David L. Westbrook

An end-user-responsive sensor network architecture for hazardous weather detection, prediction and response

We present an architecture for a class of systems that perform distributed, collaborative, adaptive sensing (DCAS) of the atmosphere. Since the goal of these DCAS systems is to sense the atmosphere when and where the user needs are greatest, end-users naturally play the central role in determining how system resources (sensor targeting, computation, communication) are deployed. We describe the meteorological command and control components that lie at the heart of our testbed DCAS system, and provide timing measurements of component execution times. We then present a utility-based framework that determines how multiple end-user preferences are combined with policy considerations into utility functions that are used to allocate system resources in a manner that dynamically optimizes overall system performance. We also discuss open challenges in the networking and control of such end-user-driven systems.

A global name service for a highly mobile internetwork

Mobile devices dominate the Internet today, however the Internet rooted in its tethered origins continues to provide poor infrastructure support for mobility. Our position is that in order to address this problem, a key challenge that must be addressed is the design of a massively scalable global name service that rapidly resolves identities to network locations under high mobility. Our primary contribution is the design, implementation, and evaluation of auspice, a next-generation global name service that addresses this challenge. A key insight underlying auspice is a demand-aware replica {placement engine} that intelligently replicates name records to provide low lookup latency, low update cost, and high availability. We have implemented a prototype of auspice and compared it against several commercial managed DNS providers as well as state-of-the-art research alternatives, and shown that auspice significantly outperforms both. We demonstrate proof-of-concept that auspice can serve as a complete end-to-end mobility solution as well as enable novel context-based communication primitives that generalize name- or address-based communication in todays Internet.

Closed-loop architecture for distributed collaborative adaptive sensing of the atmosphere: meteorological command and control

Distributed Collaborative Adaptive Sensing (DCAS) of the atmosphere is a new paradigm for detecting and predicting hazardous weather using a dense network of short-range, low-powered radars to sense the lowest few kilometres of the earths atmosphere. DCAS systems are collaborative in that the beams from multiple radars are actively coordinated in a sense-and-respond manner to achieve greater sensitivity, precision and resolution than possible with a single radar. DCAS systems are adaptive in that the radars and their associated computing and communications infrastructure are dynamically reconfigured in response to changing weather conditions and end-user needs. This paper describes an end-to-end DCAS architecture and evaluates the performance of the system in an operational testbed with actual weather events and end-user considerations driving the system. Our results demonstrate how the architecture is capable of real-time data processing, optimisation of radar control and sensing of the atmosphere in a manner that maximises end-user utility.

Hierarchical agent control: a framework for defining agent behavior

The Hierarchical Agent Control Architecture (HAC) is a general toolkit for specifying an agents behavior. HAC supports action abstraction, resource management, sensor integration, and is well suited to controlling large numbers of agents in dynamic environments. It relies on three hierarchies: action, sensor, and context. The action hierarchy controls the agents behavior. It is organized around tasks to be accomplished, not the agents themselves. This facilitates the integration of multi-agent actions and planning into the architecture. The sensor hierarchy provides a principled means for structuring the complexity of reading and transforming sensor information. Each level of the hierarchy integrates the data coming in from the environment into conceptual chunks appropriate for use by actions at this level. Actions and sensors are written using the same formalism. The context hierarchy is a hierarchy of goals. In addition to their primary goals, most actions are operating within a set of implicit assumptions. These assumptions are made explicit through the context hierarchy. We have developed a planner, GRASP, implemented within HAC, which is capable of resolving multiple goals in real time. HAC was intended to have wide applicability. It has been used to control agents in commercial computer games and physical robots. Our primary application domain is a simulator of land-based military engagements called “Capture the Flag.” HACs simulation substrate models physics at an abstract level. HAC supports any domain in which behaviors can be reduced to a small set of primitive effectors such as {\sc move} and {\sc apply-force}. At this time defining agent behavior requires Lisp programming skills; we are moving towards more graphical programming languages.

