is lot of overhead in doing Bioinformatics the old way.
To conclude with, many researchers of life sciences lack knowledge in the area of informatics expertise in which they can be able to install all the necessary components to run complex workflow analysis, where Virtual Machines plays very important role in providing great assistance for complex systems. For example, if scientists want to run different analysis like proteomics, RNS Sequence analysis, they can simply download and switch/migrate among images without reconfiguring the computers once again. And by the way, Virtual Machines are getting popular in bioinformatics arena. Furthermore, one can discuss about security aspects of Virtual Machine with respect to Bioinformatics.
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