584351
Efficient peer-to-peer data dissemination in mobile ad-hoc networks
Without infrastructural support from base stations, mobile nodes in an ad hoc network communicate with each other in a peer-to-peer fashion. This poses a challenge in data dissemination among the mobile peers, each having limited transmission range and unpredictable mobility. We first propose a novel mobility model to characterize user mobility in a civilian environment, such as a college campus. We then propose the application of Tornado coding as an efficient solution to the challenge of ad hoc peer-to-peer data dissemination. A mobile node is able to download coded file segments from different peers-at different times and in different locations. When it receives sufficient segments, it will be able to re-construct the original file. Although Tornado coding itself is not new, we for the first time propose its application to mobile ad hoc data dissemination. Furthermore, we show how Tornado coding parameters affect the performance of peer-to-peer data dissemination.
8043231
QoS-Aware Adaptive Services in Mobile Ad-Hoc Networks
Ad-hoc wireless networks consist of mobile nodes interconnected by multi-hop wireless paths. Unlike conventional wireless networks, ad-hoc networks have no fixed network infrastructure or administrative support. Because of the dynamic nature of the network topology and limited bandwidth of wireless channels, Quality-of-Service (QoS) provisioning is an inherently complex and difficult issue. In this paper, we propose a fully distributed and adaptive algorithm to provide statistical QoS guarantees with respect to accessibility of services in an ad-hoc network. In this algorithm, we focus on the optimization of a new QoS parameter of interest, service efficiency, while keeping protocol overheads to the minimum. To achieve this goal, we first theoretically derive the lower and upper bounds of service efficiency based on a novel model for group mobility, followed by extensive simulation results to verify the effectiveness of our algorithm.
8595308
Experiences with MPEG-4 multimedia streaming
With the advent of next-generation multimedia technologies such as very-low bit rate MPEG-4 codec, multimedia streaming of high-quality video and audio has become a near-term reality. The high compression ratio and error resilience offered by the MPEG-4 standard promise near-term popularity for rich contents and exceptional quality to consumers over affordable Internet connections, such as xDSL, cable modem and 3G wireless networks. Audio and video streaming applications are at the center of such scenarios; and Quality-of-Service (QoS) support in such applications is critical to their widespread acceptance.To the best of our knowledge, there has been no existing open-source MPEG-4 multimedia streaming applications in the academic community, which leads to the lack of research results using MPEG-4 streaming, especially with respect to Quality-of-Service support. In this work, we have implemented an open-source MPEG-4 multimedia streaming testbed in IP-based networks. In this paper, we show our experiences and lessons learned with such a testbed. First, we describe the algorithms and solutions used in our implemention testbed, emphasizing several critical issues. Second, through extensive experiments, we demonstrate measurements of bandwidth requirements and data loss for streaming a set of multimedia samples with different bit rates over UDP, which is ubiquitously available in the TCP/IP protocol stack on all consumer operating systems. Finally, future work for further improvements is also discussed.
5530667
On achieving optimized capacity utilization in application overlay networks with multiple competing sessions
In this paper, we examine the problem of large-volume data dissemination via overlay networks. A natural way to maximize the throughput of an overlay multicast session is to split the traffic and feed them into multiple trees. While in single-tree solutions, bandwidth of leaf nodes may remain largely under-utilized, multi-tree solutions increase the chances for a node to contribute its bandwidth by being a relaying node in at least one of the trees. We study the following problems: (1) What is the maximum capacity multi-tree solutions can exploit from overlay networks? (2) When multiple sessions compete within the same network, what is the relationship of two contradictory goals: achieving fairness and maximizing overall throughput? (3) What is the impact of IP routing in achieving at constraining the optimal performance of overlay multicast.We extend the multicommodity flow model to the case of overlay data dissemination, where each commodity is associated with an overlay session, rather than the traditional source-destination pair. We first prove that the problem is solvable in polynomial time, then propose an ε-approximation algorithm, assuming that each commodity can be split in arbitrary ways. The solution to this problem establishes the theoretical upper bound of overall throughput that any multi-tree solution could reach. We then study the same problem with the restriction that each commodity can only be split and fed into a limited number of trees. A randomized rounding algorithm and an online tree-construction algorithm are presented. All these algorithms are evaluated by extensive simulations.
7321726
A gateway-assisted approach toward QoS adaptations
We present a gateway-assisted QoS adaptation framework which satisfies high-level QoS application guarantees. We validate this framework via a distributed tracking system and show provisioning of critical QoS guarantees despite the best effort underlying resource management.
