Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems

Daniel Zhang; Dong Wang

doi:10.1109/INFCOMW.2019.8845042

Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems

Daniel Zhang, Dong Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Social sensing based Edge Computing systems (SSEC) have emerged as a new application paradigm in leveraging privately owned edge/IoT devices to collectively provide ubiquitous sensing, computation, and services. In this demo, we compare and contrast various task allocation strategies in SSEC in supporting delay sensitive social sensing applications. We evaluate the system on two real-time social sensing applications and demonstrate the energy savings as well as the Quality of Service (QoS) of the SSEC system. The demonstrated framework highlights the deficiency in traditional pure top-down and bottom-up task allocation solutions and validates a new hybrid task allocation strategy that is more scalable and efficient.

Original language	English (US)
Title of host publication	INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	977-978
Number of pages	2
ISBN (Electronic)	9781728118789
DOIs	https://doi.org/10.1109/INFCOMW.2019.8845042
State	Published - Apr 2019
Externally published	Yes
Event	2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019 - Paris, France Duration: Apr 29 2019 → May 2 2019

Publication series

Name	INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019

Conference

Conference	2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019
Country/Territory	France
City	Paris
Period	4/29/19 → 5/2/19

ASJC Scopus subject areas

Hardware and Architecture
Signal Processing
Information Systems and Management
Safety, Risk, Reliability and Quality
Computer Networks and Communications

Online availability

10.1109/INFCOMW.2019.8845042

Library availability

Discover UIUC Full Text

Cite this

Zhang, D., & Wang, D. (2019). Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems. In INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019 (pp. 977-978). Article 8845042 (INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFCOMW.2019.8845042

Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems. / Zhang, Daniel; Wang, Dong.
INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 977-978 8845042 (INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, D & Wang, D 2019, Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems. in INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019., 8845042, INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 977-978, 2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019, Paris, France, 4/29/19. https://doi.org/10.1109/INFCOMW.2019.8845042

Zhang D, Wang D. Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems. In INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 977-978. 8845042. (INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019). doi: 10.1109/INFCOMW.2019.8845042

Zhang, Daniel ; Wang, Dong. / Demo Abstract : Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems. INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 977-978 (INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019).

@inproceedings{03e0054fdf104da9a6b8fd9ff2751853,

title = "Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems",

abstract = "Social sensing based Edge Computing systems (SSEC) have emerged as a new application paradigm in leveraging privately owned edge/IoT devices to collectively provide ubiquitous sensing, computation, and services. In this demo, we compare and contrast various task allocation strategies in SSEC in supporting delay sensitive social sensing applications. We evaluate the system on two real-time social sensing applications and demonstrate the energy savings as well as the Quality of Service (QoS) of the SSEC system. The demonstrated framework highlights the deficiency in traditional pure top-down and bottom-up task allocation solutions and validates a new hybrid task allocation strategy that is more scalable and efficient.",

author = "Daniel Zhang and Dong Wang",

note = "Funding Information: ACKNOWLEDGMENTS This research is supported in part by the National Science Foundation under Grant No. CNS-1831669, CBET-1637251, CNS-1566465 and IIS-1447795, Army Research Office under Grant W911NF-17-1-0409. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019 ; Conference date: 29-04-2019 Through 02-05-2019",

year = "2019",

month = apr,

doi = "10.1109/INFCOMW.2019.8845042",

language = "English (US)",

series = "INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "977--978",

booktitle = "INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019",

address = "United States",

}

TY - GEN

T1 - Demo Abstract

T2 - 2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019

AU - Zhang, Daniel

AU - Wang, Dong

N1 - Funding Information: ACKNOWLEDGMENTS This research is supported in part by the National Science Foundation under Grant No. CNS-1831669, CBET-1637251, CNS-1566465 and IIS-1447795, Army Research Office under Grant W911NF-17-1-0409. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. Publisher Copyright: © 2019 IEEE.

PY - 2019/4

Y1 - 2019/4

N2 - Social sensing based Edge Computing systems (SSEC) have emerged as a new application paradigm in leveraging privately owned edge/IoT devices to collectively provide ubiquitous sensing, computation, and services. In this demo, we compare and contrast various task allocation strategies in SSEC in supporting delay sensitive social sensing applications. We evaluate the system on two real-time social sensing applications and demonstrate the energy savings as well as the Quality of Service (QoS) of the SSEC system. The demonstrated framework highlights the deficiency in traditional pure top-down and bottom-up task allocation solutions and validates a new hybrid task allocation strategy that is more scalable and efficient.

AB - Social sensing based Edge Computing systems (SSEC) have emerged as a new application paradigm in leveraging privately owned edge/IoT devices to collectively provide ubiquitous sensing, computation, and services. In this demo, we compare and contrast various task allocation strategies in SSEC in supporting delay sensitive social sensing applications. We evaluate the system on two real-time social sensing applications and demonstrate the energy savings as well as the Quality of Service (QoS) of the SSEC system. The demonstrated framework highlights the deficiency in traditional pure top-down and bottom-up task allocation solutions and validates a new hybrid task allocation strategy that is more scalable and efficient.

UR - http://www.scopus.com/inward/record.url?scp=85073219557&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85073219557&partnerID=8YFLogxK

U2 - 10.1109/INFCOMW.2019.8845042

DO - 10.1109/INFCOMW.2019.8845042

M3 - Conference contribution

AN - SCOPUS:85073219557

T3 - INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019

SP - 977

EP - 978

BT - INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 29 April 2019 through 2 May 2019

ER -

Demo Abstract: Real-time Social Sensing Task Allocation Strategies in Heterogeneous Edge Computing Systems

Abstract

Publication series

Conference

ASJC Scopus subject areas

Online availability

Library availability

Related links

Fingerprint

Cite this