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Cloud computing in tactical environments

Summary

Ground personnel at the tactical edge often lack data and analytics that would increase their effectiveness. To address this problem, this work investigates methods to deploy cloud computing capabilities in tactical environments. Our approach is to identify representative applications and to design a system that spans the software/hardware stack to support such applications while optimizing the use of scarce resources. This paper presents our high-level design and the results of initial experiments that indicate the validity of our approach.
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Summary

Ground personnel at the tactical edge often lack data and analytics that would increase their effectiveness. To address this problem, this work investigates methods to deploy cloud computing capabilities in tactical environments. Our approach is to identify representative applications and to design a system that spans the software/hardware stack to...

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Competing cognitive resilient networks

Published in:
IEEE Trans. Cognit. Commun. and Netw., Vol. 2, No. 1, March 2016, pp. 95-109.

Summary

We introduce competing cognitive resilient network (CCRN) of mobile radios challenged to optimize data throughput and networking efficiency under dynamic spectrum access and adversarial threats (e.g., jamming). Unlike the conventional approaches, CCRN features both communicator and jamming nodes in a friendly coalition to take joint actions against hostile networking entities. In particular, this paper showcases hypothetical blue force and red force CCRNs and their competition for open spectrum resources. We present state-agnostic and stateful solution approaches based on the decision theoretic framework. The state-agnostic approach builds on multiarmed bandit to develop an optimal strategy that enables the exploratory-exploitative actions from sequential sampling of channel rewards. The stateful approach makes an explicit model of states and actions from an underlying Markov decision process and uses multiagent Q-learning to compute optimal node actions. We provide a theoretical framework for CCRN and propose new algorithms for both approaches. Simulation results indicate that the proposed algorithms outperform some of the most important algorithms known to date.
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Summary

We introduce competing cognitive resilient network (CCRN) of mobile radios challenged to optimize data throughput and networking efficiency under dynamic spectrum access and adversarial threats (e.g., jamming). Unlike the conventional approaches, CCRN features both communicator and jamming nodes in a friendly coalition to take joint actions against hostile networking entities...

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Fast online learning of antijamming and jamming strategies

Published in:
2015 IEEE Global Communications Conf., 6-10 December 2015.

Summary

Competing Cognitive Radio Network (CCRN) coalesces communicator (comm) nodes and jammers to achieve maximal networking efficiency in the presence of adversarial threats. We have previously developed two contrasting approaches for CCRN based on multi-armed bandit (MAB) and Qlearning. Despite their differences, both approaches have shown to achieve optimal throughput performance. This paper addresses a harder class of problems where channel rewards are time-varying such that learning based on stochastic assumptions cannot guarantee the optimal performance. This new problem is important because an intelligent adversary will likely introduce dynamic changepoints, which can make our previous approaches ineffective. We propose a new, faster learning algorithm using online convex programming that is computationally simpler and stateless. According to our empirical results, the new algorithm can almost instantly find an optimal strategy that achieves the best steady-state channel rewards.
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Summary

Competing Cognitive Radio Network (CCRN) coalesces communicator (comm) nodes and jammers to achieve maximal networking efficiency in the presence of adversarial threats. We have previously developed two contrasting approaches for CCRN based on multi-armed bandit (MAB) and Qlearning. Despite their differences, both approaches have shown to achieve optimal throughput performance...

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Development and use of a comprehensive humanitarian assessment tool in post-earthquake Haiti

Summary

This paper describes a comprehensive humanitarian assessment tool designed and used following the January 2010 Haiti earthquake. The tool was developed under Joint Task Force -- Haiti coordination using indicators of humanitarian needs to support decision making by the United States Government, agencies of the United Nations, and various non-governmental organizations. A set of questions and data collection methodology were developed by a collaborative process involving a broad segment of the Haiti humanitarian relief community and used to conduct surveys in internally displaced person settlements and surrounding communities for a four-month period starting on 15 March 2010. Key considerations in the development of the assessment tool and data collection methodology, representative analysis results, and observations from the operational use of the tool for decision making are reported. The paper concludes with lessons learned and recommendations for design and use of similar tools in the future.
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Summary

This paper describes a comprehensive humanitarian assessment tool designed and used following the January 2010 Haiti earthquake. The tool was developed under Joint Task Force -- Haiti coordination using indicators of humanitarian needs to support decision making by the United States Government, agencies of the United Nations, and various non-governmental...

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