A Decentralized Locality-Preserving Context-Aware Service Discovery Framework for Internet of Things

Abstract

Today's Internet is shifting towards a larger and smarter scenario known as the Internet of Things (IoTs). The IoT envisions a multitude of heterogeneous objects and interactions with physical environments. In this environment, locating desirable services is challenging due to the considerable diversity, large number, dynamic behavior, and geographical distribution of the services provided by physical objects. In this paper, we propose a context-aware semanticsbased service discovery mechanism -LOCA that can effectively locate services based on the context requirements. The proposed discovery framework is built on a fully distributed peer-to-peer (P2P) architecture which is scalable and robust. Moreover, a key feature of the discovery mechanism is its support of content and path locality. This feature can enhance the integrity of an organization and thus greatly improve the security of the organization. The effectiveness of the proposed framework is demonstrated through comprehensive simulation studies.

Ontology‐based service discovery framework for dynamic environments

“…If no taxonomic relationship exists between the concepts, then these concepts are considered disjoint; in this case, the method ConceptSimilarityScore() will return a score 0. Otherwise, the score will be calculated by using equations (2) and (5). For example, the score of both attributes (activity description and location description) of service O3 in Table 4 is 0 because both concepts are declared disjoint in the application ontology (Fig.…”

“…Although the above‐discussed context‐aware ontology‐based semantic matching approaches address many limitations of the traditional service matching approaches, there are still certain issues that must be addressed for effective service discovery, matching and ranking, respectively. It is particularly necessary for any approach in the DERTS environment to consider role, resources, schedules, value type direction, as well as timeliness and user priorities during the service matching and ranking process (these are some of the requirements which were common, identified during the review of literature [5–28] and proposed by the experts). In addition, if no exact service matches, corresponding to user's defined criteria, are found the approach should return the approximate results to the user [14].…”

“…In addition, we seek to estimate the degree of usefulness in effective discovery ranking and selection of DERTS services. In‐order to establish evaluation criteria to measure the effectiveness, we consulted our domain experts along with a review of number of papers [5–28]. For criteria selection, we used a term weighted technique (each time a criteria requirement repeated we increased the score of that requirement by one).…”

“…Particularly, context-awareness can be used as an additional set of criteria in a selection process. However, due to highly interrelated nature of the context, it is difficult to represent it uniquely, as well as reuse and interpret it perfectly [5]. Moreover, to use context information effectively, it should be presented in an unambiguous way and the dynamic nature of embedded and real-time systems should be considered.…”

A semantic-based discovery service for the Internet of Things

“…There are several well-known drawbacks that make this approach unsuitable for IoT in a real-world scenario, e.g., low scalability and dependability. To overcome these limitations, other approaches have relied on distributed repositories to support the discovery process [7][8][9][10][11].…”