41948538
Enhanced Model Representations for an Intra-Ring Synchronous Optical Network Design Problem Allowing Demand Splitting
In this paper, we consider a network design problem arising in the context of deploying synchronous optical networks (SONET) using a unidirectional path switched ring architecture, a standard of transmission using optical fiber technology. Given several rings of this type, the problem is to find an assignment of nodes to possibly multiple rings, and to determine what portion of demand traffic between node pairs spanned by each ring should be allocated to that ring. The constraints require that the demand traffic between each node pair should be satisfiable given the ring capacities, and that no more than a specified maximum number of nodes should be assigned to each ring. The objective function is to minimize the total number of node-to-ring assignments, and hence, the capital investment in add-drop multiplexer equipments. We formulate the problem as a mixed-integer programming model, and propose several alternative modeling techniques designed to improve the mathematical representation of this problem. We then develop various classes of valid inequalities for the problem along with suitable separation procedures for tightening the representation of the model, and accordingly, prescribe an algorithmic approach that coordinates tailored routines with a commercial solver (CPLEX). We also propose a heuristic procedure which enhances the solvability of the problem and provides bounds within 5--13% of the optimal solution. Promising computational results are presented that exhibit the viability of the overall approach and that lend insights into various modeling and algorithmic constructs.
106215
A stochastic integer programming approach to solving a synchronous optical network ring design problem
We develop stochastic integer programming techniques tailored toward solving a Synchronous Optical Network (SONET) ring design problem with uncertain demands. Our approach is based on an L-shaped algorithm, whose (integer) master program prescribes a candidate network design, and whose (continuous) subproblems relay information regarding potential shortage penalty costs to the ring design decisions. This naive implementation performs very poorly due to two major problems: (1) the weakness of the master problem relaxations, and (2) the limited information passed to the master problem by the optimality cuts. Accordingly, we enforce certain necessary conditions regarding shortage penalty contributions to the objective function within the master problem, along with a corresponding set of valid inequalities that improves the solvability of the master problem. We also show how a nonlinear reformulation of the model can be used to capture an exponential number of optimality cuts generated by the linear model. We augment these techniques with a powerful upper-bounding heuristic to further accelerate the convergence of the algorithm, and demonstrate the effectiveness of our methodologies on a test bed of randomly generated stochastic SONET instances. © 2004 Wiley Periodicals, Inc. NETWORKS, Vol. 44(1), 12–26 2004
38357274
Algorithms for distributing telecommunication traffic on a multiple-ring SONET-based network
Abstract We examine a problem arising in the assignment of telecommunication traffic to a set of synchronous optical network (SONET) rings. Prior SONET design algorithms determine node-to-ring assignments while concurrently prescribing an assignment of traffic to the rings. However, due to uncertain voice and data demand among client nodes, it may become necessary to revise the planned routing scheme once the true values of this data are realized. We develop a minimum cost flow algorithm for the case in which demands may be split across multiple rings, and provide a transformation to a maximum flow problem for specially structured data. The case in which each demand pair may be routed on only one ring is proven to be NP-hard, and we accordingly provide a powerful heuristic and an effective standard valid inequality generation scheme to optimally solve this problem within reasonable computational limits. The effectiveness of our approach is demonstrated on a set of randomly generated test data.
44823536
A class of web-based facets for the generalized vertex packing problem
The generalized vertex packing problem seeks to identify a largest subset of nodes from an undirected graph, such that the subgraph induced by this subset of nodes contains no more than some threshold number of edges. This paper derives a class of valid inequalities based on certain special subgraphs called webs, which are general structures that subsume cliques, matchings, odd holes, and odd anti-holes. We also provide a set of conditions for this class of valid inequalities to be facet-inducing for the web subgraph polytope. Finally, we prescribe a web subgraph identification procedure, and test the computational benefits obtained by solving generalized vertex packing instances with formulations augmented by these web-based valid inequalities.
