The Dynamic Spectrum Access Policy Framework in Action∗† Henrique Santos1 , Alice Mulvehill1,3 , John S. Erickson1,2 , James P. McCusker1 , Minor Gordon1 , Owen Xie1 , Samuel Stouffer1 , Gerard Capraro4 , Alex Pidwerbetsky5 , John Burgess5 , Allan Berlinsky5 , Kurt Turck6 , Jonathan Ashdown6 , and Deborah L. McGuinness1,2 1 Tetherless World Constellation, Rensselaer Polytechnic Institute, Troy NY, USA 2 The Rensselaer Institute for Data Exploration and Applications, Troy NY, USA 3 Memory Based Research LLC, Pittsburgh PA, USA 4 Capraro Technologies Inc., Utica NY, USA 5 LGS Labs, CACI International Inc., Florham Park NJ, USA 6 Air Force Research Laboratory, Rome NY, USA Abstract. Because radio spectrum is a finite resource, its usage and sharing is regulated by government agencies through policies that man- age spectrum allocation. With more portions of the spectrum being li- censed for commercial use, the importance of providing an increased level of automation when evaluating such policies becomes crucial for the efficiency and efficacy of spectrum management. This poster show- cases the Dynamic Spectrum Access Policy Framework, which acts as a machine-readable policy repository providing policy management fea- tures and spectrum access request evaluation. It includes the use of the framework’s policy management capabilities to create and modify poli- cies in a novel policy representation using two recommended web stan- dards (OWL and PROV-O), and the request evaluation engine to verify the assignment of permit/deny effects to spectrum requests. 1 Introduction Usable radio spectrum is becoming crowded7 as an increasing number of ser- vices, both commercial and governmental, rely on wireless communications to operate. Techniques known as Dynamic Spectrum Access (DSA) [7] have been extensively researched as a way of promoting more efficient methods for shar- ing the radio spectrum among distinct organizations, and their respective de- vices, while adhering to regulations. Government agencies, such as the National Telecommunications and Information Administration8 (NTIA), publish author- ∗ Copyright c 2020 for this paper by its authors. Use permitted under Creative Com- mons License Attribution 4.0 International (CC BY 4.0). † Approved for public release (reference number: 88ABW-2020-1535). 7 http://bit.ly/FCC_AWS 8 http://ntia.doc.gov itative documents9 that contain spectrum policies to regulate the usage of the spectrum. This poster presents the Dynamic Spectrum Access Policy Framework (DSA Policy Framework) for supporting the management of machine-readable, radio spectrum usage policies. This is accomplished via the utilization of a novel pol- icy representation, based on two World Wide Web Consortium recommendations for encoding ontologies and provenance on the web (OWL and PROV-O), that encodes its rules in an ontology. This ontology, combined with background knowl- edge from a number of relevant sources, is stored in a Knowledge Graph that is used by a domain-specific reasoning implementation that mixes a standard for representation and querying geospatial linked data (GeoSPARQL [4]), OWL reasoning, and knowledge graph traversal to evaluate policies that are applica- ble to spectrum access requests. This poster complements our submission to the In-use track [5] by showcasing the usability of the system with an in-depth view of the framework’s capabilities from the user perspective. 2 Dynamic Spectrum Access Policy Framework Rensselaer Polytechnic Institute collaborated with spectrum domain experts from Capraro Technologies Inc. and LGS Labs of CACI International Inc. to select and analyze English, text-based policies from the NTIA Redbook and from various Federal Communications Commission (FCC) documents. The En- glish text was converted into a different representation, and many of the terms used in the English text were incorporated into a DSA domain ontology. During this process, a number of requirements were elicited: – To store machine-readable spectrum policies in a modeling that supports common constructs – To allow users to interact with the machine-readable policies, creating, mod- ifying, and specializing them as needed – To provide a policy evaluation endpoint able to receive transmission requests in a common format and assign permit/deny effects, based on existing poli- cies, while explaining the reasons for the policies’ decisions The DSA Policy Framework serves as a centralized, machine-readable, radio spectrum policy repository, providing policy management features (including creation and customization) for a wide range of radio spectrum domain users. It uses the machine-readable policies as a basis for automatically evaluating radio spectrum access requests. Built on top of the Whyis Knowledge Graph Framework [3], the DSA Policy Framework provides two major functions: Policy Management and Request Eval- uation. Policy Management enables spectrum managers to explore and manage policies. The framework provides a web interface to allow spectrum managers to have a comprehensive understanding of the DSA Knowledge Graph, which is 9 http://bit.ly/NTIA_Redbook Fig. 1. Policy Builder: enables the visual creation of DSA policies in OWL composed of policies, named locations, and entities in the DSA domain ontology. The structure and content of the interface are driven by the DSA Knowledge Graph, which ensures that it displays relevant and contextualized information and features. The Policy Builder (Figure 1), a key component of the DSA Policy Frame- work, allows users to build policies from scratch