7260523
Providing statistical delay guarantees in wireless networks
We study the delay performance of policed traffic to provide real-time guarantees over wireless networks. A number of models have been presented in the literature to describe wireless (radio or optical) networks in terms of the wireless channel and the underlying error control mechanisms. We describe a general framework to incorporate such models into delay guarantee computations for real-time traffic. Static-priority scheduling is considered, and two different admission control mechanisms are used to achieve the trade-off between resource utilization and admission overhead.
5741503
A new scheme on privacy-preserving data classification
We address privacy-preserving classification problem in a distributed system. Randomization has been the approach proposed to preserve privacy in such scenario. However, this approach is now proven to be insecure as it has been discovered that some privacy intrusion techniques can be used to reconstruct private information from the randomized data tuples. We introduce an algebraic-technique-based scheme. Compared to the randomization approach, our new scheme can build classifiers more accurately but disclose less private information. Furthermore, our new scheme can be readily integrated as a middleware with existing systems.
6827646
Design and implementation of QoS-provisioning system for voice over IP
In this paper, we address issues in implementing voice over IP (VoIP) services in packet switching networks. VoIP has been identified as a critical real-time application in the network QoS research community and has been implemented in commercial products. To provide competent quality of service for VoIP systems comparable to traditional PSTN systems, a call admission control (CAC) mechanism has to be introduced to prevent packet loss and over-queuing. Several well-designed CAC mechanisms, such as the site-utilization-based CAC-and the link-utilization-based CAC mechanisms have been in place. However, the existing commercial VoIP systems have not been able to adequately apply and support these CAC mechanisms and, hence, have been unable to provide QoS guarantees to voice over IP networks. We have designed and implemented a QoS-provisioning system that can be seamlessly integrated with the existing VoIP systems to overcome their weakness in offering QoS guarantees. A practical implementation of our QoS-provisioning system has been realized.
8639082
Delay Analysis in Temperature-Constrained Hard Real-Time Systems with General Task Arrivals
In this paper, we study temperature-constrained hard real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processor. Dynamic speed scaling is one of the major techniques to manage power so as to maintain safe temperature levels. As example, we adopt a simple reactive speed control technique in our work. We design a methodology to perform delay analysis for general task arrivals under reactive speed control with first-in-first-out (FIFO) scheduling and static-priority (SP) scheduling. As a special case, we obtain a close-form delay formula for the leaky-bucket task arrival model. Our data show how simple reactive speed control can decrease the delay of tasks compared with any constant-speed scheme
6847194
Analyzing the secure overlay services architecture under intelligent DDoS attacks
Distributed denial of service (DDoS) attacks are currently major threats to communication in the Internet. A secure overlay services (SOS) architecture has been proposed to provide reliable communication between clients and a target under DDoS attacks. The SOS architecture employs a set of overlay nodes arranged in three hierarchical layers that controls access to the target. Although the architecture is novel and works well under simple congestion based attacks, we observe that it is vulnerable under more intelligent attacks. We generalize the SOS architecture by introducing more flexibility in layering to the original architecture. We define two intelligent DDoS attack models and develop an analytical approach to study the impacts of the number of layers, number of neighbors per node and the node distribution per layer on the system performance under these two attack models. Our data clearly demonstrate that performance is indeed sensitive to the design features and the different design features interact with each other to impact overall system performance.
15576082
Real-time component-based systems
Component technology has become a central focus of software engineering in research and development. Reusability is a key factor that contributes to its success. The reuse of components can lead to a shortening of software development cycles and savings in software development costs. However, existing component models provide no support for real-time services and some real-time extensions of component models lack of consideration for reusability of components in providing real-time services. In this work, we develop a real-time component-based system that maintains the reusability of components.
