A time-sensitive IoT data analysis framework

Harindu Korala; Dimitrios  Georgakopoulos; Ali  Yavari; Prem Prakash  Jayaraman

A time-sensitive IoT data analysis framework

Harindu Korala
, Dimitrios Georgakopoulos
, Ali Yavari
, Prem Prakash Jayaraman

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

Abstract

This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a time-sensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft's Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework's ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96%.

Original language	English
Title of host publication	Proceedings of the 54th Annual Hawaii International Conference on System Sciences
Editors	Tung X. Bui
Place of Publication	Hawaii USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	7185-7194
Number of pages	10
Edition	1st
ISBN (Print)	9780998133140
Publication status	Published - 2021
Externally published	Yes
Event	Hawaii International Conference on System Sciences 2021 - Online, Virtual, Online, United States of America Duration: 4 Jan 2021 → 8 Jan 2021 Conference number: 54th https://scholarspace.manoa.hawaii.edu/handle/10125/72112 (Proceedings/Website)

Publication series

Name	Proceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)	1530-1605

Conference

Conference	Hawaii International Conference on System Sciences 2021
Abbreviated title	HICSS 2021
Country/Territory	United States of America
City	Virtual, Online
Period	4/01/21 → 8/01/21
Internet address	https://scholarspace.manoa.hawaii.edu/handle/10125/72112 (Proceedings/Website)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Internet of Things (IoT)
Time-Sensitive IoT Applications
Distributed Systems

Access to Document

http://hdl.handle.net/10125/71486

Cite this

Korala, H., Georgakopoulos, D., Yavari, A., & Jayaraman, P. P. (2021). A time-sensitive IoT data analysis framework. In T. X. Bui (Ed.), Proceedings of the 54th Annual Hawaii International Conference on System Sciences (1st ed., pp. 7185-7194). (Proceedings of the Annual Hawaii International Conference on System Sciences). IEEE, Institute of Electrical and Electronics Engineers. http://hdl.handle.net/10125/71486

Korala, Harindu ; Georgakopoulos, Dimitrios ; Yavari, Ali et al. / A time-sensitive IoT data analysis framework. Proceedings of the 54th Annual Hawaii International Conference on System Sciences. editor / Tung X. Bui. 1st. ed. Hawaii USA : IEEE, Institute of Electrical and Electronics Engineers, 2021. pp. 7185-7194 (Proceedings of the Annual Hawaii International Conference on System Sciences).

@inproceedings{f96b30a74b7242efbc3ed119a54e5eb7,

title = "A time-sensitive IoT data analysis framework",

abstract = "This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a time-sensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft's Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework's ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96\%.",

keywords = "Internet of Things (IoT), Time-Sensitive IoT Applications, Distributed Systems",

author = "Harindu Korala and Dimitrios Georgakopoulos and Ali Yavari and Jayaraman, \{Prem Prakash\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE Computer Society. All rights reserved.; Hawaii International Conference on System Sciences 2021, HICSS 2021 ; Conference date: 04-01-2021 Through 08-01-2021",

year = "2021",

language = "English",

isbn = "9780998133140",

series = "Proceedings of the Annual Hawaii International Conference on System Sciences",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "7185--7194",

editor = "Bui, \{Tung X.\}",

booktitle = "Proceedings of the 54th Annual Hawaii International Conference on System Sciences",

address = "United States of America",

edition = "1st",

url = "https://scholarspace.manoa.hawaii.edu/handle/10125/72112",

}

Korala, H, Georgakopoulos, D, Yavari, A & Jayaraman, PP 2021, A time-sensitive IoT data analysis framework. in TX Bui (ed.), Proceedings of the 54th Annual Hawaii International Conference on System Sciences. 1st edn, Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE, Institute of Electrical and Electronics Engineers, Hawaii USA, pp. 7185-7194, Hawaii International Conference on System Sciences 2021, Virtual, Online, Hawaii, United States of America, 4/01/21. <http://hdl.handle.net/10125/71486>

A time-sensitive IoT data analysis framework. / Korala, Harindu; Georgakopoulos, Dimitrios ; Yavari, Ali et al.
Proceedings of the 54th Annual Hawaii International Conference on System Sciences. ed. / Tung X. Bui. 1st. ed. Hawaii USA: IEEE, Institute of Electrical and Electronics Engineers, 2021. p. 7185-7194 (Proceedings of the Annual Hawaii International Conference on System Sciences).

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

TY - GEN

T1 - A time-sensitive IoT data analysis framework

AU - Korala, Harindu

AU - Georgakopoulos, Dimitrios

AU - Yavari, Ali

AU - Jayaraman, Prem Prakash

N1 - Conference code: 54th

PY - 2021

Y1 - 2021

N2 - This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a time-sensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft's Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework's ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96%.

AB - This paper proposes a Time-Sensitive IoT Data Analysis (TIDA) framework that meets the time-bound requirements of time-sensitive IoT applications. The proposed framework includes a novel task sizing and dynamic distribution technique that performs the following: 1) measures the computing and network resources required by the data analysis tasks of a time-sensitive IoT application when executed on available IoT devices, edge computers and cloud, and 2) distributes the data analysis tasks in a way that it meets the time-bound requirement of the IoT application. The TIDA framework includes a TIDA platform that implements the above techniques using Microsoft's Orleans framework. The paper also presents an experimental evaluation that validates the TIDA framework's ability to meet the time-bound requirements of IoT applications in the smart cities domain. Evaluation results show that TIDA outperforms traditional cloud-based IoT data processing approaches in meeting IoT application time-bounds and reduces the total IoT data analysis execution time by 46.96%.

KW - Internet of Things (IoT)

KW - Time-Sensitive IoT Applications

KW - Distributed Systems

UR - https://www.scopus.com/pages/publications/85108366723

M3 - Conference Paper

AN - SCOPUS:85108366723

SN - 9780998133140

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 7185

EP - 7194

BT - Proceedings of the 54th Annual Hawaii International Conference on System Sciences

A2 - Bui, Tung X.

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Hawaii USA

T2 - Hawaii International Conference on System Sciences 2021

Y2 - 4 January 2021 through 8 January 2021

ER -

Korala H, Georgakopoulos D, Yavari A, Jayaraman PP. A time-sensitive IoT data analysis framework. In Bui TX, editor, Proceedings of the 54th Annual Hawaii International Conference on System Sciences. 1st ed. Hawaii USA: IEEE, Institute of Electrical and Electronics Engineers. 2021. p. 7185-7194. (Proceedings of the Annual Hawaii International Conference on System Sciences).

A time-sensitive IoT data analysis framework

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Cite this