Design requirements of a global name service for a mobility-centric, trustworthy internetwork

The Internets tremendous success as well as our maturing realization of its architectural shortcomings have attracted significant research attention towards clean-slate re-designs in recent times. A number of these shortcomings can be traced back to naming. The current Internet uses IP addresses to conflate identity and network location, which results in poor support for mobility and multihoming; vulnerability to hijacking and spoofing of addresses, etc. The Internets name resolution infrastructure deeply embeds in its design the assumption of mostly stationary hosts and poorly satisfies the performance, security, and functionality demanded by modern mobile services. As a step towards addressing these shortcomings, we present the design of a global name service that forms a central component of the MobilityFirst, a clean-slate Internet architecture with mobility and trustworthiness as principal design goals. MobilityFirst relies on the global name service to cleanly separate identity from network location and to resolve identifiers to locations in a secure manner. More importantly, MobilityFirst capitalizes on the role of the name resolution infrastructure as a logically central, first point of contact to significantly enhance a number of network-layer functions such as supporting host and network mobility, multi-homed traffic engineering, content retrieval, multicast, and next-generation context-aware services. This paper identifies key challenges that must be addressed to realize such a vision and outlines the design of a distributed global name service that can resolve identifiers to dynamic attributes in a fast, consistent, and cost-effective manner at Internet scales.

Distributed Collaborative Adaptive Sensor networks for remote sensing applications

Enabled by a dense network of Doppler weather radars with overlapping coverage, Distributed Collaborative Adaptive Sensing (DCAS) represents a new paradigm in remote sensing. Rather than each radar periodically sampling its surroundings with sit-and-spin volume coverage patterns as with todays NEXRAD weather radars, DCAS is an end-user driven approach that targets sensitivity when and where the needs of its end-users are greatest. The advantage is that by adaptively allocating sensitivity, higher quality measurements are possible due to the ability to dwell longer in volumes where echoes are weak, sample faster in volumes with rapidly evolving dynamics, and obtain multi-Doppler looks for high accuracy wind field retrieval. This paper describes the multiuser, multi-attribute utilities-based approach being used to coordinate the scanning activities of the weather radars in the first prototype DCAS system being fielded by the National Science Foundation sponsored Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA- ERC).

User Evaluations of Adaptive Scanning Patterns in the CASA Spring Experiment 2007

The Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is creating a new paradigm for weather observation based on low cost, densely spaced networks of X-band radars. These networks adapt their scanning strategy based on the evolving weather and user needs for data. This paper presents the results of an evaluation by National Weather Service forecasters and academic researchers of the dynamically reconfigurable radar scanning patterns that operated in CASAs prototype test bed in southwest Oklahoma in spring 2007. The evaluation demonstrates that a pilot group of users were satisfied overall with CASAs scanning patterns. The evaluation also uncovered needed improvements to the scanning strategy that have been subsequently implemented. Through this iterative cycle of design, implementation, evaluation, we have demonstrated the flexibility of the system architecture and our ability to modify existing and add new capabilities to increase the benefits of CASA radar systems.

A TOOLBOX FOR ANALYZING PROGRAMS

As program behavior becomes complex, it’s increasingly important to analyze their behavior statistically. The article describes two separate but synergistic tools for statistically analyzing large Lisp programs. The first tool, called CLIP (Common Lisp Instrumentation Package), allows the researcher to define and run experiments, including experimental conditions (parameter values of the planner or simulator) and data to be collected. The data are written out to data files that can be analyzed by statistics software. The second tool, called CLASP (Common Lisp Analytical Statistics Package), allows the researcher to analyze data from experiments by using graphics, statistical tests, and various kinds of data manipulation. CLASP has a graphical user interface (using CLIM, the Common Lisp Interface Manager) and also allows data to be directly processed by Lisp functions. Finally, the paper describes a number of other data-analysis modules that have been added to work with CLIP and CLASP.

Dense radar networks for low-flyer surveillance

The present inability to detect low-flying aircraft over international borders renders governments and citizens vulnerable to problems such as drug trafficking and illegal immigration. This paper describes an approach to comprehensive low-altitude surveillance based on networks of small radars being developed by the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere. We examine how low-cost networked radar technology might be applied to the public safety/security problem of detecting weather hazards while simultaneously supporting the border security mission of detecting and intercepting low-flying aircraft.

Meteorological Command & Control: Architecture and Performance Evaluation

IP1 is a prototype CASA radar sensor network located in southwestern Oklahoma whose goal is to detect severe weather in the lower part of the atmosphere. At the center of this systems control loop is its Meteorological Command and Control (MC&C). In this paper, we presented the overall control architecture for the IP1 network and highlight new features that have recently been added to the MC&C. We also present an analysis of the MC&C performance based on measurement data from a 5-day operation period. In addition, we introduce a distributed version of the MC&C.