30645069
Backtrack Routing and Priority-Based Wavelength Assignment in WDM Networks
In this paper, we consider two key problems in the WDM networks: the wavelengh assignment and routing problems. The objective of the problems is to minimize the request blocking rate. We propose two priority-based methods for the wavelength assignment problem: static and dynamic strategies. Based on the priority of an incoming request, the proposed methods allocate a wavelength among the available wavelengths for the given priority. Analytic models and simulations are presented for the proposed wavelength assignment methods so as to analyse the link blocking rate. The simulation results show that the link blocking rate by the dynamic strategy is less than that by the assignment strategy. We also develop a routing algorithm that works together with the proposed wavelength assignment methods to reduce the overall blocking rates. The proposed routing method maintains a routing tree for a given connection request. Based on the routing tree, the algorithm finds a route with one available wavelength for each link along the route. We compare the proposed routing method with the fixed routing and fixed alternate routing algorithms. The experiments show that the proposed routing algorithm performs better than the fixed routing and the alternate routing methods.
14292166
A self-adjusting quality of service control scheme
We propose and analyze a self-adjusting Quality of Service (QoS) control scheme with the goal of optimizing the system reward as a result of servicing different priority clients with varying workload, QoS and reward/penalty requirements. Our scheme is based on resource partitioning and designated "degrade QoS areas" such that system resources are partitioned into priority areas each of which is reserved specifically to serve only clients in a corresponding class with no QoS degradation, plus one "degraded QoS area" into which all clients can be admitted with QoS adjustment being applied only to the lowest priority clients. We show that the best partition is dictated by the workload and the reward/penalty characteristics of clients in difference priority classes. The analysis results can be used by a QoS manager to optimize the system total rewawrd dynamically in response to changing workloads at run time. We demonstrate the validity of our scheme by means of simulation and comparing the proposed QoS self-adjusting scheme with those that do not use resource partitioning or designated degraded QoS area.
6799009
On packetization of embedded multimedia bitstreams
We study the problem of packetizing embedded multimedia bitstreams to improve the error resilience of source (compression) codes. This problem is important because of the increasing popularity of embedded compression methodology and its suitability for scalable streaming media over IP or/and mobile IP. We study various packetization schemes against packet erasure at both low and high bit rates. Maximizing packetization efficiency for embedded bitstreams is formulated as a discrete optimization problem and globally optimal packetization (OP) algorithms are proposed under different settings. Suboptimal packetization algorithms are also devised to reduce the complexity of the OP algorithms. In order to assess their effectiveness, the proposed packetization algorithms are used to packetize embedded image and video bitstreams with simulated packet loss. Experimental results show that our OP algorithms slightly outperforms suboptimal ones. In addition to confirming the superiority of the OP algorithms, these results also provide justification of heuristic packetization methods published in the literature.
359856
Curve reconstruction from noisy samples
We present an algorithm to reconstruct a collection of disjoint smooth closed curves from n noisy samples. Our noise model assumes that the samples are obtained by first drawing points on the curves according to a locally uniform distribution followed by a uniform perturbation of each point in the normal direction with a magnitude smaller than the minimum local feature size. The reconstruction is faithful with a probability that approaches 1 as n increases.We expect that our approach can lead to provable algorithms under less restrictive noise models and for handling non-smooth features.
1223930
Approximate Strategic Reasoning through Hierarchical Reduction of Large Symmetric Games
To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated local-effect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity. Motivation Consider the task of selecting among a large set of strategies to play in an 8-player game. Through careful judgment you manage to narrow down the candidates to a reasonable number of strategies (say 35). Because the performance of a strategy for one agent depends on the strategies of the other seven, you wish to undertake a game-theoretic analysis of the situation. Determining the payoff for a particular strategy profile is expensive, however, as your observations of prior game instances are quite limited, and the only operational description of the game is in the form of a simulator that takes a non-negligible time (say 10 minutes) to produce one outcome. Moreover, since the environment is stochastic, numerous samples (say 12) are required to produce a reliable estimate for even one profile. At two hours per profile, ex
2623430
Manifold reconstruction from point samples
We present an algorithm to "reconstruct" a smooth <i>k</i>-dimensional manifold <i>M</i> embedded in an Euclidean space R<sup>d</sup> from a "sufficiently dense" point sample from the manifold. The algorithm outputs a simplicial manifold that is homeomorphic and geometrically close to <i>M.</i> The running time is <i>O</i>(<i>n</i> log <i>n</i>) where <i>n</i> is the number of points in the sample (the multiplicative constant depends exponentially on the dimension though).
206577228
Fast Trellis-Coded Color Quantization of Images
We examine color quantization of images using trellis-coded quantization (TCQ) in both the RGB domain and YUV domain. Together with a simple dithering scheme, an eight-bit trellis-coded color quantizer reproduces images that are visually indistinguishable from the 24-bit originals. It can be viewed as a predictive trellis-coded color quantization scheme. We also study trellis-coded vector quantization (TCVQ) for color quantization. Our proposed TCQ-based color quantization schemes are universal in the sense that no training or look-up table is needed. The complexity of TCQ is linear with respect to image size, making trellis-coded color quantization suitable for color printing, real-time interactive graphics and window-based display environment.