Principal Investigators

Dr. James L. Flanagan (PI): Vice President of Research at Rutgers University, Director of the Center for Advanced Information Processing (CAIP) at Rutgers University, and Board of Governors Professor of Electrical and Computer Engineering, Rutgers University.
Dr. David J. Goodman: Director of the Wireless Information Network Laboratory (WINLAB) at Rutgers University, and Professor of Electrical and Computer Engineering, Rutgers University.
Dr. Sven J. Dickinson: Assistant Professor of Computer Science, Rutgers University.
Dr. Casimir A. Kulikowski: Director of the Laboratory for Computer Science Research at Rutgers University, and Board of Governors Professor of Computer Science, Rutgers University.
Dr. Narayan B. Mandayam: Assistant Professor of Electrical and Computer Engineering, Rutgers University.
Dr. Ivan Marsic: Assistant Professor of Electrical and Computer Engineering, Rutgers University.
Dr. Peter Meer: Associate Professor of Electrical and Computer Engineering, Rutgers University.
Dr. Attila Medl: Assistant Research Professor, Center for Advanced Information Processing (CAIP), Rutgers University.
Dr. Manish Parashar: Assistant Professor of Electrical and Computer Engineering, Rutgers University.
Dr. Marilyn Mantei Tremaine: Professor of Information Science and Technology, Drexel University.
Dr. Tremaine is also Chair of ACM SIGCHI.
Dr. Sorin Dusan, Assistant Research Professor, Center for Advanced Information Processing (CAIP), Rutgers University.

Project Summary

Objective

Research is proposed to establish an integrated framework for networked multimodal collaboration across wired and wireless environments. The system is designed to sense the existing computing environment (including asymmetries in resources) and adapt to provide a prescribed quality-of -service. Information transformations are invoked where needed. Evolving methods for multimodal human/machine communication, implemented at client stations, enhance naturalness, ease-of-use, and functionality. Researchers from cognitive science, sociology, psychology and human-factors partner with computing and communications specialists to establish a design methodology for ubiquitous human-centered multimodal collaboration.

Motivation

Collaboration is a hallmark of human activity. Globalization of society and burgeoning network connectivity highlight the need for new understanding in computer-mediated consensus-based decision making. A design framework which supports rapid development of collaborative applications-across wired and wireless environments-also serves universal access, increased human interaction on the Web, knowledge sharing, and assistance to disabled individuals.

Method

Seamless collaboration across heterogeneous computing environments requires integration of application software, adaptive network architectures for wired and wireless users, multimodal human/machine interfaces, signal-processing and information-transforming suites, human-factors metrology, and realistic evaluation scenarios. This expertise is drawn together in a research team to demonstrate ubiquitous collaboration applied to Telemedicine, Crisis Management and Mobile Offices. The plan of work includes: design of a Collaboration Bus architecture to support wired and wireless clients; continuous modeling of the wireless channel to adapt to changing characteristics; automatic information abstraction to maintain collaborative parity for disadvantaged users; exploitation of multimodal human/machine communication to expand functionality and to provide alternative communication for disabled users; and, creation of a four-client (two wired, two wireless) test bed system for evaluative experiments.

Milestones

Year 1: Implement a preliminary multimodal testbed network with wireless access; establish design requirements for mobile wireless collaboration using human-factors principles; develop application scenarios for evaluation.
Year 2: Create quality-of-service metrics and software control of resources; implement Telemedicine and Crisis Management scenarios; measure human/system performance; iterate strategies for information transformers and quality-of-service control.
Year 3: Implement and complete evaluation measurements for Mobile Office; demonstrate real-time system with four clients (two wired, two wireless); prepare Final Report with documented/commented software and engineering notes.

Research Tasks

Task 1: Collaboration Bus and Object State Coordination

Task Leaders: Ivan Marsic and Manish Parashar
Hiding the Complexities of Groupware Development
A Collaboration Bus is proposed as an enabling virtual "channel" that spans network fabrics and integrates heterogeneous clients. It encapsulates protocols and mechanisms for object interaction, object-state coordination, and concurrency control, and implements a novel event management and replication paradigm based on semantically enhanced events. The bus provides a component-based environment for composing multi-user collaborative applications from individual application modules that may or may not be collaboration aware.
Related project: Distributed System for Collaborative Information Processing and Learning (DISCIPLE)
Semantic Event Management (SEM) for Object-State Coordination
Related project: Semantic Interactions for Distributed Information Coordination for Heterogeneous Collaboration

Task 2: Wireless Links in Multimodal Collaborative Systems

Task Leaders: David Goodman and Narayan Mandayam
Managing Wireless Link Limitations
The research establishes mathematical and simulation models for transmission protocols and control of wireless links in the context of multimodal collaboration. The wireless channel is limiting in that scarce radio bandwidth and lossy radio transmission present significant design and control constraints. Results gained from the models define link-specific protocols that provide the required quality-of-service for multimodal collaboration. The research is divided in the following subtasks:

Feasibility of QoS Guarantees
Error Recovery Model with QoS Guarantees
Interaction of Error Recovery Models at Different Hierarchical Levels

Task 3: Information Reduction and Abstraction

Task Leaders: Peter Meer and Sven Dickinson
Providing Intelligent Information Reduction and Abstraction
Transformation methods will be established for compressing information from different modalities, primarily audio and visual, and even abstracting it to symbolic form, decreasing communication loads, and adapting to the user display requirements.
Related projects:
Robust Image Understanding Laboratory (RIUL)
The Vision, Interaction, Language, Logic and Graphics Environment (THE VILLAGE)

Task 4: Intelligent Agents for Heterogeneity Management

Task Leaders: Casimir Kulikowski, Manish Parashar, Attila Med,l and Sorin Dusan
The primary task of the intelligent agents at each client is to ensure that the client remains an effective collaborator. To achieve this, agents continually monitor the client's state, interests and capabilities, and make decisions on the type and degree of transformation or abstraction that needs to be applied to incoming information to ensure required QoS. A client's interests define the types of information on which it currently wants to collaborate. Its capabilities include available software and hardware resources, and nature of the interconnect. These capabilities essentially define the type of information on which the client can effectively collaborate. Monitoring capabilities is particularly critical in the case of wireless clients, where they are limited and varying.
Related project: Semantic Interactions for Distributed Information Coordination for Heterogeneous Collaboration
Multimodal Human/Machine Interaction
Providing Natural Communication between User and System Multimodal human/machine communication-based upon the natural dimensions of sight, sound and touch-will supplant the traditional limitations of mouse and keyboard. For stationary office environments, techniques will be transferred from the proposers' ongoing NSF-STIMULATE sponsored research. For mobile environments, new human/machine modes and information transformations will be designed and implemented.
Related project: Synergistic Multimodal Communication in Collaborative Multiuser Environments

Task 5: Human-Centered Design and System Evaluation

Task Leader: Marilyn Mantei Tremaine
Designing for Mobile Collaboration Needs
Humans use the context of their environment and spatial and gestalt cues provided by their work product to efficiently and effortlessly ground and manage their joint collaboration. Remote heterogeneous collaboration impairs these natural cues. Thus, human factors experimentation will quantify and optimize the multimodal interface designs and the collaboration-aware tools used in the collaboration. The research is divided in the following subtasks:

Data Collection on Mobile Collaboration Practices
Iterative Evaluation of Collaborative Applications
Experiments to Optimize Mismatched Collaboration Environments

Contact

For further information send email to: nsf-kdi@caip.rutgers.edu