Ramesh Rao - US grants

The principal investigators (PI) will develop and study new non- probabilistic models to analyze the behavior of control algorithms for resource allocation in packet switched data communications networks. Their approach to dealing with uncertainty differs from traditional approaches. Rather than specifying statistical properties of traffic they plan to employ and extend a non- probabilistic model for demand that specifies hard constraints satisfied by the traffic. The model facilitates the rigorous computation of bounds for parameters such as maximum delay, average delay, and buffering requirements in networks. They will focus on dynamic routing and flow control which involve the study of coupled queues. The use of models such as the nonprobabilistic model is likely to overcome the analytical problems traditionally encountered. They provide examples of problems that address these issues in networks using point to point and interacting broadcast links. As the size and demand for data networks grow, the economic impact of developing useful tools for engineering them will be quite significant. This approach develops some of these tools. ***//

Traditionally, in order to address the many complex issues that arise in communication networks, a ``layered" approach has been taken. The different layers are typically assigned different ``responsibilities," so that the general network design problem can be decomposed into simpler, more manageable problems. However, the independent design of the different layers - which ignores the detailed nature of their mutual interactions, shared constraints, and cumulative impact on the network's overall performance - can lead to inefficiencies. Future wireless communication networks will be required to provide wide coverage and high capacity to mobile users generating bursty multi-media information. This heterogeneous traffic will impose upon the network time-varying quality of service (QoS) constraints. Since many multi-media applications have delay-sensitive information with varying reliability requirements, such as numerical data, voice, and video, the project will take end-to-end delay and data integrity as its dominant system constraints. The goal of this project is, in the broadest sense, to take a more global view of end-to-end performance, to better understand the interactions among the layers, to develop techniques that improve system performance through joint optimization over the various layers and to do so in the context of a end-to-end delay constraint. One key theme of the proposal involves the optimization of system performance in the context of multiple users, particularly in a system which does not employ a cellular-type architecture. This requires the development of techniques that, on the one hand, address the deleterious effects of multiple-user interference at the physical layer, yet also incorporate end-to-end QoS objectives, especially delay, just as with the development of routing and scheduling algorithms. Another major theme will be the determination of the optimal distribution and the real-time dynamics of error control functions implemented across t he layers of the network, subject to specified end-user requirements. This requires investigation of inherent tradeoffs between error-rate and decoding delay of FEC employed at the physical layer, as well as the interactions among error control functions, including retransmission strategies, invoked at higher levels.

Third generation personal communication systems are likely to involve many bursty, mobile, multi-media users whose quality of service needs may vary dynamically over time. In order for a wireless system to respond adequately to these demands it will be necessary to determine fundamental mechanisms for allocating QoS needs in the radio environment. Unlike fiber optic links, radio links are likely to be expensive and of poorer quality. Thus, a large part of the quality of service arbitration will have to be supported via coding and other link enhancements techniques. In this proposal, we first present findings that reveal the importance of higher order error statistics in assessing the impact of particular forms of error control on higher layer services. Then we note that when communications are conducted over a layered stack, a particular error control module exerts influence on the overall end to end performance not only via its own error correcting capabilities but also via the type of error events that it passes up to the higher layers. Therefore, we propose to investigate error management mechanisms that not only correct errors but also shape and possibly exploit the statistics of the residual errors that escape to the higher layers. Finally, given a set of end user performance requirements, one can conceive of multiple ways of distributing the error control functions. So, we propose to investigate how to distribute the error control functions. We expect that the proposed work will help in the design of a new generation of network radios.

Ramesh Rao
University of California San Diego

"The New Role of Science and Engineering in Risk Reduction"


In February 2002, NSF funded a successful workshop in New York City, inspired by the events of September 11, to develop a research agenda related to unexpected events. Now, one year later and with the Department of Homeland Security established, the topic of homeland security is much better defined as it relates to the Federal Government and NSF. NSF is now engaged in developing a large cross-agency initiative in Cyber-Infrastructure. The workshop being funded by this grant is intended to bring the two areas of cyber-infrastructure and homeland security into juxtaposition, with the goal of developing a computer/information science research agenda within the context of homeland security, as related to cyber-infrastructure.

The long-term goals of this project are to radically transform the ability of organizations that respond to man-made and natural disasters to gather, process, manage, use and disseminate information both within the emergency response agencies and to the general public. The project explores a multidisciplinary approach consisting of two interrelated research thrusts:
Scalable and robust information technology solutions to facilitate access to the right information, by the right individuals and organizations, at the right time, and
Social science research that investigates the distinctive nature of dynamic virtual organizations, and the social and cultural aspects of information sharing across organizations and individuals.

Research challenges addressed include mechanisms to: enable crisis responders to become rich sources of vital situational information; seamlessly collect data from heterogeneous sources; translate low-level noisy data into meaningful information that can be effectively used for damage assessment and situation awareness; facilitate information sharing and collective decision-making across emergent virtual organizations; and rapidly disseminate information in the form most useful to recipients. Close collaborations with multiple government agencies have been developed to test and validate research in live environments.

