Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. AFRL-IF-RS-TP-2006-8 SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)Air ABSTRACTTo effectively enhance service availability, this paper proposes a redundancy configuration for a database unit residing in a command and control (C2) system that supports air operations. The results of modeling, supervisory control, and performance analysis of the database unit are presented. The unit is modeled as a closed Markovian queuing network. State variable feedback is used to implement the functions of restoration and routing upon the identification of the failure of one of the database servers in the unit. Several control policies are evaluated in terms of the resulting mean time to unit failure, the steady state availability, the expected response time, and the service overhead of the database unit. Abstract -To effectively enhance service availability, this paper proposes a redundancy configuration for a database unit residing in a command and control (C2) system that supports air operations. The results of modeling, supervisory control, and performance analysis of the database unit are presented. The unit is modeled as a closed Markovian queuing network. State variable feedback is used to implement the functions of restoration and routing upon the identification of the failure of one of the database servers in the unit. Several control policies are evaluated in terms of the resulting mean time to unit failure, the steady state availability, the expected response time, and the service overhead of the database unit.
Airborne sensor platforms are becoming increasingly significant for both civilian and military operations; yet, at present, their sensors are typically idle for much of their flight time, e.g., while the sensor-equipped platform is in transit to and from the locations of sensing tasks. The sensing needs of many other potential information consumers might thus be served by sharing such sensors, thereby allowing other information consumers to opportunistically task them during their otherwise unscheduled time, as well as enabling other improvements, such as decreasing the number of platforms needed to achieve a goal and increasing the resilience of sensor tasks through duplication. We have implemented a prototype system realizing these goals in Mission-Driven Tasking of Information Producers (MTIP), which leverages an agent-based representation of tasks and sensors to enable fast, effective, and adaptive opportunistic sharing of airborne sensors. Using a simulated large-scale disaster-response scenario populated with publicly available Geographic Information System (GIS) datasets, we demonstrate that correlations in task location are likely to lead to a high degree of potential for sensor-sharing. We then validate that our implementation of MTIP can successfully carry out such sharing, showing that it increases the number of sensor tasks served, reduces the number of platforms required to serve a given set of sensor tasks, and adapts well to radical changes in flight path.
Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. AFRL-IF-RS-TP-2006-7 SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)Air Force Research Laboratory/IFSB 525 Brooks Rd Rome NY 13441-4505 SPONSORING/MONITORING AGENCY REPORT NUMBER AFRL-IF-RS-TP-2006-7 DISTRIBUTION AVAILABILITY STATEMENT Approved for public release: distribution is unlimited. PA# 06-32413. SUPPLEMENTARY NOTES Paper presented at the 8th International Workshop on Discrete Event Systems, July 10-12, 2006, in Ann Arbor, MI. This material is declared a work of the U. S. Government and is not subject to copyright protection in the United States. ABSTRACTThis paper extends the performance analysis of a controlled database unit studied in Wu, Metzler, and Linderman (2005) to include the cases where errors and delays can occur in state-based control actions as a result of uncertainty in the knowledge of the system state. The paper details the way such errors and delays are captured through augmenting the state space in the Markov model of the database unit. State variable feedback is used to activate the process of restoration upon the failure of one of the database servers in the unit. The performance of the database is evaluated in terms of the resulting mean time to unit failure, the steady state availability, the expected response time, and the service overhead of the database unit. All performance measures are examined with respect to the likelihood of decision error and the amount of control action delay. SUBJECT TERMSdiscrete event systems, supervisory control, Markov model, queuing network SECURITY
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