158009
Threshold optimization algorithm for weak signal in distributed-sensor fusion system
Distributed order statistics constant false alarm rate (OS-CFAR) detection techniques are important for nonstationary observation with varying weak narrowband random signals. However, it is very difficult to choose system parameters to obtain optimal threshold values at the fusion center because of the nonlinear property of distributed OS-CFAR detection system. This paper provides a novel solution based on an effective and flexible genetic algorithm. Using this approach, all system parameters are directly coded in decimal chromosomes and they can be optimized simultaneously. Furthermore, we also derive the more general model by implementing the K fusion rules. The simulation results show that applying the proposed approach one can achieve comparable performances with the reported methods and results.
27140699
Differential Algebraic Method for Aberration Analysis of Electron Optical Systems
Differential algebraic method is a powerful technique in computer numerical analysis. It presents a straightforward method for computing arbitrary order derivatives of functions with extreme high accuracy limited only by the machine error. When applied to nonlinear dynamics systems, the arbitrary high order transfer properties of the system can be derived directly. In this paper, the principle of differential algebraic method is applied to calculate high order aberrations of electron optical systems. As an example, an electrostatic lens with an analytical expression has been calculated using this method. Relative errors of the Gaussian properties and spherical aberration coefficient of the lens compared with the analytic solutions are of the order 10− 11 or smaller. It is proved that differential algebraic aberration method is very helpful with high accuracy for high order aberration analysis and computation of electron optical systems.
161273
Dynamic power management for streaming data
This paper presents a method that uses data buffers to smoothen request variations and to create long idleness for power management. This method considers the power consumed by the buffers and assigns an energy penalty for buffer underflow. Our approach provides analytic formulas for calculating the optimal buffer sizes and the amount of data to store in the buffers. We use video prefetching as a case study and obtain power savings of more than 74% for MPEG-1 and 34% for MPEG-2 videos.
2733921
Joint power management of memory and disk
The paper presents a scheme to combine memory and power management for achieving better energy reduction. Our method periodically adjusts the size of physical memory and the timeout value to shut down a hard disk for reducing the average power consumption. We use Pareto distributions to model the distributions of idle time. The parameters of the distributions are adjusted at run-time for calculating the corresponding timeout value of the disk power management. The memory size is changed based on the inclusion property to predict the number of disk accesses at different memory sizes. Experimental results show more than 50% energy savings compared to a 2-competitive fixed-timeout method.
1182896
Power Reduction of Multiple Disks Using Dynamic Cache Resizing and Speed Control
This paper presents an energy-conservation method for multiple disks and their cache memory. Our method periodically resizes the cache memory and controls the rotation speeds under performance constraints. The cache memory stores the data from the disks for reuse. Enlarging the cache memory reduces disk accesses and disk utilization. This allows the disks to reduce their speeds and conserve energy because the disks' power consumption is quadratic to their speeds. However, the cache memory itself consumes power to retain data. Shrinking cache memory can save memory power while increasing disk accesses and degrading performance. Choosing proper cache sizes and rotation speeds can reduce the energy consumption of both memory and disks with satisfactory performance. We model cache resizing and speed setting as an optimization problem with minimizing the power consumption as objective and limiting disk utilization as constraints. We compare our method with the methods resizing cache based on request rates. The simulation results show that our method achieves better energy-savings while limiting disk access latency
7907707
Fast search in DNA sequence databases using punctuation and indexing
Exact pattern searching in DNA sequence databases has applications in identification of highly conserved regulatory sequences, the design of hybridization probes, and improving performance of approximate homology searching tools such as BLAST and BLAT. We propose a new pattern searching algorithm, Compressed-Punctuated-Boyer-Moore (cp-BM), to enhance exact pattern match searches of DNA sequences. cp-BM encodes two bits to represent each A, T, C, G character (4-character 8 bit (4C8B) compression), plus punctuator characters to indicate unambiguously the encoding frame of the compressed target sequence, thereby solving the misalignment problem in searching patterns with ordinary 4C8B compression. cp-BM searches DNA patterns at least 6 times faster than AGREP for pattern lengths ≥ 128 and between 2-fold and 5-fold faster than d-BM for all pattern lengths. cp-BM's performance is enhanced by punctuator indexing and multiple punctuators, especially for short sequences, yielding greater than 10-fold enhancements compared to d-BM and AGREP. In addition, cp-BM outperformed BLAT for sequences 64 or more bases in length, and was more than three-fold faster for 256 base sequences.
5831663
Program counter-based prediction techniques for dynamic power management
Reducing energy consumption has become one of the major challenges in designing future computing systems. This paper proposes a novel idea of using program counters to predict I/O activities in the operating system. It presents a complete design of program-counter access predictor (PCAP) that dynamically learns the access patterns of applications and predicts when an I/O device can be shut down to save energy. PCAP uses path-based correlation to observe a particular sequence of program counters leading to each idle period and predicts future occurrences of that idle period. PCAP differs from previously proposed shutdown predictors in its ability to: 1) correlate I/O operations to particular behavior of the applications and users, 2) carry prediction information across multiple executions of the applications, and 3) attain higher energy savings while incurring lower mispredictions. We perform an extensive evaluation study of PCAP using a detailed trace-driven simulation and an actual Linux implementation. Our results show that PCAP achieves lower average mispredictions and higher energy savings than the simple timeout scheme and the state-of-the-art learning tree scheme