1974741
Strategyproof Mechanisms towards Dynamic Topology Formation in Autonomous Networks
In autonomous networks, cooperations among nodes cannot be assumed, since each node is capable of making independent decisions based on their personal preferences. In particular, when a node needs the help of intermediate nodes to relay messages to other nodes, these intermediaries may be reluctant to contribute their network resource for the benefit of others. Ideally, the right amount of incentives should be provided to motivate cooperations among autonomous nodes so that a mutually beneficial network results. In this paper, we leverage the power of mechanism design in microeconomics to design a distributed incentive mechanism that motivates each node towards a more desirable network topology. Since network parameters and constraints change dynamically in reality, the desirable topology can vary over time. Our solution presented in this paper has successfully encompassed such a dynamic nature of the network topology. In addition, we have transformed our solution to an easy-to-implement distributed algorithm, that converges towards the globally optimal topology.
1260337
An Improved k-Nearest Neighbor Algorithm for Text Categorization
k is the most important parameter in a text categorization system based on k-Nearest Neighbor algorithm (kNN).In the classification process, k nearest documents to the test one in the training set are determined firstly. Then, the predication can be made according to the category distribution among these k nearest neighbors. Generally speaking, the class distribution in the training set is uneven. Some classes may have more samples than others. Therefore, the system performance is very sensitive to the choice of the parameter k. And it is very likely that a fixed k value will result in a bias on large categories. To deal with these problems, we propose an improved kNN algorithm, which uses different numbers of nearest neighbors for different categories, rather than a fixed number across all categories. More samples (nearest neighbors) will be used for deciding whether a test document should be classified to a category, which has more samples in the training set. Preliminary experiments on Chinese text categorization show that our method is less sensitive to the parameter k than the traditional one, and it can properly classify documents belonging to smaller classes with a large k. The method is promising for some cases, where estimating the parameter k via cross-validation is not allowed.
14227223
Bridging the semantic gap in sports video retrieval and summarization
One of the major challenges facing current media management systems and related applications is the so-called ''semantic gap'' between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs, with a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. We implemented an MPEG-7 compliant browsing system for semantic retrieval and summarization of sports video using the proposed algorithms.
12626074
Dynamic routing and wavelength assignment in the presence of wavelength conversion for all-optical networks
Blocking probability has been one of the key performance indexes in the design of wavelength-routed all-optical WDM networks. Existing research has demonstrated that an effective Routing and Wavelength Assignment (RWA) algorithm and wavelength conversion are two primary vehicles for improving the blocking performance. However, these two issues have largely been investigated separately; in particular the existing RWA algorithms have seldom considered the presence of wavelength conversion. In this paper, we firstly demonstrate that the existing dynamic RWA algorithms do not work well in the presence of wavelength conversion as they usually only take into account the current traffic, and do not explicitly consider the route lengths. We then propose a weighted least-congestion routing and first-fit wavelength assignment (WLCR-FF) algorithm that considers both the current traffic load and the route lengths jointly. We further introduce an analytical model that can evaluate the blocking performance for WLCR algorithm. We carry out extensive numerical studies over typical topologies including ring, mesh-torus, and the 14-node NSFNET; and compare the performance of WLCR-FF with a wide variety of existing routing algorithms including static routing, fixed-alternate routing and least-loaded routing. The results conclusively demonstrate that the proposed WLCR-FF algorithm can achieve much better blocking performance in the presence of sparse or/and full wavelength conversion.
1669054
Nonconforming finite element approximation of crystalline microstructure
We consider a class of nonconforming nite element approxima- tions of a simply laminated microstructure which minimizes the nonconvex variational problem for the deformation of martensitic crystals which can un- dergo either an orthorhombic to monoclinic (double well) or a cubic to tetrag- onal (triple well) transformation. We rst establish a series of error bounds in terms of elastic energies for the L 2 approximation of derivatives of the de- formation in the direction tangential to parallel layers of the laminate, for the L 2 approximation of the deformation, for the weak approximation of the de- formation gradient, for the approximation of volume fractions of deformation gradients, and for the approximation of nonlinear integrals of the deformation gradient. We then use these bounds to give corresponding convergence rates for quasi-optimal nite element approximations.
46149042
Data reconciliation for real-time optimization of an industrial coke-oven-gas purification process
Online optimization is more and more used in the chemical industry to run a process near its optimum operating condition by providing real-time computed optimal set-points to the distributed control system. Process measurements are necessary for these applications to determine the actual state of the process and to increase the accuracy of the model with parameter estimation techniques. However, these measurements usually contain random as well as gross errors which have to be identified and eliminated before the measurements are used for online optimization. In this contribution, a data reconciliation approach was integrated into an online optimization framework for the ammonia hydrogen sulfide circulation scrubbing, a common industrial coke-oven-gas purification process. We used a rigorous rate-based model to describe this reactive absorption and desorption process. To increase the accuracy of the model, we estimated several process parameters using a sequential parameter estimation approach. Data reconciliation was performed based on simple component balances to achieve model-consistent data and to identify measurement biases. The model was then validated online on a pilot plant by connecting the estimation package through the process control system. Based on the online measured data, operating cost minimization was carried out and the computed optimal set-points realized real-time. A satisfactory agreement between measured data and optimization was achieved.