Engineering Commons^™

Camouflaging Timing Channels In Web Traffic, Sarah H. Sellke, Chih-Chun Wang, Saurabh Bagchi, Ness B. Shroff

Department of Electrical and Computer Engineering Technical Reports

Web traffic accounts for more than half of Internet traffic today. Camouflaging covert timing channels in Web traffic would be advantageous for concealment. In this paper, we investigate the possibility of disguising network covert timing channels as HTTP traffic to avoid detection. Extensive research has shown that Internet traffic, including HTTP traffic, exhibits self-similarity and long range persistence. Existing covert timing channels that mimic i.i.d. legitimate traffic cannot imitate HTTP traffic because these covert traffic patterns are not long range dependent. The goal of this work is to design a covert timing channel that can be camouflaged as HTTP traffic. …

A Parallel Direct Solver For The Simulation Of Large-Scale Power/Ground Networks, Stephen Cauley, Venkataramanan Balakrishnan, Cheng-Kok Koh

Department of Electrical and Computer Engineering Technical Reports

We present an algorithm for the fast and accurate simulation of power/ground mesh structures. Our method is a direct (non-iterative) approach for simulation based upon a parallel matrix inversion algorithm. Through the use of additional computational resources, this distributed computing technique facilitates the simulation of large-scale power/ground networks. In addition, the new dimension of flexibility provided by our algorithm allows for a more accurate analysis of power/ground mesh structures using RLC interconnect models. Specifically, we offer a method that employs a sparse approximate inverse technique to consider more reluctance coupling terms for increased accuracy of simulation. The inclusion of additional …

Ccack: Efficient Network Coding Based Opportunistic Routing Through Cumulative Coded Acknowledgments, Dimitrios Koutsonikolas, Chih-Chun Wang, Y. Charlie Hu

Department of Electrical and Computer Engineering Technical Reports

The use of random linear network coding (NC) has significantly simplified the design of opportunistic routing (OR) protocols by removing the need of coordination among forwarding nodes for avoiding duplicate transmissions. However, NC-based OR protocols face a new challenge: How many coded packets should each forwarder transmit? To avoid the overhead of feedback exchange, most practical existing NC-based OR protocols compute offline the expected number of transmissions for each forwarder using heuristics based on periodic measurements of the average link loss rates and the ETX metric. Although attractive due to their minimal coordination overhead, these approaches may suffer significant performance …

Defining And Implementing Commutativity Conditions For Parallel Execution, Milind Kulkarni, Dimitrios Prountzos, Donald Nguyen, Keshav Pingali

Department of Electrical and Computer Engineering Technical Reports

Irregular applications, which manipulate complex, pointer-based data structures, are a promising target for parallelization. Recent studies have shown that these programs exhibit a kind of parallelism called amorphous data-parallelism. Prior approaches to parallelizing these applications, such as thread-level speculation and transactional memory, often obscure parallelism because they do not distinguish between the concrete representation of a data structure and its semantic state; they conflate metadata and data.

Exploiting the semantic commutativity of methods in complex data structures is a promising approach to exposing more parallelism. Prior work has shown that abstract locks can be used to capture a subset of …

Multicore-Aware Reuse Distance Analysis, Derek L. Schuff, Benjamin S. Parsons, Vijay S. Pai

Department of Electrical and Computer Engineering Technical Reports

This paper presents and validates methods to extend reuse distance analysis of application locality characteristics to shared-memory multicore platforms by accounting for invalidation-based cache-coherence and inter-core cache sharing. Existing reuse distance analysis methods track the number of distinct addresses referenced between reuses of the same address by a given thread, but do not model the effects of data references by other threads. This paper shows several methods to keep reuse stacks consistent so that they account for invalidations and cache sharing, either as references arise in a simulated execution or at synchronization points. These methods are evaluated against a Simics-based …

An Error Bound For The Sensor Scheduling Problem, Wei Zhang, Jianghai Hu, Michael P. Vitus

Department of Electrical and Computer Engineering Technical Reports

The sensor scheduling problem tries to select one out of multiple available sensors at each time step to minimize a weighted sum of all the estimation errors over a certain time horizon. The problem can be solved by enumerating all the possible schedules. The complexity of such an enumeration approach grows exponentially fast as the horizon increases. In this report, by introducing some numerical relaxation parameter, we develop an efficient way to compute a suboptimal sensor schedule. It is shown that by choosing the relaxation parameter small enough, the performance of the obtained suboptimal schedule can be made arbitrarily close …

Evaluation Of Regression Ensembles On Drug Design Datasets, M. Fatih Amasyali, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Studies on drug design datasets are continuing to grow. These datasets are usually known as hard modeled, having a large number of features and a small number of samples. The most common problems in the drug design area are of regression type. Committee machines (ensembles) have become popular in machine learning because of their high performance. In this study, dynamics of ensembles on regression related drug design problems are investigated on a big dataset collection. The study tries to determine the most successful ensemble algorithm, the base algorithm-ensemble pair having the best / worst results, the best successful single algorithm, …

