2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing Resource annotation, dissemination and discovery in the Semantic Web of Things: a CoAP-based framework M. Ruta, F. Scioscia, A. Pinto, E. Di Sciascio, F. Gramegna, S. Ieva, G. Loseto DEI - Politecnico di Bari via E. Orabona 4, I-70125, Bari, Italy (m.ruta, f.scioscia, agnese.pinto, disciascio)@poliba.it, (gramegna, ieva, loseto)@deemail.poliba.it Abstract—The Semantic Web of Things (SWoT) vision aims on context; severe computational constraints. In such dynamic to provide more advanced resource management and discov- environments, resource discovery is more challenging than ery w.r.t. standard Internet of Things architectures, by means static Web scenarios. of the integration of knowledge representation and reasoning techniques originally devised for the Semantic Web. This paper Among several alternatives proposed to define protocols proposes a novel SWoT framework, based on a backward- for object networks, 6LoWPAN [2] at network layer and the compatible extension of the Constrained Application Protocol Constrained Application Protocol (CoAP) [3] at application (CoAP), supporting non-standard inference services for semantic layer are emerging as widespread standards. Nevertheless, matchmaking. It allows retrieval and logic-based ranking of current solutions only allow a simplistic data-oriented rep- annotated resources. A computationally efficient data mining is also integrated in the framework to process raw data gathered resentation of resources and elementary retrieval procedures from the environment in order to detect high-level events and based on “string matching” between requests and resource characterize them with machine-understandable metadata. In attributes, which provide just binary yes/no outcomes. Exact order to test the effectiveness of the proposed approach, a case request/resource matches are very uncommon in real-world study about environmental risk prevention for Vehicular Ad-hoc scenarios with heterogeneous devices, sensors and actuators NETworks (VANETs) is presented. from several independent providers. Much like the case of Web Keywords—Semantic Web of Things, CoAP, Resource discovery, mashups [4], a large human effort is required on a case-by-case Matchmaking, Data mining basis for the design, deployment and integration of current IoT and Web of Things (WoT) applications. I. INTRODUCTION A more effective resource discovery should support also The Semantic Web of Things (SWoT) [1] is an emerging partial correspondences, possibly providing a measure of the vision, joining together the Semantic Web and the Internet of similarity degree between a request and available resources. Things paradigms. Every information resource in the Semantic Ideas and technologies adapted from the Semantic Web may be Web is annotated with metadata in RDF1 expressed w.r.t. useful to reach this goal. This paper proposes an overall frame- an RDF Schema2 or OWL3 ontology. Language specification work for the SWoT, managing semantic-based annotations of includes a standard XML serialization syntax. The adopted data streams, devices, high-level events and services with a knowledge representation models are grounded on formal, well-defined meaning w.r.t. a shared domain conceptualization 4 (i.e., ontology). The proposal introduces: (i) a slight backward- logic-based semantics. Query languages, e.g., SPARQL , are 5 6 defined to extract and combine asserted information, while compatible extensions to CoAP and CoRE Link Format reasoning engines can automatically infer knowledge entailed resource discovery protocol; (ii) computationally efficient data by a given Knowledge Base (KB). The goal of the SWoT is to mining procedures to detect and annotate high-level events associate semantically rich and machine-understandable infor- from raw data collected by a Semantic Sensor Network mation to real-world objects, locations and events, by means of (SSN) and the SSN-XG W3C ontology [5] is adopted as inexpensive, unobtrusive and often disposable micro-devices, reference vocabulary for resource annotations; (iii) a semantic- so enabling new classes of smart applications and services. based matchmaking via non-standard inference services [6] In order to allow this vision, frameworks and technologies to retrieve and rank resources best matching a given request, must deal with pervasive computing issues, that is resource, supporting not only full matches but also approximate ones. user and device volatility; platform heterogeneity; dependence In order to test and validate the proposed approach, a case study is also presented about environmental risk monitoring 1Resource Description Framework, W3C Recommendation, 10 February and management in Vehicular Ad-hoc NETworks (VANETs). 