Mining Large Graphs through Subgraph Sampling

Given the growing significance of online interactions in our daily lives, the Web graph and the graph of online social networks are of scholarly interest to not just computer scientists but also mathematicians, sociologists and economists. However, the size and complexity of these Big Data graphs have always posed significant challenges, limiting the scope of their analysis and thus also limiting the implications that one can draw from them. A comprehensive analysis of these graphs has usually required access to large distributed computing platforms and sophisticated software such as MapReduce and Google Pregel. The proposed project aims to address a portion of these challenges by investigating a new method, based in statistics and spectral graph theory, to infer essential properties of the full graph through extracting a representative sample of small subgraphs from the full graph. The goal is to reduce the computational burden on researchers interested in large graphs and thus broaden participation in Big Data activities.

This project is partially funded by NSF Award 1250786 (2013-2018)

Anomaly Detection for Security in Wireless Networks

Many new techniques developed in statistics and signal processing (e.g., compressive sampling) offer new and promising but heretofore untested approaches to anomaly detection in wireless networks. This project will test the feasibility, the efficacy and the limitations of these approaches in a real network, while also developing recommendations for practitioners. A key focus is on development and evaluation of distributed algorithms to accomplish real-time monitoring and early detection of anomalous behavior such as those caused by a spreading worm or a security vulnerability under exploitation. Motivated by both theoretical insights and practical considerations, the project makes contributions to anomaly detection in computing systems drawing from a variety of fields including data science, machine learning, statistics and signal processing.

This project is partially funded by NSF Award 1228847 (2012-2018)

An Integrated Environment-Independent Approach to Topology Control

This project, in collaboration with Lehigh University and the University of North Carolina at Charlotte, seeks to design topology control algorithms in wireless ad hoc networks with a particular focus on two philosophical goals: an environment-independent approach which makes no constraining assumptions about the wireless environment and an integrated approach that does not separate the problem of topology control from other problems such as routing and scheduling. A key goal of this project is to explore fundamental theoretical limits of the environment-independent approach.

This project is partially funded by NSF Award 0915393 (2009-2013)

Coverage Control in Heterogeneous Sensor Networks

Sensor nodes are often equipped with a suite of sensing capabilities (e.g., temperature, light, sound) but only a subset of these may need to be activated at any given node. Given data collection requirements in a heterogeneous sensor network, this project invesigates issues of spatial placement for each type of sensing capability over the region of interest while maximizing energy conservation. Coverage issues considered include evenness of coverage, fullness of coverage and the graceful degradation of coverage during the lifespan of the network.

This project is partially funded by NSF Award 0626548 (2006-2010)

Security through Improved Network-wide Diversity

In this project, we investigate network-wide diversity a viable security strategy against viruses and other malcode. We examine tradeoffs between the quality of diversity and the resulting tolerance to attacks. The project concludes that not only is diversity critical for improving the attack tolerance of a network, but diversity must be applied at all levels of system design including mechanisms to introduce the diversity itself.

This work was partially funded by an NSF Graduate Research Fellowship (2003-2006).

Topology Control for Mobile Ad Hoc Networks

Topology control for energy conservation has largely been examined only for ad hoc networks with stationary nodes (e.g., most sensor networks). This project seeks to develop new topology control algorithms and related strategies that take mobility into account and quantifies trade-offs between energy conservation, degree of mobility, and connectivity.

This project was partially funded by the SMART Defense Scholarship for Service Program (2008-2009) and by NSF Award CNS-0322797.

Fair Packet Scheduling Algorithms in the Internet

Fairness in the allocation of resources in a network shared among multiple flows of traffic is an intuitively desirable property with many practical benefits. Fairness in traffic management can improve the isolation between traffic streams, offer a more predictable performance, eliminate certain kinds of transient bottlenecks and may serve as a critical component of a strategy to achieve certain guaranteed services such as delay bounds and minimum bandwidths. This project investigates fundamental principles and practical strategies for fair allocation across a single as well as multiple resources such as bandwidth, buffer and the router processor.

This project was partially funded by NSF CAREER Award CCR-9984161 (2000-2006) and by DARPA.

Network Economics

In this work, we investigate practical, flexible and computationally simple pricing strategies that can achieve QoS provisioning in Differentiated Services networks with multiple priority classes operating in an efficient economic market, while also maintaining stable transmission rates from end-users. The project proposes to add a separate price component for the preferential service received by a packet in order to permit achieve automatic and efficient capacity management in the allocation of resources among the various service classes.

This work was partially funded by Drexel University's ECE Colehower Endowed Fellowship.

Simulation of Mobile Ad Hoc Networks

The goal of this effort was to investigate a variety of performance and quality-of-service issues in mobile ad hoc networks through simulation experiments in OPNET and ns-2. Improving simulation technologies for faster real-time simulation was also a goal.

This set of efforts was funded through four different grants from CERDEC, two grants from Lockheed Martin Corporation, and one grant from Northrop Grumman Corporation during the years 2001-2005.

Fair and Low-Latency Switch Design

In this project, we consider an input-queued switch based on the virtual-output-queueing architecture wherein each flow shares the bandwidth at its input and output ports with other flows. We develop idealized as well as practical and distributed algorithms for scheduling packets for two separate goals: low-latency and fairness.

This project was partially funded by NSF CAREER Award CCR-9984161 (2000-2006) and by DARPA.

Network-layer Strategies for Wireless Ad Hoc Networks with Smart Antennas

This project identified three aspects related to smart antennas that have significant implications on medium access strategies, routing algorithms and higher layers in a wireless ad hoc network: directional transmissions, stream control, and accommodation of spatial diversity. As part of this project, our work has examined each of the above three implications of smart antennas and proposed new algorithms for medium access, topology control, avoidance of receiver overloading and exploitation of flexible interference suppression.

This project was partially funded by NSF Award CNS-0322797 (2003-2007)