Routing table partitioning for speedy packet lookups in scalable routers

Most of the high-performance routers available commercially these days equip each of their line cards (LCs) with a forwarding engine (FE) to perform table lookups locally. This work introduces and evaluates a technique for speedy packet lookups, called SPAL, in such routers. The BGP routing table under SPAL is fragmented into subsets which constitute forwarding tables for different FEs so that the number of table entries in each FE drops as the router grows. This reduction in the forwarding table size drastically lowers the amount of SRAM (e.g., L3 data cache) required in each LC to hold the trie constructed according to the prefix matching algorithm. SPAL calls for caching the lookup result of a given IP address at its home LC (denoted by LC/sub ho/, using the LR-cache), such that the result can satisfy the lookup requests for the same address from not only LC/sub ho/, but also other LCs quickly. Our trace-driven simulation reveals that SPAL leads to improved mean lookup performance by a factor of at least 2.5 (or 4.3) for a router with three (or 16) LCs, if the LR-cache contains 4K blocks. SPAL achieves this significant improvement, while greatly lowering the SRAM (i.e., the L3 data cache plus the LR-cache combined) requirement in each LC and possibly shortening the worst-case lookup time (thanks to fewer memory accesses during longest-prefix matching search) when compared with a current router without partitioning the routing table. It promises good scalability (with respect to routing table growth) and exhibits a small mean lookup time per packet. With its ability to speed up packet lookup performance while lowering overall SRAM substantially, SPAL is ideally applicable to the new generation of scalable high-performance routers.     

The impact of general and specific performance and self-efficacy on learning with computer-based concept mapping

When students learn a new and challenging task, for which they have very limited corresponding personal or vicarious experiences to refer, it is important to understand how their self-efficacy beliefs evolve during the course of sequential lessons; how they differ in the way their general learning performance and self-efficacy influence their ratings of task-specific self-efficacy and performance; and, how such differences may result in different learning outcomes and motivations for learning. By examining a group of 66 students engaged in learning to construct good concept maps with computer software, this study revealed several important findings on these questions. Students generally tended to initially overestimate their ability to successfully carry out the required task. They also varied in the way their general self-efficacy and performance were associated with their task-specific self-efficacy and performance. And, these differences did appear to be associated with different learning outcomes and motivations for learning. These results indicate that investigating individual differences in students’ patterns of association between general and specific performance and their self-efficacy may lead to a better understanding of how students differ in their levels of motivation and outcomes when learning a new and challenging task.     

Identification of general fuzzy measures by genetic algorithmsbased on partial information

This study develops an identification procedure for general fuzzy measures using genetic algorithms. In view of the difficulty in data collection in practice, the amount of input data is simplified through a sampling procedure concerning attribute subsets, and the corresponding detail design is adapted to the partial information acquired by the procedure. A specially designed genetic algorithm is proposed for better identification, including the development of the initialization procedure, fitness function, and three genetic operations. To show the applicability of the proposed method, this study simulates a set of experimental data that are representative of several typical classes. The experimental analysis indicates that using genetic algorithms to determine general fuzzy measures can obtain satisfactory results under the framework of partial information.     

Birefringence examination in a practical fiber-current-sensing system

The output of a fiber-current sensor with a nonideal input (either misaligned linear or elliptical polarization) and moderate output misalignment in the setup (the fiber end versus the Wollaston prism) has been considered. Based on this, a novel method that uses a statistical approach, including a set of scanning elliptical polarization inputs and the corresponding curve-fitting outputs for a given current, is used to determine the birefringence of the fiber-current-sensing system. The experimentally measured bend-induced birefringence agrees with the estimated value of the bend birefringence.     

Design of two-channel perfect-reconstruction linear-phase finite-duration impulse response filter banks for subband image coding by the genetic algorithm approach

In this paper, a powerful approach is proposed for the design of two-dimensional two-channel perfect-reconstruction finite-duration impulse response filter banks employing diamond-shaped linear-phase filters. When one of the analysis filter pair is properly designed, the condition of perfect reconstruction is formulated in a spatial-domain constraint equation for designing the other. The method is based on minimizing the integrated square error for the frequency response over the pass band and stop band while imposing the spatial-domain constraint. One numerical design example is given to demonstrate the perfect reconstruction for the proposed system.     

Continuous-flow particle and cell separations in a serpentine microchannel via curvature-induced dielectrophoresis

Particle and cell separations are critical to chemical and biomedical analyses. This study demonstrates a continuous-flow electrokinetic separation of particles and cells in a serpentine microchannel through curvature-induced dielectrophoresis. The separation arises from the particle size-dependent cross-stream dielectrophoretic deflection that is generated by the inherent electric field gradients within channel turns. Through the use of a sheath flow to focus the particle mixture, we implement a continuous separation of 1 and 5 μm polystyrene particles in a serpentine microchannel under a 15 kV/m DC electric field. The effects of the applied DC voltages and the serpentine length on the separation performance are examined. The same channel is also demonstrated to separate yeast cells (range in diameter between 4 and 8 μm) from 3 μm particles under an electric field as low as 10 kV/m. The observed focusing and separation processes for particles and cells in the serpentine microchannel are reasonably predicted by a numerical model.     

Adaptive frame synchronization for surveillance system across a heterogeneous network

As mobile techniques are booming, the surveillance function is extended from a stationary mode to a mobile mode. In a heterogeneous network environment, cameras and viewers are located in different networks so that frame synchronization may span across diverse network domains with different transmission capabilities. The mismatch of transmission capabilities may affect the viewing continuity and playback liveness between cameras and viewers. In the article, we propose an adaptive frame synchronization mechanism for frame capturing at cameras based on the network condition to improve the frame synchronization between two sides across a heterogeneous network. Based on a brief theoretical analysis of the asynchronization effect for video communication in a heterogeneous network environment, the proposed adaptive pause time mechanism can be an effective solution to relieve the asynchronization effect in the unmatched transmission rate situation. The evaluation results show that the proposed scheme can achieve a shorter time delay between the captured frames at the camera site and the viewer site.     

Channel Management for Multi-Service Traffic in Cellular Wireless Networks

Channel management aims to provide quality of service guarantees for mobile users while efficiently utilize limited radio spectrum. With the increasing demand for diverse services in wireless networks, channel management for multi-service traffic in wireless networks is important. To provide diverse broadband services in limited radio spectrum, previous literature has presented adaptive services which provide mobile users with good quality of services. This study considers channel management for multi-service traffic in wireless networks with adaptive services. A channel management scheme, namely, restricted sharing, is devised to provide multi-class traffic with quality of service guarantees while increase channel utilization as much as possible. An analysis is used to study the performance of the restricted sharing scheme. Three classes are considered in numerical results. Numerical results show that the restricted sharing scheme guarantees quality of service and achieves high channel utilization.     

Diagnosis by Image Recovery: Finding Mixed Multiple Timing Faults in a Scan Chain

In this brief, we present a robust new paradigm for diagnosing a scan chain with multiple faults that could have different fault types. As compared to previous methods, the major advantage of ours is the ability to not only target mixed multiple types of timing faults in the same scan chain but also tolerate non-ideal conditions, e.g., when these faults only manifest themselves intermittently. Unlike the previous matching-based algorithms, we formulate the diagnosis problem as an image recovery process featuring a dynamic windowing technique and a running sequence handling technique. Experimental results on a number of real designs show that this paradigm can successfully deal with some situations beyond existing methods.