2004. http://www.w3.org/TR/rdf-primer/ 2RDF Vocabulary Description Language 1.0 (RDF Schema), W3C Recom- The remainder of the paper is organized as follows. Details mendation, 10 February 2004 http://www.w3.org/TR/rdf-schema/ 3OWL 2 Web Ontology Language Document Overview (Second Edition), 5We will refer to Constrained Application Protocol, IETF CoRE W3C Recommendation, 11 December 2012, http://www.w3.org/TR/owl2- Working Group Internet-Draft, version 13, 6 December 2012, overview/ http://tools.ietf.org/id/draft-ietf-core-coap-13.txt 4SPARQL Query Language for RDF, W3C Recommendation 15 January 6CoRE Link Format, IETF CoRE Working Group Internet-Draft, version 2008, http://www.w3.org/TR/rdf-sparql-query/ 14, 1 June 2012, http://www.ietf.org/id/draft-ietf-core-link-format-14.txt 978-0-7695-5046-6/13 $26.00 © 2013 IEEE 527 DOI 10.1109/GreenCom-iThings-CPSCom.2013.103 about functions and components of the framework architecture 6 V`J:C QG1CV are provided in Section II, followed by a case study in Section ]]C1H: 1QJ QC1VJ C%$1J III. Finally, Section IV discusses most relevant related research 1"1`Q QHQC and Section V closes the paper. ^$ 8GL]_ Q Q II. PROPOSED APPROACH Q: V1:7 Q In what follows the proposed CoAP enhancements, the semantic matchmaking framework (adopted for resource dis- Q1J@ QRV Q1J@ QRV covery) and the event mining approach will be thoroughly Q described. A. Semantic-enhanced CoAP and CoRE Link Format QRG:VRVJQ` V 1Q`@ Following the REST architectural style, CoAP adopts a loosely coupled client/server model, based on stateless op- Fig. 1. Framework Architecture erations on resources representation [3]. Each resource is a server-controlled abstraction, unambiguously identified by a In order to support a semantic-based resource discovery, URI (Uniform Resource Identifier). Clients access resources the CoAP protocol has been improved with a novel usage via synchronous request/response interactions, using HTTP- of standard URI-query options and with the addition of derived methods basically mapping the Read, Create, Update new ones. The CoAP-based SSN framework proposed here and Delete operations of data management. Basically, a CoAP extends the enhancements described in [7] enabling further message is composed of: (i) a 32-bit header, containing the non-standard inferences to support automated sensor discovery request method code (or response status); (ii) an optional token and composition, representing one of the main novelties of value, used to associate replies to requests, (iii) a sequence the approach. However the resulting framework is still fully of option fields (carrying information as resources URI and backward compatible: servers which do not support semantics payload media type), (iv) the payload data. The CoRE Link will simply reply to requests returning no resource records. Format specification is adopted for resource discovery. A Semantic-based requests are led back to standard CoAP ones client will access the reserved URI /.well-known/core by introducing three novel attributes: (i) reference ontology on the server via GET to retrieve available resources entry (ro), containing the URI of the domain conceptualization; (ii) points. Further GET requests will include URI-query fields semantic description (sd), i.e., the annotated request, com- to recall only resources with given attributes. Standardized pressed to cope with the verbosity of XML-based languages; query attributes include resource type (rt), interface usage (iii) annotation-type (at), specifying the compression format. (if), content-type (ct), and MIME (Multipurpose Internet The reference geographical location is achieved by specify- Mail Extension) type for a resource. Further non-reserved ing lg (longitude) and lt (latitude) attributes. Furthermore, attributes can be freely used. CoAP also provides push noti- md (maximum distance) is used to indicate the maximum fications without polling7, a useful feature when data have to acceptable distance (in meters) from the reference location be monitored over a time span. for retrieving resources. The adoption of a (center, distance) constraint allows the server to pre-filter resources, so avoiding In CoAP-based scenarios, each sensor is seen as a possibly expensive inference procedures for resources outside server, exposing both readings and internal information as the requested area. Finally, each provided reasoning task de- resources toward clients, which act on behalf of end-user voted to resource discovery is identified by a code, specified by applications. Different data series will be identified by dis- st (semantic task) attribute. In addition to existing tasks, a new tinct URIs. Further URIs will