8218071
Adaptive hard disk power management on personal computers
Dynamic power management can be effective for designing low-power systems. In many systems, requests are clustered into sessions. This paper proposes an adaptive algorithm that can predict session lengths and shut down components between sessions to save power. Compared to other approaches, simulations show that this algorithm can reduce power consumption in hard disks with less impact on performance or reliability.
15594355
Replacing Failed Sensor Nodes by Mobile Robots
Sensor replacement is important for sensor networks to provide continuous sensing services. Existing approaches relocate redundant nodes to fill the holes created by failed sensors and require all or most sensor nodes to have mobility. However, mobility equipment is expensive while technology trends are scaling sensors to be smaller and cheaper. In this paper, we propose to use a small number of mobile robots to replace failed sensors in a large-scale static sensor network. We study algorithms for detecting and reporting sensor failures and coordinating the movement of robots that minimize the motion energy of mobile robots and the messaging overhead incurred to the sensor network. A manager receives failure reports and determines which robot to handle a failure. We study three algorithms: a centralized manager algorithm, a fixed distributed manager algorithm, and a dynamic distributed manager algorithm. Our simulations show that: (a) The centralized and the dynamic distributed algorithms have lower motion overhead than the fixed distributed algorithm. (b) The centralized algorithm is less scalable than the two distributed manager algorithms. (c) The two distributed algorithms have higher messaging cost than the centralized algorithm. Hence, the optimal choice of the coordination algorithm depends on the specific scenarios and objectives being optimized.
9215156
Energy management using buffer memory for streaming data
This work presents a new approach for energy management by inserting data buffers. The buffers are managed using the concept of inventory control by treating energy as cost and computation as production. The data stored in the buffers are considered as merchandise. Our method provides a mathematical framework to develop general strategies managing the energy consumption in computers. The approach can solve a wide range of problems. For example, it can calculate the needed buffer sizes to achieve optimal energy savings. It can derive the conditions when a standby state saves energy. The method also shows the effect of load balancing on energy conservation and can handle the variations of data rates. We use sensor networks as case studies and demonstrate more than 20% energy savings.
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.
14287933
Statistically optimal dynamic power management for streaming data
This paper presents a method that uses data buffers to create long periods of idleness to exploit 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 without subjective or heuristic decisions. We simulate four different hardware configurations with MPEG-1, MPEG-2, and MPEG-4 formats as a case study. Our results indicate that the optimal buffer size varies significantly for different data formats on different hardware. Simulation results indicate that 16 MB buffers are sufficient for MPEG-1, MPEG-2, and MPEG-4 video streams from a microdrive or a network card, but transfers from an IDE disk require buffer sizes ranging from 16 MB to 176 MB, depending on each video's statistical properties.
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.
42676253
Synchronization of large sequential circuits by partial reset
In this paper, we present a technique to synchronize large synchronous sequential circuits, which uses partial reset to break feedback loops in the circuits such that they become synchronizable. The method also provides a synchronizing sequence. Experimental results for ISCAS'89 benchmark circuits are presented, including the largest circuits, which were not synchronized previously.
702707
Rate-distortion analysis for H.264/AVC video coding and its application to rate control
In this paper, an efficient rate-control scheme for H.264/AVC video encoding is proposed. The redesign of the quantization scheme in H.264/AVC results in that the relationship between the quantization parameter and the true quantization stepsize is no longer linear. Based on this observation, we propose a new rate-distortion (R-D) model by utilizing the true quantization stepsize and then develop an improved rate-control scheme for the H.264/AVC encoder based on this new R-D model. In general, the current R-D optimization (RDO) mode-selection scheme in H.264/AVC test model is difficult for rate control, because rate control usually requires a predetermined set of motion vectors and coding modes to select the quantization parameter, whereas the RDO does in the different order and requires a predetermined quantization parameter to select motion vectors and coding modes. To tackle this problem, we develop a complexity-adjustable rate-control scheme based on the proposed R-D model. Briefly, the proposed scheme is a one-pass process at frame level and a partial two-pass process at macroblock level. Since the number of macroblocks with the two-pass processing can be controlled by an encoder parameter, the fully one-pass implementation is a subset of the proposed algorithm. An additional topic discussed in this paper is about video buffering. Since a hypothetical reference decoder (HRD) has been defined in H.264/AVC to guarantee that the buffers never overflow or underflow, the more accurate rate-allocation schemes are proposed to satisfy these requirements of HRD.
16579446
Mining Correlation between Motifs and Gene Expression
One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
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.
1552056
Pama: a Fast String Matching Algorithm
String matching is a fundamental operation in computer science, and its performance has great impact on many applications including database query, text processing, DNA and protein sequence analysis. In this paper, we propose a fast string matching algorithm, PAMA (PAttern MAtching). The shift rule used by PAMA not only subsumes both the bad character rule and the good suffix rule employed by the well-known Boyer-Moore algorithm, but also employs an additional key observation to enable faster shifting during the string matching process. Theoretically, we prove that from the same alignment, the next shift of PAMA will be at least as much as that of the Boyer-Moore algorithm. Experimentally, we show that PAMA indeed significantly outperforms the original Boyer-Moore algorithm in almost all cases, and outperforms other Boyer-Moore variants such as Tuned-BM, Turbo-BM and Horspool for long patterns (length ≥ 128) or for small alphabets (size < 8).