We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

We propose a natural scene statistic-based distortion-generic blind/no-reference (NR) image quality assessment (IQA) model that operates in the spatial domain. The new model, dubbed blind/referenceless image spatial quality evaluator (BRISQUE) does not compute distortion-specific features, such as ringing, blur, or blocking, but instead uses scene statistics of locally normalized luminance coefficients to quantify possible losses of “naturalness” in the image due to the presence of distortions, thereby leading to a holistic measure of quality. The underlying features used derive from the empirical distribution of locally normalized luminances and products of locally normalized luminances under a spatial natural scene statistic model. No transformation to another coordinate frame (DCT, wavelet, etc.) is required, distinguishing it from prior NR IQA approaches. Despite its simplicity, we are able to show that BRISQUE is statistically better than the full-reference peak signal-to-noise ratio and the structural similarity index, and is highly competitive with respect to all present-day distortion-generic NR IQA algorithms. BRISQUE has very low computational complexity, making it well suited for real time applications. BRISQUE features may be used for distortion-identification as well. To illustrate a new practical application of BRISQUE, we describe how a nonblind image denoising algorithm can be augmented with BRISQUE in order to perform blind image denoising. Results show that BRISQUE augmentation leads to performance improvements over state-of-the-art methods. A software release of BRISQUE is available online: http://live.ece.utexas.edu/research/quality/BRISQUE_release.zip for public use and evaluation.

/pdf/no-reference-image-quality-assessment-in-the-spatial-domain-2mnlvf25ig.pdf

No-Reference Image Quality Assessment in the Spatial Domain

An important aim of research on the blind image quality assessment (IQA) problem is to devise perceptual models that can predict the quality of distorted images with as little prior knowledge of the images or their distortions as possible. Current state-of-the-art “general purpose” no reference (NR) IQA algorithms require knowledge about anticipated distortions in the form of training examples and corresponding human opinion scores. However we have recently derived a blind IQA model that only makes use of measurable deviations from statistical regularities observed in natural images, without training on human-rated distorted images, and, indeed without any exposure to distorted images. Thus, it is “completely blind.” The new IQA model, which we call the Natural Image Quality Evaluator (NIQE) is based on the construction of a “quality aware” collection of statistical features based on a simple and successful space domain natural scene statistic (NSS) model. These features are derived from a corpus of natural, undistorted images. Experimental results show that the new index delivers performance comparable to top performing NR IQA models that require training on large databases of human opinions of distorted images. A software release is available at http://live.ece.utexas.edu/research/quality/niqe_release.zip.

/pdf/making-a-completely-blind-image-quality-analyzer-4rsald8tn3.pdf

Making a “Completely Blind” Image Quality Analyzer

Over the past decade, there has been an explosion of interest in network research across the physical and social sciences. For social scientists, the theory of networks has been a gold mine, yielding explanations for social phenomena in a wide variety of disciplines from psychology to economics. Here, we review the kinds of things that social scientists have tried to explain using social network analysis and provide a nutshell description of the basic assumptions, goals, and explanatory mechanisms prevalent in the field. We hope to contribute to a dialogue among researchers from across the physical and social sciences who share a common interest in understanding the antecedents and consequences of network phenomena.

/pdf/network-analysis-in-the-social-sciences-440fzedv4c.pdf

Network Analysis in the Social Sciences

I. the origin of species by means of natural selection

Unequal error protection (UEP) is essential when different portions of the source data do not contribute evenly to the overall duality of the decoded information. Conventional techniques achieve UEP by independent coding of the bit streams or by adopting conventional unequal error-protection codes. In this paper, we propose a practical alternative to the QPSK-based transmission systems with explicit UEP, such as GSM or IS-54 wireless transmission standards. In this scheme, the task of providing unequal protection is divided between the channel encoder and a nonuniform signal set, which discriminates in favor of the more important bits. The new approach allows for a simpler convolutional encoder and, hence, a less complex decoding procedure. Specifically, a reduction by more than half in the number of encoder states can easily be achieved using our scheme. Countering the degradation of the less important bits, we propose to adopt a high-rate punctured convolutional code to minimize the incurred transmission rate penalty. We also discuss a pilot sequence transmission scheme which realizes a coherent reception. Decentralizing the bit protection culminates in an extra degree of freedom which, in turn, introduces more flexibility into the system design.

Modulation-assisted unequal error protection over the fading channel

In this paper we discuss how to enable Software-Defined Networking (SDN) applications on Software-Defined Infrastructure (SDI) which is an approach for integrated control and management of converged computing and networking resources. Current separated resource management for computing or networking resources is not sufficient for addressing applications and multimedia services that require guaranteed service and quality levels. In addition, current resource management is not capable of managing heterogeneous resources that include computing and networking resources in combination with other resources such as programmable hardware, GPUs and network processors. We present an SDI that provides pluggable resource management modules for scheduling, networking control, fault management, and so on. This paper focuses on the design and implementation of a networking control module that enables SDN applications using information available from other modules. Currently, we have deployed the network control module in the practical multi-tier cloud infrastructure, SAVI Testbed. We present real measurements that show the functional evaluation results of our network control module.

Enabling SDN applications on Software-Defined Infrastructure

http://www.ece.iit.edu/~yucheng/YCheng_CompCom.pdf

A generic architecture for autonomic service and network management

This paper presents performance results that indicate that packetized voice service can be provided on a token-passing ring without adversely affecting the performance of data traffic. This is accomplished by introducing a relatively mild priority structure: stations are limited to a single packet transmission per medium access, and voice packets are given access priority over data packets at the same station. In addition, voice traffic is allowed longer packet lengths than data traffic. Several versions of this basic scheme are considered: 1) the number of active stations is constrained so that voice packets are guaranteed access within one packetization period, 2) no guarantee on access time is provided and voice packets are discarded when the waiting time exceeds one packetization period, and 3) no guarantee on access time is provided and voice packets are buffered until they can be transmitted.

Performance of Integrated Packet Voice/Data Token-Passing Rings

We address the problem of allocating transmission rates to a set of network sessions with end-to-end bandwidth and delay requirements. We give a unified convex programming formulation that captures both average and probabilistic delay requirements. Moreover, we present a distributed algorithm and establish its convergence to the global optimum of the overall rate allocation problem. In our algorithm, session sources selfishly update their rates as to maximize their individual benefit (utility minus bandwidth cost), the network partitions end-to-end delay requirements into local per-link delays, and the links adjust their prices to coordinate the sources' and network's decisions, respectively. This algorithm relies on a network utility maximization (NUM) approach, and can be viewed as a generalization of TCP and active queue management (AQM) algorithms to handle end-to-end QoS. We extend our results to deterministic delay requirements when nodes employ Packet-level Generalized Processor Sharing (PGPS) schedulers.

Alberto Leon-Garcia

Papers

Modulation-assisted unequal error protection over the fading channel

Enabling SDN applications on Software-Defined Infrastructure

A generic architecture for autonomic service and network management

Performance of Integrated Packet Voice/Data Token-Passing Rings

Optimal network rate allocation under end-to-end quality-of-service requirements