Efficient Execution of Complex Context Queries to Enable Near Real-Time Smart IoT Applications
| Autor: | Prem Prakash Jayaraman, Alexey Medvedev, Pari Delir Haghighi, Arkady Zaslavsky, Alireza Hassani, Sea Ling |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
IoT
query execution Computer science Distributed computing Context (language use) 02 engineering and technology Query language 01 natural sciences Biochemistry Article Analytical Chemistry context 0202 electrical engineering electronic engineering information engineering CMP Electrical and Electronic Engineering Instrumentation business.industry 010401 analytical chemistry Context management 020206 networking & telecommunications Competitor analysis Atomic and Molecular Physics and Optics 0104 chemical sciences Workflow Scalability Internet of Things business complex |
| Zdroj: | Sensors Volume 19 Issue 24 Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s19245457 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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