Electrical and Computer Engineering

College of Engineering and Applied Science

Dr. Suresh Muknahallipatna's Research

> Visit Dr. Muknahallipatna's webpage

Computer Networks and High Performance Computing (HPC)

Storage Area Networks:

The ever-increasing demand for fast and reliable data storage has led to a storage system known as a storage area network (SAN). A SAN is a storage network that connects servers to storage through a network known as a fabric. The fabric is based either on the Fiber Channel (FC) or Fast Ethernet protocol and is most often composed of fiber optic devices. The devices of a fabric run at high data rates, 1Gbps to 40Gbps, with very low losses. Medium sized SANs have been a common implementation for data storage in enterprise data centers, but with the increasing demand for data storage the SANs have developed into distributed SANs (DSANs). Dr. Muknahallipatna and his graduate students are performing research in analyzing the stability and scalability of SANs. The outcome of the research has been the development of discrete event simulators and hardware simulator to test SANs.

 

Mobile Adhoc Network

The Mobile Adhoc network (MANET) provides the capability to rapidly deploy a communication network for applications like battlefield communications, collection of environmental data for natural system analysis to mention a few.  A MANET consists of mobile nodes forming a network to relay information across the network. However, developing a communication network infrastructure on an ad-hoc basis, poses significant technology challenges including design and fielding of antennas, radios, terminals, and higher-layer communications protocols. Some of the fundamental challenges of an ad-hoc network include harsh radio frequency (RF) propagation environments, spectrum limitations, varying degrees of terminal (node) mobility, scalability, energy consumption, network lifetime, self-healing, localization, and routing.
Dr. Muknahallipatna and a team of collaborators are addressing this technological challenges and the outcome of the research can be found at http://www.uwyo.edu/electrical/research/signal-processing.html

 

High Performance Computing

GPGPU based HPC is a new approach to achieve Super Computer computing capabilities at minimal cost. This involves developing parallel software satisfying the graphical processing unit (GPU) architecture to achieve high computation speedups. Recently, Dr. Muknahallipatna and a team of collaborators have developed parallel algorithms in the area of computer vision, radio propagation maps and snow modeling to execute on a GPGPU cluster. These parallel algorithms are useful in applications like real-time remote rehabilitation, real-time terrain based radio propagation map generation and flood forecasting