Next Article in Journal
1/f Noise Modelling and Characterization for CMOS Quanta Image Sensors
Previous Article in Journal
Exploiting Opportunistic Scheduling Schemes and WPT-Based Multi-Hop Transmissions to Improve Physical Layer Security in Wireless Sensor Networks
Previous Article in Special Issue
Design and Implementation of a Trust Information Management Platform for Social Internet of Things Environments
Open AccessArticle

Efficient Execution of Complex Context Queries to Enable Near Real-Time Smart IoT Applications

School of Information Technology, Deakin University, Geelong 3216, Australia
Faculty of Information Technology, Monash University, Melbourne 3145, Australia
Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Author to whom correspondence should be addressed.
Sensors 2019, 19(24), 5457;
Received: 1 November 2019 / Revised: 3 December 2019 / Accepted: 6 December 2019 / Published: 11 December 2019
(This article belongs to the Special Issue Real-Time AI over IoT Data)
As the Internet of Things (IoT) is evolving at a fast pace, the need for contextual intelligence has become more crucial for delivering IoT intelligence, efficiency, effectiveness, performance, and sustainability. Contextual intelligence enables interactions between IoT devices such as sensors/actuators, smartphones and connected vehicles, to name but a few. Context management platforms (CMP) are emerging as a promising solution to deliver contextual intelligence for IoT. However, the development of a generic solution that allows IoT devices and services to publish, consume, monitor, and share context is still in its infancy. In this paper, we propose, validate and explain the details of a novel mechanism called Context Query Engine (CQE), which is an integral part of a pioneering CMP called Context-as-a-Service (CoaaS). CQE is responsible for efficient execution of context queries in near real-time. We present the architecture of CQE and illuminate its workflows. We also conduct extensive experimental performance and scalability evaluation of the proposed CQE. Results of experimental evaluation convincingly demonstrate that CoaaS outperforms its competitors in executing complex context queries. Moreover, the advanced functionality of the embedded query language makes CoaaS a decent candidate for real-life deployments. View Full-Text
Keywords: complex; context; query; execution; IoT; CMP complex; context; query; execution; IoT; CMP
Show Figures

Figure 1

MDPI and ACS Style

Hassani, A.; Medvedev, A.; Zaslavsky, A.; Delir Haghighi, P.; Jayaraman, P.P.; Ling, S. Efficient Execution of Complex Context Queries to Enable Near Real-Time Smart IoT Applications. Sensors 2019, 19, 5457.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop