WSNs being energy constrained systems, one major problem is to employ the sensor nodes in such a manner so as to ensure maximum coverage and connectivity with minimal or optimal number of nodes and furthermore elongate network lifetime with maximum energy utilization.
The problem addressed has been tackled for 1-D linear array and further extended to 2-Dimensions as stated in the next slides.
Traveling Salesperson Problem
Our branch-and-strategy splits a branch and bound solution into two groups:
one group including a particular arc and the other excluding this arc.
1.Each splitting incurs a lower bound and we shall traverse the searching tree with the "lower" lower bound.
2.If a constant subtracted from any row
or any column of the cost matrix, an
optimal solution does not change.
) Compression using huffman code
-with a number of bits k per code word
-provide huffman table
Huffman coding is optimal for a symbol-by-symbol coding with a known input probability distribution.This technique uses a variable-length code table for encoding a source symbol. The table is derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol .Huffman coding uses a specific method for representing each symbol, resulting in a prefix code that expresses the most common characters using shorter strings of bits than those used for less common source symbols.The Huffman coding is a procedure to generate a binary code tree.
MATSNL is a package of MATLAB M-files for computing wireless sensor node lifetime/power budget and solving optimal node architecture choice problems. It is intended as an analysis and simulation tool for researchers and educators that are easy to use and modify. MATSNL is designed to give the rough power/ lifetime predictions based on node and application specifications while giving useful insight on platform design for the large node lifetime by providing side-by-side comparison across various platforms. The MATSNL code and manual can be found at the bottom of this page. A related list of publications describing the models used in MATSNL is posted on the ENALAB part of the 2 project at http://www.eng.yale.edu/enalab/aspire.htm
The emphasis of this book is on real-time application of Synopsys tools, used
to combat various problems seen at VDSM geometries. Readers will be
exposed to an effective design methodology for handling complex, submicron
ASIC designs. Significance is placed on HDL coding styles,
synthesis and optimization, dynamic simulation, formal verification, DFT
scan insertion, links to layout, physical synthesis, and static timing analysis.
At each step, problems related to each phase of the design flow are identified,
with solutions and work-around described in detail. In addition, crucial issues
related to layout, which includes clock tree synthesis and back-end
integration (links to layout) are also discussed at length. Furthermore, the
book contains in-depth discussions on the basics of Synopsys technology
libraries and HDL coding styles, targeted towards optimal synthesis solution.
The NetBeans IDE has seen adoption snowballing over the past
years, particularly with the introduction of a completely new,
rewritten, slick Java editor. You’ll fnd this reference card helpful
if you want to get as much out of the Java editor as its authors
intended when creating it. It lists all the keyboard shortcuts in carefully thought out categories and it provides a thorough
exposition of optimal handling of Java code in the editor,
covering viewing, navigation, source handling, and refactoring.
Get NetBeans IDE: http://www.netbeans.org/downloads
MATSNL is a package of MATLAB M-files for computing wireless sensor node
lifetime/power budget and solving optimal node architecture choice problems. It is intended
as an analysis and simulation tool for researchers and educators that are easy to use and
modify. MATSNL is designed to give the rough power/ lifetime predictions based on node
and application specifications while giving useful insight on platform design for the large
node lifetime by providing side-by-side comparison across various platforms.
sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.
Commercially available active noise control headphones rely on fixed analog controllers to drive "anti-noise" loudspeakers. Our design uses an adaptive controller to optimally cancel unwanted acoustic noise. This headphone would be particularly useful for workers who operate or work near heavy machinery and engines because the noise is selectively eliminated. Desired sounds, such as speech and warning signals, are left to be heard clearly. The adaptive control algorithm is implemented on a Texas Instruments (TI™ )
1
TMS320C30GEL digital signal processor (DSP), which drives a Sony CD550 headphone/microphone system. Our experiments indicate that adaptive noise control results in a dramatic improvement in performance over fixed noise control. This improvement is due to the availability of high-performance programmable DSPs and the self-optimizing and tracking
capabilities of the adaptive controller in response to the surrounding noise.
We introduce a sub-cell WENO reconstruction method to evaluate spatial derivatives in the high-order ADER scheme. The basic idea in our reconstruction is to use only r stencils to reconstruct the point-wise values of solutions and spatial derivatives for the 2r-1 th order
ADER scheme in one dimension, while in two dimensions, the dimension-by-dimension sub-cell reconstruction approach for spatial derivatives is employed. Compared with the original ADER scheme of Toro and Titarev (2002) [2] that uses the direct derivatives of reconstructed polynomials for solutions to evaluate spatial derivatives, our method not only reduces greatly the computational costs of the ADER scheme on a given mesh,
but also avoids possible numerical oscillations near discontinuities, as demonstrated by a number of one- and two-dimensional numerical tests. All these tests show that the 5th-order ADER scheme based on our sub-cell reconstruction method achieves the desired accuracy, and is essentially non-oscillatory and computationally cheaper for problems with discontinuities.
