Networking at ODU-CS
Intelligent Networking and Systems (iNetS) Research Group in the Department of Computer Science at Old Dominion University



This project focuses on the development of ALERT: An Architecture for the Emergency Re-tasking of Wireless Sensor Networks. The novelty of this work lies in the theoretical foundation of re-tasking independently-deployed sensor networks, leading to a fundamental understanding of the design principles of capability reallocation and sharing to best satisfy the needs of emergency applications. Both re-tasking and integration of sensor capabilities will be transparent to the emergency applications. The resource-constrained nature of sensors, the wireless communication medium, and the failure-prone networking environment, combined with the dynamic QoS requirements of the emergency applications pose formidable challenges for the design of ALERT.

The understanding acquired from developing ALERT will promote a wider adoption of sensor network systems in support of guarding our national infrastructure and public safety. This project will result in significant scientific and technological advances that will provide invaluable help with disaster management and search-and-rescue operations. ALERT will have a broad societal impact as sensor networks are being integrated into the fabric of the society. The project will integrate research and education and will lead to the development of new graduate and undergraduate courses in sensor networks and embedded and distributed systems. In turn, these courses and their focus on information integration will introduce novel research topics to undergraduate and graduate students in computer science and engineering that fit within the overall missions of Old Dominion University and Clemson University. Focused efforts will be undertaken to stimulate interest and to facilitate the academic progress of women and underrepresented minorities.

Project Website

Funding: CSR: An Architecture for the Emergency Re-tasking of Wireless Sensor Networks (ALERT), Michele C. Weigle and Stephan Olariu, NSF - CNS 1116238, Aug 2011-Aug 2014, $358,549 to ODU (total: $440,000).

With Jason Hallstrom (Clemson)

Past Projects


Highway congestion due to traffic incidents costs billions of dollars in lost productivity and billions of gallons in wasted fuel. With advance notification of traffic congestion, drivers could make educated decisions about taking alternate routes, thus saving time and fuel. Recently, systems using vehicular ad-hoc networks (VANETs) that employ vehicle-to-vehicle (V2V) communications have been proposed for this purpose. Unfortunately, relying solely on V2V communications has the undesired side effect of inviting the introduction of false alerts and misleading messages.

This project takes a novel look at solving the problem of propagating traffic-related information in VANETs in a secure and privacy-preserving manner. The goal of this project is to develop and evaluate an architecture for the Notification of Traffic Incidents and Congestion (NOTICE). NOTICE consists of sensor belts embedded in the roadway at regular intervals. Vehicles passing over a belt will provide information about their travel directly to the belt. The collective information stored by the belts will be used to make intelligent inferences about the occurrence of traffic incidents. NOTICE will provide secure and privacy-preserving communications between vehicles and the belts, efficiently propagate incident information to vehicles, and infer the presence of traffic congestion without driver intervention.

Project Website

Funding: NeTS-WN: An Architecture for the Notification of Traffic Incidents and Congestion (NOTICE), Michele C. Weigle and Stephan Olariu, NSF - CNS 0721586, 2007-2011, $400,000.


Aggregations of massively deployed sensors are expected to create sophisticated sensing, computation, communication and control platforms called Networked Sensor Systems (NSS) that will pervade society, revolutionizing the way in which we live and work. In order to scale, these systems must be largely autonomous, decentralized entities whose corporate resources can be made available to authorized users. Such autonomous, geographically-dispersed NSS are increasingly recognized as key to numerous applications ranging from healthcare to smart homes and homeland security. For example, autonomous NSS can assist first responders, often in inhospitable environments, by locating survivors, identifying danger areas and enhancing user awareness of the situation The resource-constrained sensors, the wireless communication medium, the large-scale deployment, combined with the mobility of users, the close interaction with the physical environment and the highly sensitive nature of mission-critical operations pose formidable challenges to autonomous NSS design. The key inter-related technical contributions of this project are:

  1. Dynamic task-based networking supporting application-level tasks and queries while hiding resource-level details;
  2. Smart AFN mobility subject to changing application requirements and network conditions; and
  3. providing secure ANSWER operation and multi-level secure interactions with in-situ mobile users.

The ANSWER prototype can serve as a tool to explore mobile user behavior in ubiquitous networks under varying environmental and network conditions.

Funding: NeTS-NOSS: AutoNomouS netWorked sEnsoR Systems (ANSWER), Stephan Olariu, NSF - CNS 0721563, 2007-2011, $142,840.

With Mohamed Younis (UMBC) and Scott Midkiff (Virginia Tech)


Networking research has long relied on simulation as the primary vehicle for demonstrating the effectiveness of proposed protocols and mechanisms. Typically, one simulates network hardware and software in software using, for example, the widely used ns-2 simulator. Experimentation proceeds by simulating the use of the network by a given population of users using applications such as ftp or web browsers. Synthetic workload generators are used to inject data into the network according to a model of how the applications or users behave.

In order to perform realistic network simulations, one needs a traffic generator that is capable of generating realistic synthetic traffic in a closed-loop fashion that "looks like" traffic found on an actual network. Unfortunately, the networking community suffers from a lack of validated tools and models suitable for synthetic traffic generation. As a result, all too often, networking technology is evaluated using ad hoc workloads with an unknown relationship to traffic seen on real links and hence begs the question of how believable the results of the evaluation are.

This project is a collaborative effort to develop a synthetic traffic generation resource for the experimental networking research community. The resource consists of

  1. synthetic traffic generators for the ns-2, ns-3, and GTNets software simulators, and Linux and BSD-based testbeds,
  2. a repository of datasets to be used by the traffic generators to generate traffic that is statistically equivalent to traffic found on a variety of network links including campus networks, wide-area backbone networks, corporate intranets, wireless networks, etc, and
  3. a set of traffic analysis tools to enable researchers to generate empirical models of traffic on network links of interest and to use these models to drive the synthetic traffic generation process.

Project Website

Funding: CRI: CRD: Synthetic Traffic Generation Tools and Resources: A Community Resource for Experimental Networking Research, Michele C. Weigle, NSF - CNS 0709058, 2007-2011, $201,794.

With Kevin Jeffay (UNC), F. D. Smith (UNC), Paul Barford (Wisconsin), and Amin Vahdat (UCSD)