22667475
High-performance IP routing table lookup
Nowadays, the commonly used table lookup scheme for IP routing is based on the so-called classless interdomain routing (CIDR). With CIDR, routers must find out the best matching prefix (BMP) for IP packets forwarding, which complicates the IP lookup. Currently, this process is mainly done in software and several schemes have been proposed for hardware implementation. Since the IP lookup performance is a major design issue for the new generation routers, in this article we propose a fast IP address lookup scheme, which significantly reduces the forwarding table to fit into SRAM with very low cost. It can also be implemented in hardware using the pipeline technique. By using our proposed method, the required memory space can be 90-170Kb less than the previous scheme and three memory accesses for a lookup in the worst case. When implemented in hardware pipeline architecture, our mechanism can achieve one routing lookup per memory access.
15398175
Hardware-based Packet Classification Made Fast and Efficient
To achieve fast packet classification, a hardware-based scheme, cross-producting recurrence (CPR), based on a formerly proposed cross-producting scheme is proposed. This scheme simplifies the classification procedure and decrease the distinct combinations of fields by hierarchically decomposing the multi-dimensional space. In the new scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into repeatedly searching for matching subspaces. The required storage of the proposed scheme is significantly reduced since the distinct fields of subspaces is controlled by a pre-defined configuration and can be much less than that of the filters. The experimental results demonstrate the effectiveness and scalability of the proposed scheme
14294426
Gigabit packet classification by using lookahead caching
Hashing is a widely used method to perform fast lookup. Several schemes have been proposed to support Internet lookup that includes IP lookup and packet classification. Rectangular search is a well-known packet classification scheme based on multiple hash accesses for different filter length. It shows good scalability with respect to the number of filters; however, the lookup performance is not satisfactory. For example, through experiments, each packet classification takes about 40 hash accesses in a 100,000-filter database and each hash access may take more than one memory access. Obviously, this is insufficient to provide gigabits throughput. We proposed a novel "lookahead caching" which can significantly improve the performance of the hash-based algorithm. The basic idea is to find out the unmatched case for each incoming packet, thus it is different from the traditional caching mechanism. The experimental results indicate that the proposed scheme can improve the performance by a factor of two. The scheme can be further enhanced using parallel processing.
38910166
Parallel Object Representation and Recognition
A parallel method for 3-dimensional (3d) object recognition is introduced, using the concept of coordinated graph, layered graph representation, and parallel matching techniques, and significantly reduces the time required for dealing with 3-dimensional image analysis problems. Their fundamental parallel properties and concept of finite representations are investigated and several interested examples including curved and disconnected images are illustrated. In addition to its importance in theoretical parallel study, it can also be applied to 3-d parallel object recognition, image processing and computer vision.
6309219
Contextual browsing for highlights in sports video
A novel highlight browsing approach for sports videos, based on contextual cue categorization, is proposed in this paper. Contextual cues are those salient audio and visual cues around highlight segments, and they are also informative and attractive to audiences. With further analysis and categorization of these contextual cues, the user could access highlights more flexibly and effectively. An experimental system is built for broadcasting diving videos in our current work, in which contextual cues such as slow-motion replays and game statistics information are extracted and categorized for highlight browsing. An efficient algorithm for slow-motion replay detection and categorization in diving videos is also proposed. Experimental results on 2 hours broadcasting diving videos have demonstrated the effectiveness and efficiency of the proposed approach.
13452585
Robust Clustering based on Winner-Population Markov Chain
In this paper, we propose an unsupervised genetic clustering algorithm, which produces a new chromosome without any conventional genetic operators, and instead according to the gene reproducing probabilities determined by Markov chain modeling. Selection of cluster centers from the dataset enables construction of a look-up table that saves the distances between all pairs of data points. The experimental results show that the proposed algorithm not only solves the premature problem to provide a more stable clustering performance in terms of number of clusters and clustering results, but also improves the time efficiency
15078369
Self-organising impact boundaries in ageless aerospace vehicles
Self-monitoring, self-repairing aerospace vehicles require modular, flexible and adaptive sensing and communication networks. In general, a modular (multi-cellular) sensing and communication network is expected to detect and react to impact location, energy and damage over a wide range of impacts. It is critical that global response emerges as a result of interactions involving transfer of information embedded locally, avoiding single points-of-failure. This work presents mechanisms ensuring self-organisation of autonomous cells into robust and continuously connected impact boundaries. The spatiotemporal stability is demonstrated for a variety of cell shapes in a dynamic environment with varying energy dissipation and damage probability models.
16423538
On Decentralised Clustering in self-monitoring networks
A Decentralised Adaptive Clustering (DAC) algorithm for multiagent networks is contrasted with a Fixed-order Centralised Adaptive Clustering algorithm (FCAC). The clustering is done on sensor readings detected within a self-monitoring impact sensing network. Simulation results show that DAC algorithm scales well with increasing network and data sizes and in some cases outperforms FCAC algorithm. While the common-sense intuition suggests that centralised algorithm is always superior, we support the simulation results with a simple counter-example.