SCAN-Fault: Scalable Autonomic Fault Detection and Root-Cause Analysis in a Heterogeneous Network

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$80,000.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
N66001-13-P-5116
Award Id:
n/a
Agency Tracking Number:
N123-162-0153
Solicitation Year:
2012
Solicitation Topic Code:
N123-162
Solicitation Number:
2012.3
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
Y
Duns:
161911532
Principal Investigator:
RenatoLevy
Chief Scientist
(301) 294-5241
rlevy@i-a-i.com
Business Contact:
MarkJames
Director, Contracts and P
(301) 294-5221
mjames@i-a-i.com
Research Institute:
Stub




Abstract
To support reliable and secure communications, a suitable network analysis tool is needed for accurately and efficiently detecting, diagnosing, and predicting faults in the network. In tactical networks, faults can be very common, and are typically hard and time consuming to detect, isolate and fix. Moreover, in a heterogeneous network, a small network problem along any part of an end-to-end path can potentially degrade the user experience significantly. But identifying and resolving this problem may require knowledge and action across different domains and planes. Furthermore, fault analysis schemes designed for the traditional networks are not fully suitable to wireless networks such as mobile ad hoc networks and cognitive radio networks. To address these issues, Intelligent Automation, Inc. (IAI) proposes to develop a SCalable AutoNomic Fault detection and root-cause analysis (SCAN-Fault) scheme that can analyze the monitored network as a whole and assist the users (i.e., network operators) in maintaining, optimizing, and securing the managed network. The proposed approach will significantly improve the reliable and secure access to battlefield network, and reduce the cost and risks for network management.

* information listed above is at the time of submission.

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