Prediction Of Disorder With New Computational Tool: Bvdea, Irem Ersoz Kaya, Turgay Ibrikci, Okan K. Ersoy

Department of Electrical and Computer Engineering Technical Reports

Motivation: Recognizing that many intrinsically disordered regions in proteins play key roles in vital functions and also in some diseases, identification of the disordered regions has became a demanding process for structure prediction and functional characterization of proteins. Therefore, many studies have been motivated on accurate prediction of disorder. Mostly, machine learning techniques have been used for dealing with the prediction problem of disorder due to the capability of extracting the complex relationships and correlations hidden in large data sets. Results: In this study, a novel method, named Border Vector Detection and Extended Adaptation (BVDEA) was developed for predicting disorder …

A Study Of Meta Learning For Regression, M. Fatih Amasyali, Okan K. Ersoy

Department of Electrical and Computer Engineering Technical Reports

In regression applications, there is no single algorithm which performs well with all data since the performance of an algorithm depends on the dataset used. In practice, different algorithms / approaches are tried, and the best one is selected in each application. It is meaningful to ask whether there is a different way instead of running such tedious experiments. In meta learning studies, one investigates clues for the performance of an algorithm over a dataset using several features of the dataset. In this context, it is important to estimate which dataset features (meta features) are most significant for the performance …

How To Keep Your Head Above Water While Detecting Errors, Saurabh Bagchi, Ignacio Laguna, Fahad Arshad, David M. Grothe

Department of Electrical and Computer Engineering Technical Reports

Abstract. Today’s distributed systems need runtime error detection to catch errors arising from software bugs, hardware errors, or unexpected operating conditions. A prominent class of error detection techniques operates in a stateful manner, i.e., it keeps track of the state of the application being monitored and then matches state-based rules. Large-scale distributed applications generate a high volume of messages that can overwhelm the capacity of a stateful detection system. An existing approach to handle this is to randomly sample the messages and process the subset. However, this approach, leads to non-determinism with respect to the detection system’s view of what …

A Study Of The Discrete-Time Switched Lqr Problem, Wei Zhang, Jianghai Hu, Alessandro Abate

Department of Electrical and Computer Engineering Technical Reports

This paper studies the discrete-time switched LQR (DSLQR) problem based on a dynamic programming approach. One contribution of this paper is the analytical characterization of both the value function and the optimal hybridcontrol strategy of the DSLQR problem. Their connections to the Riccati equation and the Kalman gain of the classical LQR problem are also discussed. Several interesting properties of the value functions are derived. In particular, we show that under some mild conditions, the family of finite-horizon value functions of the DSLQR problem is homogeneous (of degree 2), uniformly bounded over the unit ball, and converges exponentially fast to …

Support Vector Selection And Adaptation For Classification Of Remote Sensing Images, Gulsen Taskin Kaya, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Classification of nonlinearly separable data by nonlinear support vector machines is often a difficult task especially due to the necessity of a choosing a convenient kernel type. In this study, we propose a new classification method called support vector selection and adaptation (SVSA) that is applicable to both linearly and nonlinearly separable data in terms of some reference vectors generated by processing of support vectors obtained from the linear SVM. The method consists of two steps called selection and adaptation. In these two steps, once the support vectors are obtained by a linear SVM, some of them are rejected and …

Stabilizing Switched Linear Systems With Unstabilizable Subsystems, Wei Zhang, Jianghai Hu, Alessandro Abate

Department of Electrical and Computer Engineering Technical Reports

Abstract This paper studies the exponential stabilization problem for discrete-time switched linear systems based on a control-Lyapunov function approach. A number of versions of converse control-Lyapunov function theorems are proved and their connections to the switched LQR problem are derived. It is shown that the system is exponentially stabilizable if and only if there exists a finite integer N such that the N-horizon value function of the switched LQR problem is a control-Lyapunov function. An efficient algorithm is also proposed which is guaranteed to yield a control-Lyapunov function and a stabilizing strategy whenever the system is exponentially stabilizable.

Remote Sensing Methods By Compressive Sensing, Atul Divekar, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Compressive Sensing is a recently developed technique that exploits the sparsity of naturally occurring signals and images to solve inverse problems when the number of samples is less than the size of the original signal. We apply this technique to solve underdetermined inverse problems that commonly occur in remote sensing, including superresolution, image fusion and deconvolution. We use l1-minimization to develop algorithms that perform as well as or better than conventional methods for these problems. Our algorithms use a library of samples from similar images or a model for the image to be reconstructed to express the image as a …