Posted by Hemprasad Y. Badgujar on August 30, 2014
“Mobile Cloud Computing at its simplest, refers to an infrastructure where both the data storage and the data processing happen outside of the mobile device. Mobile cloud applications move the computing power and data storage away from mobile phones and into the cloud, bringing applications and mobile computing to not just smartphone users but a much broader range of mobile subscribers”.
From the concept of MCC, the general architecture of MCC can be shown in Fig. In Fig. , mobile devices are connected to the mobile networks via base stations (e.g., base transceiver station (BTS), access point, or satellite) that establish and control the connections (air links) and functional interfaces between the networks and mobile devices. Mobile users’ requests and information (e.g., ID and location) are transmitted to the central processors that are connected to servers providing mobile network services. Here, mobile network operators can provide services to mobile users as AAA (for authentication, authorization, and accounting) based on the home agent (HA) and subscribers’ data stored in databases. After that, the subscribers’ requests are delivered to a cloud through the Internet. In the cloud, cloud controllers
process the requests to provide mobile users with the corresponding cloud services. These services are Accepted in Wireless Communications and Mobile Computing -developed with the concepts of utility computing, virtualization, and service-oriented architecture (e.g.,web, application, and database servers).
Posted in CLOUD, Computer Network & Security, Computer Software, Computing Technology | Tagged: GPU Computing, installation | Leave a Comment »
Posted by Hemprasad Y. Badgujar on January 3, 2014
Installing CUDA Toolkit 5.5 on Ubuntu 12.10 Linux
The following explains how to install CUDA Toolkit 5.5 on 64-bit Ubuntu 12.10 Linux. I have tested it on a self-assembled desktop with AMD Phenom II X4 CPU, 4GB RAM, 500GB hard drive, 650W power supply, and NVIDIA GeForce GTX 550 Ti graphics card. The instruction assumes you have the necessary CUDA compatible hardware support. Depending on your system configuration, your mileage may vary.
Retrieve the CUDA repository package for Ubuntu 12.10 from the CUDA download site and install it in a terminal.
$ sudo dpkg –i
$ sudo apt-get update
Linux Kernel Header
Then you need to install the necessary Linux kernel headers.
$ sudo apt-get install linux
Proprietary Video Driver
The built-in nouveau video driver in Ubuntu is incompatible with the CUDA Toolkit, and you have to replace it with the proprietary NVIDIA driver.
$ sudo apt-get remove –purge \
$ sudo apt-get install nvidia
You can reboot the system afterwards and verify the driver installation with the nvidia-settings utility.
Then you can install the CUDA Toolkit using apt-get.
$ sudo apt-get install cuda
As part of the CUDA environment, you should add the following in the .bashrc file of your home folder.
CUDA SDK Samples
Now you can copy the SDK samples into your home directory, and proceed with the build process.
If everything goes well, you should be able to verify your CUDA installation by running thedeviceQuery sample in bin/linux/release.
Posted in Computer Languages, Computing Technology, CUDA, GPU (CUDA), PARALLEL | Tagged: GPU, GPU Computing, Security, Ubuntu, Ubuntu Software Center, Universal Studios | Leave a Comment »
Posted by Hemprasad Y. Badgujar on May 29, 2013
P0212 GPU Acceleration In Multilayer Parallel User Authentication Schemes By Optimizing Hardware Use
Hemprasad Badgujar (Hardsoft)
Posted in Mixed | Tagged: Authentication, GPU, GPU Computing, parallel computing, Security | 1 Comment »