The project is expected to result in robust information systems that enable first responders to make well-informed and better decisions, to prioritize their response, and to focus on activities that have the highest potential to save lives and property. The resulting timely and effective response can contain or prevent secondary disasters, and reduce the resulting economic losses and social disruption during disasters.

The project will create new shared data sets for text, video and data mining. This will allow a larger scientific community to test algorithmic innovations against these field gathered data sets. Our community outreach programs will help generate greater awareness of the role of IT, stimulating new innovations as first responders interact more closely with researchers. Our educational programs will generate a better trained crisis management work force.

Broader Impact: Timely and effective response to natural or man-made disasters can reduce deaths and injuries, contain or prevent secondary disasters, and reduce the resulting economic losses and social disruption. During a crisis, responding organizations confront grave uncertainties in making critical decisions. There is a strong correlation between the quality of these decisions and the accuracy, timeliness, and reliability of the situational information (e.g., state of the civil, transportation and information infrastructures) and the availability of resources (e.g., medical facilities, rescue and law enforcement units) to the decision-makers. Recently, at UCI and UCSD many projects have been launched that address the technological challenges in with the objective of radically transforming the ability of organizations to gather, manage, use and disseminate information when responding to man-made and natural catastrophes. Dramatic improvements in the speed and accuracy at which information about the crisis flows through the disaster response networks has the potential to revolutionize crisis response saving human lives and property. . The purpose of this infrastructure proposal is to establish an campus-level experimental Information Technology infrastructure, called Responsphere, to serve as a platform for development, testing, and validation of our current research efforts on responding to a crisis.
Intellectual Merit: Challenges in bringing accurate, timely, and relevant information to decision-makers during crisis response arises due to the scale and complexity of the problem, the diversity of data and data sources, the state of the communication and information infrastructures through which the information flows, and the unique character and dynamic nature of the responding organizations. To address these challenges, our research team is exploring a multidisciplinary approach focusing on the following research elements in the context of crisis response: (1) Enabling humans (rescue workers, observers) to become rich sources of vital crisis-related information; (2) Seamlessly collecting data from heterogeneous sources in highly dynamic disaster situations where the IT infrastructure may have partially failed; (3) Translating low-level noisy data into meaningful events useful for damage assessment and situation awareness; (4) Enabling information sharing and collective decision-making across highly dynamic emergent virtual organizations; (5) Rapidly disseminating information in the form most useful to recipients while observing the fundamental limitations of the underlying communication and information technologies. Validation platforms and testbeds will be deployed in close partnership with first responders from the City and County of LA, San Diego and Irvine Police departments as well as the California Office of Emergency Services in live environments and will help us evaluate the effectiveness of the research.

The testbeds created as a part of Responsphere will provide the team with an experimental platform to field-test and refine research on information collection, analysis, sharing, and dissemination in controlled yet realistic settings significantly enhancing their research capability. Specific testbeds include:
Mobile Incidence Level Response (MILLR) Testbed
Crisis Assessment, Mitigation, and Analysis (CAMAS) Testbed
Advanced Traffic Rerouting for Unplanned Events (TRUE) Testbed
At UC Irvine we will (1) expand the campus 802.11b based wireless infrastructure to cover major outdoor regions, (2) add instrumentation and management tools to the campus wireless environment, (3) add compute, visualization and storage capabilities for crisis management and response research, and (4) expand the available pool of mobile devices and embellish them with specialized video capture and streaming capabilities suitable for field response experiments. At UC San Diego we will (1) establish RF propagation modeling capabilities using GIS and 3D data generation and transformation tools, (2) build a wireless communications infrastructure in the Gas Lamp Quarter downtown, (3) build a command and control prototyping environment in a visualization facility, (4) create a vehicular based mobile command and control platform, (5) design a location/tracking system and prototype it along with other sensing and communications equipment in a custom man worn implementation ("manpack"), and (6) participate in the upgrade of the UCSD Police communication environment.. Specific research components tested in Responsphere are (1) a system for accurate position location in uncertain environments; (2) an integrated end-to-end quality aware distributed data collection system; (3) an end-to-end data analysis system; and (4) system for seamless multimodal interaction involving audio/video and image information. Other research efforts at UCI and UCSD in the areas of mobile computing, networking, middleware, security and ubiquitous computing will benefit from the Responsphere infrastructure

SGER: CogNet (Cognitive Complete Knowledge Network) System

Award 0650048

Ramesh Rao


The Cognitive Complete Knowledge Network (CogNet) system combines advances in storage, network connectivity, and device capability, with advances in analytical approaches to make next generation wireless systems refine their performance throughout the lifetime of their
deployment. The CogNet architecture exploits the availability of low cost "some time some where" communications to asynchronously and automatically gather large amounts of user data by enlisting users, devices, and even the whole network as probes. The information gathered
is derived from the radio state, network state, environment state, and user profiles, and is spatio-temporally tagged and archived in a distributed repository and made available to the community of participants. A user in a particular spatio-temporal region could learn
about typical usage, others' experiences, network conditions, and protocol parameters by querying this repository and tune or adapt itself to achieve the desired quality of service.

