7272374
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
We present an "opportunistic" transmission scheduling policy that exploits time-varying channel conditions and maximizes the system performance stochastically under a certain resource allocation constraint. We establish the optimality of the scheduling scheme and also that every user experiences a performance improvement over any nonopportunistic scheduling policy when users have independent performance values. We demonstrate via simulation results that the scheme is robust to estimation errors and also works well for nonstationary scenarios, resulting in performance improvements of 20%-150% compared with a scheduling scheme that does not take into account channel conditions. Last, we discuss an extension of our opportunistic scheduling scheme to improve "short-term" performance.
5642431
Sensing-based opportunistic channel access
Enabled by regulatory initiatives and advanced radio technologies, more flexible opportunistic spectrum access has great potential to alleviate the spectrum scarcity. In this paper, we study the channel selection issue of secondary users in spectrum-agile communication systems. We focus on the sensing-based approach because it is simple and has low infrastructure requirements. We propose a two-step approach for channel selection. The first step is to determine whether or not a channel is idle and thus accessible to secondary users. We propose three algorithms to perform the accessibility check based on measurements of primary signals. Then we address the question whether an accessible channel is a good opportunity for a secondary user.
292448
Efficient Network Utilization for Multimedia Wireless Networks
In this paper, we present an access scheme to satisfy the QoS requirements for two classes of traffic during the contention phase of packet-switched wireless communications. In the proposed scheme, difierent classes of users contend with other users for resources based on controlled class-dependent permission probabilities. We prove that our algorithm is stable for a large class of arrival processes. Under certain QoS requirements, we derive an upper-bound on the throughput for a general class of random access algorithms. We show that the throughput of our algorithm asymptotically approaches this upper-bound. We also show, through numerical examples, that our algorithm achieves high network utilization.
12314143
Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks
In this paper we investigate efficient strategies for supporting on-demand information dissemination and gathering in large-scale vwireless sensor networks. In particular, we propose a "comb-needle" discovery support model resembling an ancient method: use a comb to help find a needle in sands or a haystack. The model combines push and pull for information dissemination and gathering. The push component features data duplication in a linear neighborhood of each node. The pull component features a dynamic formation of an on-demand routing structure resembling a comb. The comb-needle model enables us to investigate the cost of a spectrum of push and pull combinations for supporting discovery and query in large scale sensor networks. Our result shows that the optimal routing structure depends on the frequency of query occurrence and the spatial-temporal frequency of related events in the network. The benefit of balancing push and pull for discovery in large scale geometric networks are demonstrated. We also raise the issue of query coverage in unreliable networks and investigate how redundancy can improve the coverage via both theoretical analysis and simulation. Last, we study adaptive strategies for the case where the frequencies of query and events are unknown a priori and time-varying.
368408
A framework for opportunistic scheduling in wireless networks
Abstract We present a method, called opportunistic scheduling, for exploiting the time-varying nature of the radio environment to increase the overall performance of the system under certain quality of service/fairness requirements of users. We first introduce a general framework for opportunistic scheduling, and then identify three general categories of scheduling problems under this framework. We provide optimal solutions for each of these scheduling problems. All the proposed scheduling policies are implementable online; we provide parameter estimation algorithms and implementation procedures for them. We also show how previous work by us and others directly fits into or is related to this framework. We demonstrate via simulation that opportunistic scheduling schemes result in significant performance improvement compared with non-opportunistic alternatives.
9148979
Face detection using spectral histograms and SVMs
We present a face detection method using spectral histograms and support vector machines (SVMs). Each image window is represented by its spectral histogram, which is a feature vector consisting of histograms of filtered images. Using statistical sampling, we show systematically the representation groups face images together; in comparison, commonly used representations often do not exhibit this necessary and desirable property. By using an SVM trained on a set of 4500 face and 8000 nonface images, we obtain a robust classifying function for face and nonface patterns. With an effective illumination-correction algorithm, our system reliably discriminates face and nonface patterns in images under different kinds of conditions. Our method on two commonly used data sets give the best performance among recent face-detection ones. We attribute the high performance to the desirable properties of the spectral histogram representation and good generalization of SVMs. Several further improvements in computation time and in performance are discussed.
