A cognitive policy management framework for DoD

Sherman, Matthew; Comba, Andrew; He, Donya; McDonald, Howard

doi:10.1109/milcom.2010.5679562

Cited by 11 publications

(2 citation statements)

References 5 publications

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“…To that end, policy based management is discussed in [6], [7] and especially for cognitive networks in [8]. The terminology as well as exact roles and implementations of policy engine varies, but generally there is a need for "reasoning architecture" which sets the goals for the reasoning intelligence.…”

Section: Related Workmentioning

confidence: 99%

Network management issues in military Cognitive Radio Networks

Bräysy

Tuukkanen

Couturier

et al. 2017

2017 International Conference on Military Communications and Information Systems (ICMCIS)

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Abstract-Cognitive Radio (CR) was designed to support flexible spectrum usage by adding spectrum sensing facilities and decision making logic to the radio devices. Cognitive Radio Network (CRN) is an extension of the CR concept to enable holistic end-to-end optimization of the network operation and services. We discuss CRN management issues in the context of military and tactical operation environments, where the key feature is the temporal nature of the network installations. Our special interest is in the wireless ad hoc network solutions. The network lifetime may extend from just hours to several days. The limited lifetime of the networks makes it both possible and necessary to define the management functionalities with respect to different mission phases. Traditional FCAPS (Fault, Configuration, Administration, Performance, and Security) functions and their required actions are therefore detailed to some level at each operational phase (before, during and after mission). We will emerge the idea that, as the cognitive and autonomous technologies will be developed to operate communication networks and become trustworthy enough to be applied also in tactical context, they will most likely first be applied in the during mission phase. Of course, this phase is also the most critical in the sense that it is here that lives are at stake. To answer this critical issue, the policy management must be seen as an equally critical functionality. It is necessary to develop the interconnection between mission goals and defined policies so that the Cognitive Network Engine (CNE) determining the operational parameters of the network, in all situations provides a reliable and failsafe communication solution to be utilized. 1

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Section: Related Workmentioning

confidence: 99%

Network management issues in military Cognitive Radio Networks

Bräysy

Tuukkanen

Couturier

et al. 2017

2017 International Conference on Military Communications and Information Systems (ICMCIS)

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“…The main goal of the policy engine is to prevent the transmission of unauthorized waveforms while being liberal to allow multiple types of waveforms operate on the system [20]. In general, the policy engine exploits a database of regulatory policies which determines the accepted outputs for the radio, such as allowed transmission frequency and power [35].…”

Section: Optimization Modulementioning

confidence: 99%

Algorithms for Opportunistic Load Balancing Cognitive Engine

Mäkeläinen¹,

Khan²,

Hänninen³

et al. 2014

Proceedings of the 9th International Conference on Cognitive Radio Oriented Wireless Networks

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Due to the increasing use of more and more powerful smart devices demands on the scarce radio spectrum are becoming more intense. One way to cope with increasing demands on radio spectrum is to apply innovative and flexible authorization schemes like spectrum sharing. Under the spectrum sharing paradigm, multiple users and/or systems are authorized to utilize the same spectrum band in a defined sharing agreement. A technology that is generally recommended for the implementation of spectrum sharing is called cognitive radio (CR).In this thesis, we design and implement a cognitive engine (CE) that intelligently and dynamically allocates spectrum resources to users. We first consider a scenario where a network has an exclusive access to a spectrum band and the CE accepts or rejects the arrival user requests based on an algorithm that takes into account a user's priority and its bandwidth demand. We then consider a spectrum sharing scenario where along with the exclusive utilization to its own spectrum band a network also can opportunistically utilize another network's spectrum band. For this scenario, we design and implement a CE that performs two main tasks: 1) Accepts or rejects arrival user requests based on a priority based algorithm; and 2) it intelligently load balances the user traffic between the two available network resources, while taking into account the primary user activity in the shared spectrum band. We provide a load balancing algorithm and evaluate its performance under different primary and secondary user traffic scenarios. We show that the proposed load balancing algorithm increases average throughput of the network and it also reduces the average number of users rejected by the network. Keywords: cognitive radio, simulator, medium access, radio resource management Mäkeläinen M. (2013) Opportunistiset kuormituksentasausalgoritmit kognitiivisessa koneessa. Oulun yliopisto, tietotekniikan osasto. Diplomityö, 64 s. TIIVISTELMÄYhä tehokkaampien älykkäiden langattomien päätelaitteiden nopea lisääntymi-nen johtaa niukan radiospektrin yhä kiihtyvään käyttöön. Eräs menetelmä radiospektrin lisääntyvän kysynnän tyydyttämiseen on hyödyntää innovatiivista ja joustavaa resurssin käytönjakoa kuten spektrin jakamista. Spektrinjakamismalli mahdollistaa useiden käyttäjien ja/tai järjestelmien yhtäaikaisen käytön samalla taajuuskaistalla hyödyntämällä sovittua käytäntöä resurssien jakamisesta. Radiospektrin jakaminen on tänä päivänä yleisesti suositeltu toteuttamaan hyödyn-tämällä kognitiivista radioteknologiaa.Tässä työssä suunnittellaan ja toteutetaan kognitiivinen päätöksentekokone, joka jakaa radiospektriresursseja käyttäjille älykkäästi ja dynaamisesti. Kognitiivista päätöksentekokonetta radioresurssien jakamisessa hyödynnetään kahdessa skenaariossa. Ensimmäisessä skenaariossa radioverkolla on yksinomainen pää-sy taajuuskaistalle, jonka käyttöä kognitiivinen päätöksentekokone säätelee joko hyväksymällä tai hylkäämällä verkkoon liittyviä käyttäjiä. Kognitiivinen päätök-sentekokoneen päätökset perustuu...

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