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A New Computing Paradigm for Energy-Efficient Collaboration in Underwater Sensor Networks

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-04-M-0031
Agency Tracking Number: N032-0535
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N03-224
Solicitation Number: 2003.2
Timeline
Solicitation Year: 2003
Award Year: 2004
Award Start Date (Proposal Award Date): 2003-12-02
Award End Date (Contract End Date): 2004-10-01
Small Business Information
7519 Standish Place, Suite 200
Rockville, MD 20855
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Xiaodong Zhang
 Research Scientist
 (301) 294-5269
 xzhang@i-a-i.com
Business Contact
 Marc Toplin
Title: Director of Contracts
Phone: (301) 294-5215
Email: mtoplin@i-a-i.com
Research Institution
N/A
Abstract

In this proposal, Intelligent Automation, Inc. (IAI) and its subtractor, Prof. Hairong Qi of the University of Tennessee at Knoxville, propose a novel mobile-agent-based computing paradigm for collaborative information exchange among distributed sensor nodes. Unlike the traditional client/server-based method, the proposed mobile-agent-based approach transfers the partially integrated results and executable code from one node to another and the processing can be done locally on the sensor nodes. The proposed approach consists of two levels: (1) mobile-agent-based computing for collaborative processing among multiple sensor nodes and (2) data processing and fusion at the local nodes. The proposed mobile-agent-based computing model provides a nice balance between energy efficiency and fault tolerance. It presents a framework for efficient usage of energy and bandwidth, scalable computing, reliable and fault-tolerant decision making, as well as supports intermediate results with progressive accuracy. The collaborative data processing and fusion algorithms use the information from multiple sensors. We develop both simulators to study the performance between the mobile-agent-based collaborative processing and the client/server-based centralized processing based on compression algorithms providing a compression ratio.

* Information listed above is at the time of submission. *

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