18781640
An Analysis of the Alias Method for Discrete Random-Variate Generation
This paper introduces and studies an optimization problem related to the alias method for discrete random-variate generation. The alias method is an efficient method to generate random variates from a discrete probability distribution. The efficiency of the alias method can be improved by designing the alias table such that the expected number of computations that must be performed per value generated is minimized. The problem of optimizing the construction of the alias table is proven to be strongly NP-hard, even if either of two variations of the alias method relaxing the alias-table-generation restrictions are used. Integer-programming formulations describing these three optimization problems are presented, and insights regarding necessary optimality criteria and relationships among their optimal solutions are discussed.
2339969
Interactive search fusion methods for video database retrieval
In this paper, we investigate a new method for video database retrieval using interactive search fusion. Recent video analysis techniques have enabled the extraction of a variety of descriptors of features, concepts, clusters, classification results, speech and textual terms, MPEG-7 metadata, and so on. However, given an information need users are faced with a daunting task of trying to formulate queries over these multiple disparate data sources in order to retrieve the desired video content. In this paper, we explore a novel approach based on search fusion in which the user interactively builds a query by sequentially choosing among the descriptors and data sources and by selecting from various combining and score aggregation functions to fuse results of individual searches. For example, the system allows building of queries such as "retrieve video clips that have color of beach scenes, the detection of sky, and detection of water". In this paper we present the search fusion method and evaluate the performance on a large video database.
38193465
Modeling semantic concepts to support query by keywords in video
Supporting semantic queries is a challenging problem in video retrieval. We propose the use of a lexicon of semantic concepts for handling the queries. We also propose automatic modeling of lexicon items using probabilistic techniques. We use Gaussian mixture models to build computational representations for a variety of semantic concepts including rocket-launch, outdoor greenery, sky etc. Training requires a large amount of annotated (labeled) data. Using the TREC Video test bed we compare the performance of this system supporting query by keywords with the conventional approach of query by example. Results demonstrate significant gains in performance using the automatically learnt models of semantic concepts.
18353433
VideoZoom Spatio-Temporal Video Browser
We describe a system for browsing and interactively retrieving video over the Internet at multiple spatial and temporal resolutions. The VideoZoom system enables users to start with coarse, low-resolution views of the sequences and selectively zoom-in in space and time. VideoZoom decomposes the video sequences into a hierarchy of view elements, which are retrieved in a progressive fashion. The client browser incrementally builds the views by retrieving, caching, and assembling the view elements, as needed. By integrating browsing and retrieval into a single progressive retrieval paradigm, VideoZoom provides a new and useful system for accessing video over the Internet. VideoZoom is suitable for digital video libraries and a number of other applications in which streaming methods provide insufficient quality of video, video downloading introduces large latencies, and generating video summaries is difficult or not well integrated with video retrieval tasks.
9844851
Communicating emotion through a haptic link: Design space and methodology
Communication of affect across a distance is not well supported by current technology, despite its importance to interpersonal interaction in modern lifestyles. Touch is a powerful conduit for emotional connectedness, and thus mediating haptic (touch) displays have been proposed to address this deficiency; but suitable evaluative methodology has been elusive. In this paper, we offer a first, structured examination of a design space for haptic support of remote affective communication, by analyzing the space and then comparing haptic models designed to manipulate its key dimensions. In our study, dyads (intimate pairs or strangers) are asked to communicate specified emotions using a purely haptic link that consists of virtual models rendered on simple knobs. These models instantiate both interaction metaphors of varying intimacy, and representations of virtual interpersonal distance. Our integrated objective and subjective observations imply that emotion can indeed be communicated through this medium, and confirm that the factors examined influence emotion communication performance as well as preference, comfort and connectedness. The proposed design space and the study results have implications for future efforts to support affective communication using the haptic modality, and the study approach comprises a first model for systematic evaluation of haptically expressed affect.
2764558
A statistical modeling approach to content based video retrieval
Statistical: modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evaluation and comparison of a variety of different algorithms on a set of high-level queries for multimedia retrieval. We report on the use of techniques adopted from statistical learning theory. Our method depends on training of models based on large data sets. Particularly, we use statistical models such as Gaussian mixture models to build computational representations for a variety of semantic concepts including rocket-launch, outdoor greenery, sky etc. Training requires a large amount of annotated (labeled) data. Thus, we explore the use of active learning for the annotation engine that minimizes the number of training samples to be labeled for satisfactory performance.