We use stochastic analysis, algorithm development, performance analysis and optimization, and prototype deployment to identify globally relevant internal state data from the vast amounts generated within any mobile device; manage data transfer and archiving; design learning models and algorithms to fit the large and diverse collected dataset; develop cross-layer, cross-system adaptations to use information obtained from the collective experience; and analyze and learn the network traffic and network parameters to identify appropriate service compositioning parameters to guarantee user experience.

In July 2014, the National Telecommunication Information Administration (NTIA) and the Federal Communications Commission's (FCC) Office of Engineering and Technology (OET) issued a Joint Public Notice (PN) to seek public comment on the creation of an urban test city to support rapid experimentation and development of policies, underlying technologies, and system capabilities for advanced, dynamic spectrum sharing by wireless devices. Based on the responses received from this comments process, the FCC and NTIA are seeking inputs to support the development of a framework for the model test city. The framework for the Model City would include consideration of several aspects including, technical, collaborative, funding and governance aspects. The FCC is sponsoring a workshop on April 15-16, 2015, to facilitate this process. The workshop aims to bring together a group of 100 experts in the field from a variety of sectors and backgrounds, including from government, industry and academia, at the local, state, national and even international levels. This project will support the travel of 20 attendees from academia and 10 from the public safety sector who would otherwise be unable to attend. Travel support will be used to promote participation of attendees who can contribute to the sharing of ideas between academia and industry and federal agencies.

It is expected that this workshop will develop a strategic plan for new approaches that will allow commercial interests to share currently underutilized bandwidth without jeopardizing functionality and safety in emergency situations. The workshop will also contribute valuable insights to the growing acceptance that wireless spectrum is becoming an integral part of so-called "Critical Infrastructure" and therefore requiring of Critical Infrastructure Protection.

This award is a planning grant for the Spectrum Innovation Initiative: National Center for Wireless Spectrum Research (SII-Center). The focus of a spectrum research SII-Center goes beyond 5G, IoT, and other existing or forthcoming systems and technologies to chart out a trajectory to ensure United States leadership in future wireless technologies, systems, and applications in science and engineering through the efficient use and sharing of the radio spectrum. The need for wireless systems is exponentially growing, and future implications need to be explored. Emerging issues, opportunities and challenges for use of highly valuable spectrum and the definition of important and potential breakthrough research agendas and new technologies need to be defined to meet new challenges and achieve a safe, secure, and reliable mobile networked world.

Led by the University of California, San Diego, the assembled team includes team members from the University of Oklahoma, Stanford University, the University of Wisconsin, New York University, Hughes Research Laboratory, the Jet Propulsion Laboratory, Keysight Technologies, Qualcomm, MIT, Lincoln Laboratory, Shared Spectrum Company, Verizon, and Google. Key areas the team will explore include science users, air traffic management, communications, radars, wide area radio frequency sensing including low-Earth orbit (LEO) constellations, radio layer innovations with particular emphases on machine learning and networking around small cells, implementation aspects of 6G and THz band systems, and policy.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This project investigates methods to mitigate radio-frequency interference. The research team will implement new approaches, which are needed because traditional electromagnetic (radio-frequency) spectrum monitoring approaches are losing effectiveness. The continuing growth of wireless communications requires the limited available spectrum to be used ever more efficiently. To pack wireless systems more tightly, transmitters and receivers are evolving to use directional antennas that can steer away from interference. Directional transmissions mean a sensor at a single location can no longer rely on detecting all nearby transmissions, and when the sensor does observe an incoming signal, it cannot easily predict what other devices or locations are impacted. SweepSpace seeks to overcome these limitations and provide new spatial and directional information that enables safely increasing communications and sensing capacity without increasing spectrum cost. This project evaluates the new methods and the SweepSpace prototype through analysis, laboratory tests and limited field experiments. The project will provide training for the next-generation workforce for wireless communications and spectrum science by engaging graduate, undergraduate, and high-school students, including students from underrepresented groups. SweepSpace sensor kits, based on a low-cost software defined radio, will be created for use in workshops, demonstrations, and classrooms. <br/><br/>SweepSpace is a generalized spectrum sensing architecture designed to report all spatio-temporal activity in a spatial-frequency volume. Complete knowledge of transmissions requires the deployment of a dense network of sensors; it requires each sensor to detect all incoming signals across a wide range of frequencies; and it requires each sensor to identify the direction of all incoming signals. Rapid sweeping across 3D space over a wide band enables a low-cost sensor with a single moderate-bandwidth receiver to frequently sample every channel in a wide range and to frequently sample all incident directions via a sweeping phased array antenna. The team will investigate the use of off-the-shelf components to develop a prototype low-cost SweepSpace node. They will investigate 1) reconstruction of a full spatio-temporal activity map from samples that are sparse across space, time, frequency, and incident direction; 2) enhancing the directional precision of individual sensors; 3) optimizing the placement and parameterization of the; and 4) identifying spatio-temporal holes for safe insertion of new activity. They will also investigate single-sensor questions, such as minimum detectability bounds, risk of missed detections and false positives, and optimal scheduling policies, and they will characterize the probability of missed detections by a network of sensors. The project includes development of risk mitigation tools that can be used by others to tailor SweepSpace for their use cases.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.