Deakin University
Browse
zaslavsky-contextdefinition-2019.pdf (14.81 MB)

Context definition and query language: conceptual specification, implementation, and evaluation

Download (14.81 MB)
journal contribution
posted on 2019-01-01, 00:00 authored by Ali Hassani, Alexey Medvedev, Pari Delir Haghighi, Sea Ling, Arkady ZaslavskyArkady Zaslavsky, Prem Prakash Jayaraman
As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability. As the standardisation efforts for IoT are fast progressing, efforts in standardising context management platforms led by the European Telecommunications Standards Institute (ETSI) are gaining more attention from both academic and industrial research organizations. These standardisation endeavours will enable intelligent interactions between 'things', where things could be devices, software components, web-services, or sensing/actuating systems. Therefore, having a generic platform to describe and query context is crucial for the future of IoT applications. In this paper, we propose Context Definition and Query Language (CDQL), an advanced approach that enables things to exchange, reuse and share context between each other. CDQL consists of two main parts, namely: context definition model, which is designed to describe situations and high-level context; and Context Query Language (CQL), which is a powerful and flexible query language to express contextual information requirements without considering details of the underlying data structures. An important feature of the proposed query language is its ability to query entities in IoT environments based on their situation in a fully dynamic manner where users can define situations and context entities as part of the query. We exemplify the usage of CDQL on three different smart city use cases to highlight how CDQL can be utilised to deliver contextual information to IoT applications. Performance evaluation has demonstrated scalability and efficiency of CDQL in handling a fairly large number of concurrent context queries.

History

Journal

Sensors

Volume

19

Issue

6

Article number

1478

Pagination

1 - 43

Publisher

MDPI

Location

Basel, Switzerland

eISSN

1424-8220

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2019, the authors