The Netgroup at the department of Computer Science and Engineering at University of Nebraska-Lincoln works on broad areas of Networking research with a focus on creating and building efficient, scalable, reliable, secure and cost-effective architectures and systems. Netgroup is working on a wide range of projects in the areas Networking and Security, with application to Optical Networks and Grids, Peer-to-Peer Networks, Software-Defined Networks, Wireless and Sensor Networks, Satellite Networks Network Security, and Secure Group Communication.
Some of the important aspects of the group’s research involve the design and development of novel architectures and solutions by combining cross-disciplinary approaches from network protocols and algorithms, network security, optimization, and graph theory.
Netgroup at UNL also works on Optical Networks Research, including work on Cloud/Grid infrastructure resource provisioning. We explore provisioning and optimization problems for virtualized cloud services in IP/MPLS over EON settings, multi-layer convergence, control and energy savings in optical core networks.
Research and Education networks (R&E) networks are undergoing a major transformation. At the campus level, implementations must balance performance, security, and the flexibility to handle innovative network applications research. Without adequate performance, the core application stakeholders would quickly leave; without security, the university networks would not allow integration of new approaches; without innovations, future leadership is at stake. The Holland Computing Center (HCC) at the University of Nebraska-Lincoln (UNL) campus has identified the need to increase the flexibility of UNL’s network to support scientific users and network researchers; UNL addresses this by deploying a production software-defined network (SDN) using OpenFlow.
This deployment enhances UNL’s HCC network through SDN, in three focused areas. First, it enhances resource management for GridFTP transfers by having the applications communicate with an SDN controller to set up paths and path properties for large transfers. By enabling communication between the applications and the network controller, we allow for application-driven bandwidth provisioning. Second, it integrates security with SDN-based dynamic routing so that only flows that require specific middleboxes be routed through them. This increases the scalability of the network by reducing the load on middleboxes and enabling automated reaction to security alerts raised by these devices. Third, it uses Content-Centric Networking (CCN) to provide access to the Compact Muon Solenoid (CMS) experiment data. CCN provides in-network caching and content-based routing. UNL leverages these techniques to efficiently deliver experiment data to scientific applications without always requiring access to the server where the data is stored.
The MobilityFirst project is founded on the premise that the Internet is approaching an historic inflection point, with mobile platforms and applications poised to replace the fixed-host/server model that has dominated the Internet since its inception. This predictable, yet fundamental, shift presents a unique opportunity to design a next generation Internet in which mobile devices, and applications, and the consequent changes in service, trustworthiness, and management are primary drivers of a new architecture. The major design goals of our proposed architecture are: mobility as the norm with dynamic host and network mobility at scale; robustness with respect to intrinsic properties of wireless medium; trustworthiness in the form of enhanced security and privacy for both mobile networks and wired infrastructure; usability features such as support for context-aware pervasive mobile services, evolvable network services, manageability and economic viability. The design is also informed by technology factors such as radio spectrum scarcity, wired bandwidth abundance, continuing Moore’s law improvements to computing, and energy constraints in mobile and sensor devices.
The UNL team (led by Byrav Ramamurthy) will study the impact of the rising number of mobile users on the Internet core, which consists of a fiber-optic network. In addition, UNL researchers will contribute to the overall design and evaluation of the MobilityFirst Future Internet architecture.
In this project, we propose to enhance the capability of the DoE’s ESnet by providing dynamic, optimized, advance scheduling of bandwidth demands required by large-scale science applications.
In the area of peer-to-peer computing, we are investigating efficient techniques for supporting large-scale multimedia streaming over such networks. Such applications will enable large-scale deployments of high-bandwidth optical and wireless access networks, making ubiquitous broadband a reality.
The Great Plains Environment for Network Innovation – GpENI is a regional network between The University of Kansas (KU), Kansas State University (KSU), University of Nebraska – Lincoln (UNL), and University of Missouri – Kansas City within the Great Plains Network, supported with optical switches from Ciena interconnected by Qwest fiber infrastructure, in collaboration with the Kansas Research and Education Network (KanREN) and Missouri Research and Education Network. GpENI is undergoing significant expansion to Europe and Asia using various tunneling protocols. GpENI is funded in part by the National Science Foundation GENI (Global Environment for Network Innovations) Program, as well as by the participating institutions that are contributing substantial resources. To run a demo on the GpENI network.
In this project, we will develop techniques to improve the data transfer speeds for multimedia data over NASA’s space networks. The project involves collaboration between researchers at UNL CSE department and NASA Jet Propulsion Laboratory (JPL).
While failure detection can happen quickly at the optical layer, the recovery (restoration) is slow and hard at the IP layer. Moreover, a single failure event at lower layer cascades into multiple failure events at the IP layer. Developing efficient cross-layer mechanisms for IP layer restoration after network failures is the focus of this work.
This project aims to develop a real-time groundwater-level monitoring network in Nebraska to provide fast and reliable data that will support agricultural decision-makers and other groundwater users to better plan for, recognize, deal with, and document multiple-year droughts.
A framework for remote telemetry using smart sensors and wireless telecommunication technology is being designed and implemented to collect and analyze groundwater hydrologic information from over 50 sites around Nebraska. Observation wells will be primarily chosen for their ability to detect the onset, magnitude and recovery of hydrological drought.
The architecture of the proposed framework consists of three main components: data acquisition unit, data transfer unit and data processing unit.
Data acquisition unit consists of a traditional water monitoring transducer and an embedded system. The embedded system does preliminary signal processing and packs the hydrologic data collected by the transducer into a proper and secure format ready for remote transmission. Data transfer unit consists of a satellite transceiver module or an cellular communication module, both of which will guarantees the reliable telecommunication with minimum expense. Both data acquisition unit and data transfer unit are powered by a solar panel and battery. All the hydrologic data will be collected hourly and transmitted daily to a central base station. Adjustments in the frequency of measurements and reporting can be made if a site is experiencing significant changes in water level or if future research investigations require more frequent measurements. A data processing unit, with a friendly Graphical interface, is located at the base station to analysis and archive the real-time data.
Information produced through this network could be utilized to address the effects of multiple-year drought in Nebraska and increase the economic and production stability of agricultural producers. The network also can be easily adapted to other fields of environmental monitoring.