or to create policies by reusing the rules of existing policies. The Policy Builder leverages the DSA Knowledge Graph to provide user support during policy creation. In the back end, the policy is converted to an OWL representation and stored as a new piece of knowledge in the DSA Knowledge Graph. Fig. 2. Visualizing a policy’s details The Policy Detail view (Figure 2) provides a display of policy metadata, including name, original text and identifier, and a human-readable version of the policy encoded rules. If the policy specifies locations, those locations will be displayed on a map. Request Evaluation utilizes policies to automatically process incoming spec- trum requests originating from devices that want to use a part of the spectrum. The request evaluation engine (Figure 3) follows a four-phase pipeline, with a set of requests as input and the assigned effect, a list of obligations, and a list of reasons for each request as output. First, the engine elicits the geographical relationships among the requests’ coordinates and named locations in the DSA KG using GeoSPARQL. Following this, the HermiT OWL reasoner [2] is used to classify the requests’ instances in the applicable policies’ classes. Next, pol- icy precedence is decided by comparing precedence levels of applicable policies. Lastly, the engine traverses the KG to find rules that were not satisfied in order to explain the assignment of the deny effect to requests. The results generated include ref- Request evaluation engine erences to any policy that was in- OWL reasoner Requests GeoSPARQL volved in the evaluation. As poli- Results Precedence explanation Evaluation evaluation (HermiT) cies evolve, the underlying knowl- edge representation evolves, enabling the request evaluation engine to use the most current policy information to reason and assign effects (permit, deny, permit with obligation) to spec- Fig. 3. Request evaluation pipeline trum requests. 3 The DSA Policy Framework in Use The DSA Policy Framework is being used in simulated scenarios, where it sup- ports the research & development of other components of a dynamic spectrum management system. It currently contains approximately 165 high-level policies from the NTIA Redbook (including their sub-policies). The DSA Ontology con- tains 695 classes and is constantly evolving to address new domain constructs and support more precise request evaluation. The framework is transitioning to support live, over-the-air field exercises that involve a diverse set of federal and commercial radios. During these ex- ercises, the Framework supports (1) the creation, deletion, and revision of lo- cal policies, (2) the real-time processing of numerous spectrum requests, and (3) the generation of explanations that describe how the spectrum requests were processed. The publicly released assets developed during the course of the project can be accessed at https://github.com/tetherless-world/ dsa-open/. 4 Conclusion While the policy aspect of dynamic spectrum access has been extensively re- searched over the past years, there is a shortage of working implementations in the literature to operationalize it in a real environment. Ulversøy [6] describes the potential that policy-based spectrum management offers to combine comprehen- sive administrative control with the benefit of fast, local decision making. This paper provides an overview of research about policy-based spectrum manage- ment. The second part of their paper outlines a proposed OWL-based ontology for spectrum management and provides a few examples. It concludes by stat- ing that the efficient evaluation of highly localized, fine-grained spectrum access policies is a “hard problem” requiring further research. The DSA Policy Framework relies on a novel policy representation approach that builds on previous work by matching the cross-domain policy expression se- mantics of XACML [1]. It extends these semantics with the capacity to express rich spatio-temporal restrictions, enabling the implementation of a wide vari- ety of attribute-based policies across domains. It leverages background knowl- edge from domain-specific knowledge graphs that are structured with a domain- derived ontology, enabling the inference of policy applicability based on at- tributes and constraints. It also uniquely conceptualizes policies as PROV activ- ities and provides a set of user interfaces to enable the exploration, visualization, creation, and modification of such policies. One of the outstanding benefits of this policy representation is the ability to provide detailed explanations for denied requests. By identifying unsatisfied rules, the framework allows domain policy developers to understand the precise reasons for policy decisions. Acknowledgement of Support and Disclaimer. This work is partially funded in support of National Spectrum Consortium (NSC) project number NSC-17- 7030. Any opinions, findings and conclusions or recommendations expressed in this material are those the authors and do not necessarily reflect the views of AFRL. References 1. eXtensible Access Control Markup Language (XACML) Version 3.0. http:// docs.oasis-open.org/xacml/3.0/xacml-3.0-core-spec-os-en.html 2. Glimm, B., Horrocks, I., Motik, B., Stoilos, G., Wang, Z.: HermiT: An OWL 2 Reasoner. Journal of Automated Reasoning 53(3), 245–269 (2014) 3. McCusker, J., Rashid, S.M., Agu, N., Bennett, K.P., McGuinness, D.L.: The Whyis Knowledge Graph Framework in Action. In: International Semantic Web Conference (P&D/Industry/BlueSky) (2018) 4. 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