ConQeng:  A Middleware for Quality of Context Aware Selection, Measurement and Validation

Kanaka Sai Jagarlamudi; Arkady Zaslavsky; Seng W. Loke; Alireza Hassani; Alexey Medvedev

doi:10.1007/978-3-031-20936-9_17

ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation

Kanaka Sai Jagarlamudi, Arkady Zaslavsky, Seng W. Loke, Alireza Hassani, Alexey Medvedev

Deakin University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

1 Citation (Scopus)

Abstract

A set of quality metrics (e.g., timeliness, completeness) together represent the Quality of Context (QoC); their values determine the usability of context to context consumers (IoT applications). Therefore, obtaining adequate ‘QoC from the context providers (context sources) represents a significant research challenge. This paper presents a framework called conQeng that addresses such a challenge through novel approaches in QoC-aware selection, QoC measurement and validation. ConQeng selects the potential context providers that deliver an adequate QoC during runtime, assesses their performance - for further selection, and transfers QoC-assured context to the context management platforms (CMPs). We have implemented conQeng in a simulated scenario involving autonomous cars, marketing service agencies as context consumers, and thermal and video cameras as context providers. The results demonstrate that it outperforms three heuristic approaches in reducing context acquisition cost and improving effectiveness and performance efficiency while obtaining adequate QoC.

Original language	English
Title of host publication	Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers
Editors	Aurora González-Vidal, Ahmed Mohamed Abdelgawad, Essaid Sabir, Sébastien Ziegler, Latif Ladid
Place of Publication	Switzerland
Publisher	Springer Nature Switzerland AG
Pages	211-225
Number of pages	15
Volume	13533
ISBN (Print)	9783031209352
DOIs	https://doi.org/10.1007/978-3-031-20936-9_17
Publication status	Published - Jan 2023
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13533 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Context management platforms
QoC measurement
QoC-aware selection
Selection framework

Access to Document

10.1007/978-3-031-20936-9_17

Cite this

Jagarlamudi, K. S., Zaslavsky, A., Loke, S. W., Hassani, A., & Medvedev, A. (2023). ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation. In A. González-Vidal, A. Mohamed Abdelgawad, E. Sabir, S. Ziegler, & L. Ladid (Eds.), Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers (Vol. 13533, pp. 211-225). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13533 LNCS). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-20936-9_17

Jagarlamudi, Kanaka Sai ; Zaslavsky, Arkady ; Loke, Seng W. et al. / ConQeng : A Middleware for Quality of Context Aware Selection, Measurement and Validation. Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers. editor / Aurora González-Vidal ; Ahmed Mohamed Abdelgawad ; Essaid Sabir ; Sébastien Ziegler ; Latif Ladid. Vol. 13533 Switzerland : Springer Nature Switzerland AG, 2023. pp. 211-225 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "A set of quality metrics (e.g., timeliness, completeness) together represent the Quality of Context (QoC); their values determine the usability of context to context consumers (IoT applications). Therefore, obtaining adequate {\textquoteleft}QoC from the context providers (context sources) represents a significant research challenge. This paper presents a framework called conQeng that addresses such a challenge through novel approaches in QoC-aware selection, QoC measurement and validation. ConQeng selects the potential context providers that deliver an adequate QoC during runtime, assesses their performance - for further selection, and transfers QoC-assured context to the context management platforms (CMPs). We have implemented conQeng in a simulated scenario involving autonomous cars, marketing service agencies as context consumers, and thermal and video cameras as context providers. The results demonstrate that it outperforms three heuristic approaches in reducing context acquisition cost and improving effectiveness and performance efficiency while obtaining adequate QoC.",

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Jagarlamudi, KS, Zaslavsky, A, Loke, SW, Hassani, A & Medvedev, A 2023, ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation. in A González-Vidal, A Mohamed Abdelgawad, E Sabir, S Ziegler & L Ladid (eds), Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers. vol. 13533, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13533 LNCS, Springer Nature Switzerland AG, Switzerland , pp. 211-225. https://doi.org/10.1007/978-3-031-20936-9_17

ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation. / Jagarlamudi, Kanaka Sai; Zaslavsky, Arkady; Loke, Seng W. et al.
Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers. ed. / Aurora González-Vidal; Ahmed Mohamed Abdelgawad; Essaid Sabir; Sébastien Ziegler; Latif Ladid. Vol. 13533 Switzerland : Springer Nature Switzerland AG, 2023. p. 211-225 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13533 LNCS).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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AB - A set of quality metrics (e.g., timeliness, completeness) together represent the Quality of Context (QoC); their values determine the usability of context to context consumers (IoT applications). Therefore, obtaining adequate ‘QoC from the context providers (context sources) represents a significant research challenge. This paper presents a framework called conQeng that addresses such a challenge through novel approaches in QoC-aware selection, QoC measurement and validation. ConQeng selects the potential context providers that deliver an adequate QoC during runtime, assesses their performance - for further selection, and transfers QoC-assured context to the context management platforms (CMPs). We have implemented conQeng in a simulated scenario involving autonomous cars, marketing service agencies as context consumers, and thermal and video cameras as context providers. The results demonstrate that it outperforms three heuristic approaches in reducing context acquisition cost and improving effectiveness and performance efficiency while obtaining adequate QoC.

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Jagarlamudi KS, Zaslavsky A, Loke SW, Hassani A, Medvedev A. ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation. In González-Vidal A, Mohamed Abdelgawad A, Sabir E, Ziegler S, Ladid L, editors, Internet of Things - 5th The Global IoT Summit, GIoTS 2022, Revised Selected Papers. Vol. 13533. Switzerland : Springer Nature Switzerland AG. 2023. p. 211-225. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-20936-9_17