14647313
Energy-efficient disk replacement and file placement techniques for mobile systems with hard disks
Mobile systems have usually used hard disks as the secondary storage devices because of their high capacity per cost and high I/O throughput. However, their high power consumption is the main limiting factor for extending their adoptions in mobile systems. In this paper, we propose enhanced file placement techniques for mobile platforms with multiple smaller disks (instead of a single large disk). We investigate that how many smaller disks are necessary to obtain energy saving while maintaining the required performance using both a simplified energy model and a realistic trace-based simulator under the proposed multiple disk configurations. We also propose energy-efficient file placement techniques, which aggregate files with common attributes the same set of disks. By skewing I/O operations, the proposed techniques achieve additional energy saving. Experimental results show that the proposed techniques can reduce the energy consumption by up to 43% when eight 1" disks are used instead of a single 2.5" disk with an acceptable increase in the average response time.
15453065
Device-Aware Cache Replacement Algorithm for Heterogeneous Mobile Storage Devices
Hard disks, most prevalent mass-storage devices, have high power consumption and high response time for random I/O requests. Recent remarkable technology improvement of flash memory has made it a rising secondary storage device but flash memory still has high cost per bit. Usage of heterogeneous storage devices such as a pair of a hard disk and a flash memory can provide reasonable cost, relatively acceptable response time, and low-power consumption. In this paper, we propose a novel buffer cache replacement algorithm which targets a mobile computing system with a heterogeneous storage pair of a hard disk and a flash memory. The algorithm partitions the cache per each device and adjusts the size of each partition based on the performance indices of the devices, and manages each partition according to workload patterns. Simulations show that the proposed algorithm yields a hit rate up to two times higher than LRU on the typical mobile traces according to the cache size and achieves also better system I/O response time and energy consumption.
28723686
Implementation of ECC/ECDSA cryptography algorithms based on Java card
This paper describes the implementations and test results of elliptic curve cryptography (ECC) and elliptic curve digital signature algorithm (ECDSA) algorithms based on Java card. A 163-bit ECC guarantees as secure as the 1024-bit Rivest-Shamir-Adleman (RSA) public key algorithm, which has been frequently used until now. According to our test results, the 163-bit ECC processing time is about five times faster compared with the 1024-bit RSA, and the amount of resource usages of ECC is smaller than RSA. Therefore, ECC is more appropriate for use on secure devices such as smart cards and wireless devices with constrained computational power consumption and memory resources.
35466192
Scheduling on parallel identical machines to minimize total tardiness
This paper focuses on the problem of scheduling n independent jobs on m identical parallel machines for the objective of minimizing total tardiness of the jobs. We develop dominance properties and lower bounds, and develop a branch and bound algorithm using these properties and lower bounds as well as upper bounds obtained from a heuristic algorithm. Computational experiments are performed on randomly generated test problems and results show that the algorithm solves problems with moderate sizes in a reasonable amount of computation time. � 2005 Elsevier B.V. All rights reserved.
33400437
Facial Expression Recognition Using Active Appearance Model
This paper describes a facial expression recognition system based upon Active Appearance Model (AAM), which has been typically used for the face recognition task. Given that AAM has been also used in tracking the moving object, we thought it could be effective in recognizing the facial expressions of humans. Our results show that the performance of the facial expression recognition using AAM is reliably high when it combined with an enhanced Fisher classification model.
14130132
Signal space detection for recording channels with jitter noise
A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector.
80432
Resource sharing and pipelining in coarse-grained reconfigurable architecture for domain-specific optimization
Coarse-grained reconfigurable architectures aim to achieve goals of both high performance and flexibility. However, existing reconfigurable array architectures require many resources without considering the specific application domain. Functional resources that take long latency and/or large area can be pipelined and/or shared among the processing elements. Therefore, the hardware cost and the delay can be effectively reduced without any performance degradation for some application domains. We suggest such a reconfigurable array architecture template and a design space exploration flow for domain-specific optimization. Experimental results show that our approach is much more efficient, in both performance and area, compared to existing reconfigurable architectures.
2382558
Convex Hull Ensemble Machine for Regression and Classification
We propose a new ensemble algorithm called Convex Hull Ensemble Machine (CHEM). CHEM in Hilbert space is first developed and modified for regression and classification problems. We prove that the ensemble model converges to the optimal model in Hilbert space under regularity conditions. Empirical studies reveal that, for classification problems, CHEM has a prediction accuracy similar to that of boosting, but CHEM is much more robust with respect to output noise and never overfits datasets even when boosting does. For regression problems, CHEM is competitive with other ensemble methods such as gradient boosting and bagging.