1063503
Mutual anonymous overlay multicast
Multicast services are demanded by a variety of applications. Many applications require anonymity during their communication. However, there has been very little work on anonymous multicasting and such services are not available yet. Due to the fundamental differences between multicast and unicast, the solutions proposed for anonymity in unicast communications cannot be directly applied to multicast applications. In this paper we define the anonymous multicast system, and propose a mutual anonymous multicast (MAM) protocol including the design of a unicast mutual anonymity protocol and construction and optimization of an anonymous multicast tree. MAM is self-organizing and completely distributed. We define the attack model in an anonymous multicast system and analyze the anonymity degree. We also evaluate the performance of MAM by comprehensive simulations.
44899292
Subspace gradient domain mesh deformation
In this paper we present a general framework for performing constrained mesh deformation tasks with gradient domain techniques. We present a gradient domain technique that works well with a wide variety of linear and nonlinear constraints. The constraints we introduce include the nonlinear volume constraint for volume preservation, the nonlinear skeleton constraint for maintaining the rigidity of limb segments of articulated figures, and the projection constraint for easy manipulation of the mesh without having to frequently switch between multiple viewpoints. To handle nonlinear constraints, we cast mesh deformation as a nonlinear energy minimization problem and solve the problem using an iterative algorithm. The main challenges in solving this nonlinear problem are the slow convergence and numerical instability of the iterative solver. To address these issues, we develop a subspace technique that builds a coarse control mesh around the original mesh and projects the deformation energy and constraints onto the control mesh vertices using the mean value interpolation. The energy minimization is then carried out in the subspace formed by the control mesh vertices. Running in this subspace, our energy minimization solver is both fast and stable and it provides interactive responses. We demonstrate our deformation constraints and subspace deformation technique with a variety of constrained deformation examples.
3103928
Maximizing performance by retiming and clock skew scheduling
The application of retiming and clock skew scheduling for improving the operating speed of synchronous circuits under setup and hold constraints is investigated in this paper. It is shown that when both long and short paths are considered, circuits optimized by the simultaneous application of retiming and clock scheduling can achieve shorter clock periods than optimized circuits generated by applying either of the two techniques separately. A mixed-integer linear programming formulation and an efficient heuristic are given for the problem of simultaneous retiming and clock skew scheduling under setup and hold constraints. Experiments with benchmark circuits demonstrate the efficiency of this heuristic and the effectiveness of the combined optimization. All of the test circuits show improvement. For more than half of them, the maximum operating speed increases by more than 21% over the optimized circuits obtained by applying retiming or clock skew scheduling separately.
2869410
UMass at TREC 2003: HARD and QA
Abstract : The Center for Intelligent Information Retrieval (CIIR) at UMass Amherst participated in two tracks for TREC 2003: High Accuracy Retrieval from Documents (HARD) and Question Answering (QA). In the HARD track, we developed document metadata to correspond to query metadata requirements; implemented clarification forms based on query expansion, passage retrieval, and clustering; and retrieved variable length passages deemed most likely to be relevant. This work is discussed at length in Section 1. In the QA track, we focused on retrieving passages that were likely to contain the answer to the question. In the QA track, we developed a dynamic passaging retrieval system to identify passages likely to contain answers. CIIR last participated in the QA task in TREC 9 (2000). At that time we fielded the Marsha system [11]. This system was based on an INQUERY document retrieval engine followed by the application of a series of heuristics rules to identify 250-byte long passages in the retrieved documents that were likely to contain the desired answers. This year's passage sub-task in the QA track has allowed us to participate once again utilizing our current approach to passage retrieval with language models. We developed a dynamic passaging system that retrieved document passages based on the simplest implementation of language models: cross-entropy between bag-of-word models for a question and a candidate passage.