210649
Combining Statistical Language Models via the Latent Maximum Entropy Principle
We present a unified probabilistic framework for statistical language modeling which can simultaneously incorporate various aspects of natural language, such as local word interaction, syntactic structure and semantic document information. Our approach is based on a recent statistical inference principle we have proposed—the latent maximum entropy principle—which allows relationships over hidden features to be effectively captured in a unified model. Our work extends previous research on maximum entropy methods for language modeling, which only allow observed features to be modeled. The ability to conveniently incorporate hidden variables allows us to extend the expressiveness of language models while alleviating the necessity of pre-processing the data to obtain explicitly observed features. We describe efficient algorithms for marginalization, inference and normalization in our extended models. We then use these techniques to combine two standard forms of language models: local lexical models (Markov N-gram models) and global document-level semantic models (probabilistic latent semantic analysis). Our experimental results on the Wall Street Journal corpus show that we obtain a 18.5% reduction in perplexity compared to the baseline tri-gram model with Good-Turing smoothing.
45928612
Transmission Range Designation Broadcasting Methods for Wireless Ad Hoc Networks
The broadcast operation in ad hoc wireless networks is essential, but expensive in terms of power consumption. In DP (dominant pruning) algorithms, the number of forward nodes is treated as a criterion to measure the consumed power. However, this principle is not suitable anymore if the power-adaptive characteristic is supported and each node can detect the strength of a received packet and tune its transmission power level. Thus, in this paper, we propose a modified version of the DP algorithm with the objective being to minimize the total power consumption of forward nodes. Comparing with original DP algorithms, the sender in our algorithm not only chooses its forward nodes, but also designates the transmission ranges of its forward nodes. As a result, the designated transmission ranges not only maintain the same coverage as DP algorithms, but also reduce the total power consumption. We propose a new forward nodes selection process where the weight of a node is dependent on the incremental transmission cost rather than the effective degree. Although the resultant number of forward nodes in the proposed approach is often greater than DP algorithms, the power consumption shown in simulations is less than DP algorithms.
35913610
Knowledge Discovery Through Self-Organizing Maps: Data Visualization and Query Processing
Abstract. In data mining, the usefulness of a data pattern depends on the user of the database and does not solely depend on the statistical strength of the pattern. Based on the premise that heuristic search in combinatorial spaces built on computer and human cognitive theories is useful for effective knowledge discovery, this study investigates how the use of self-organizing maps as a tool of data visualization in data mining plays a significant role in human–computer interactive knowledge discovery. This article presents the conceptual foundations of the integration of data visualization and query processing for knowledge discovery, and proposes a set of query functions for the validation of self-organizing maps in data mining.
18089723
Globally Optimal Grouping for Symmetric Boundaries
Many natural and man-made structures have a boundary that shows certain level of bilateral symmetry, a property that has been used to solve many computer-vision tasks. In this paper, we present a new grouping method for detecting closed boundaries with symmetry. We first construct a new type of grouping token in the form of a symmetric trapezoid, with which we can flexibly incorporate various boundary and region information into a unified grouping cost function. Particularly, this grouping cost function integrates Gestalt laws of proximity, closure, and continuity, besides the desirable boundary symmetry. We then develop a graph algorithm to find the boundary that minimizes this grouping cost function in a globally optimal fashion. Finally, we test this method by some experiments on a set of natural and medical images.
1997167
Open-Curve Shape Correspondence Without Endpoint Correspondence
Shape correspondence is the foundation for accurate statistical shape analysis; this is usually accomplished by identifying a set of sparsely sampled and well-corresponded landmark points across a population of shape instances. However, most available shape correspondence methods can only effectively deal with complete-shape correspondence, where a one-to-one mapping is assumed between any two shape instances. In this paper, we present a novel algorithm to correspond 2D open-curve partial-shape instances where one shape instance may only be mapped to part of the other, i.e., the endpoints of these open-curve shape instances are not presumably corresponded. In this algorithm, some initially identified landmarks, including the ones at or near the endpoints of the shape instances, are refined by allowing them to slide freely along the shape contour to minimize the shape-correspondence error. To avoid being trapped into local optima, we develop a simple method to construct a better initialization of the landmarks and introduce some additional constraints to the landmark sliding. We evaluate the proposed algorithm on 32 femur shape instances in comparison to some current methods.