CIS Seminar - Two Talks on Wireless Sensor Networks
3:00 PM, Wednesday March 2 2016
235 Weir Hall
Talk1: Survey on Swarm Intelligence based Routing Protocols for Wireless Sensor Networks -- An Extensive Study
Abstract: Swarm Intelligence (SI) techniques have been widely used in the science and engineer domains such as Mobile Ad Hoc Networks (MANETs) and Wireless Sensor Networks (WSNs). It is a relatively novel and promising field, focusing on the adaptation of collective behaviors of various natural creatures like ants, fish, birds, and honey bees, and a large number of routing protocols for WSNs have been developed according to the inspiration from the foraging behaviors of these species. In this talk, I will first discuss the general principle of swarm intelligence and survey the research efforts on these Swarm Intelligence based protocols according to various promising meta-heuristics. In the second part of the talk, I will present the properties of termite colony optimization and fission-fusion social structure based spider monkey optimization based clustering in WSNs. Last, I will conclude the work with a comparative analysis, pointing out the fundamental issues and potential future directions.
Bio: Tina Gui is a Ph.D. student in the Department of Computer and Information Science at the University of Mississippi, who is currently a research assistant in the Bioinformatics Research Group under supervision of Professor Dawn E. Wilkins and Professor Yixin Chen. Tina received her MS degree in Computer Science from University of Mississippi and BS degree from California State University. Her research interests include machine learning, data mining, computational biology and wireless sensor networks.
Talk2: On Wireless Video Sensor Network Deployment for3D Indoor Space Coverage
Abstract: Nowadays, wireless video sensor networks (WVSNs) play a prominent role in a wide range of security, industrial, medical and environmental applications. Unlike traditional sensors such as heat or light sensors often considered with omnidirectional sensing range, the sensing range of a video sensor can be deemed as a fan-shape in 2D and pyramid-shape in 3D, rendering the deployment solutions for traditional sensors and 2D sensing field inapplicable and incapable of solving the WVSN deployment problem for 3D indoor space coverage. In this talk, we take the first attempt to address this by modeling the general problem in a continuous space and strive to minimize the number of required video sensors to cover the given 3D regions. We then convert it into a discrete version by incorporating 3D grids for our discrete model, which can achieve arbitrary approximation precision by adjusting the grid granularity. We propose a greedy heuristic and an enhanced Depth First Search (DFS) algorithm to solve the discrete version problem where the latter, if given enough time can return the optimal solution. Our preliminary evaluation results demonstrate that our greedy heuristic can reduce the required video sensors by up to 50% over a baseline algorithm, and our enhanced DFS can achieve an additional reduction of video sensors by up to 20%.
Bio: Tisha Brown is a current Ph.D. candidate in the CS department at OleMiss. She received a MS degree in Computer Science from Jackson State University and a BS degree in Computer Science from Mississippi Valley State University. Mrs. Brown is a former Mississippi Space Grant Consortium, McNair and SREB Fellow. In 2014, she joined Dr. Wang’s Future Computer Networking Research Group. Tisha’s current research topic is Wireless Video Sensor Networks specifically to improve and optimize the deployment, coverage and communication traffic in an indoor 3D space environment. Tisha is currently completing the Prospectus proposal while serving as a graduate instructor and Turning Technologies intern this semester.