New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing

Khoi D. Hoang; Christabel Wayllace; William Yeoh; Jacob Beal; Soura Dasgupta; Yuanqiu Mo; Aaron Paulos; Jon Schewe

doi:10.1007/978-3-030-33792-6_5

New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing

Khoi D. Hoang
, Christabel Wayllace
, William Yeoh
, Jacob Beal
, Soura Dasgupta
, Yuanqiu Mo
, Aaron Paulos
, Jon Schewe

Department of Computer Science & Engineering

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

7 Scopus citations

Abstract

Edge computing is a paradigm for improving the performance of cloud computing systems by performing data processing at the edge of the network, closer to the users and sources of data. As data processing is traditionally done in large data centers, typically located far from their users, the edge computing paradigm will reduce the communication bottleneck between the user and the location of data processing, thereby improving overall performance. This becomes more important as the number of Internet-of-Things (IoT) devices and other mobile or embedded devices continues to increase. In this paper, we investigate the use of distributed constraint reasoning (DCR) techniques to model and solve the distributed load balancing problem in edge computing problems. Specifically, we (i) provide a mapping of the distributed load balancing problem in edge computing to a distributed constraint satisfaction and optimization problem; (ii) propose two DCR algorithms to solve such problems; and (iii) empirically evaluate our algorithms against a state-of-the-art DCR algorithm on random and scale-free networks.

Original language	English
Title of host publication	PRIMA 2019
Subtitle of host publication	Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings
Editors	Matteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
Publisher	Springer
Pages	69-86
Number of pages	18
ISBN (Print)	9783030337919
DOIs	https://doi.org/10.1007/978-3-030-33792-6_5
State	Published - 2019
Event	22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, Italy Duration: Oct 28 2019 → Oct 31 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11873 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
Country/Territory	Italy
City	Turin
Period	10/28/19 → 10/31/19

Keywords

DCOPs
DisCSPs
Edge computing
Multi-agent systems

Access to Document

10.1007/978-3-030-33792-6_5

Cite this

Hoang, K. D., Wayllace, C., Yeoh, W., Beal, J., Dasgupta, S., Mo, Y., Paulos, A., & Schewe, J. (2019). New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. In M. Baldoni, M. Dastani, B. Liao, Y. Sakurai, & R. Zalila Wenkstern (Eds.), PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings (pp. 69-86). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11873 LNAI). Springer. https://doi.org/10.1007/978-3-030-33792-6_5

Hoang, Khoi D. ; Wayllace, Christabel ; Yeoh, William et al. / New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings. editor / Matteo Baldoni ; Mehdi Dastani ; Beishui Liao ; Yuko Sakurai ; Rym Zalila Wenkstern. Springer, 2019. pp. 69-86 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e43f3d3232d7415189d203682bf78037,

title = "New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing",

abstract = "Edge computing is a paradigm for improving the performance of cloud computing systems by performing data processing at the edge of the network, closer to the users and sources of data. As data processing is traditionally done in large data centers, typically located far from their users, the edge computing paradigm will reduce the communication bottleneck between the user and the location of data processing, thereby improving overall performance. This becomes more important as the number of Internet-of-Things (IoT) devices and other mobile or embedded devices continues to increase. In this paper, we investigate the use of distributed constraint reasoning (DCR) techniques to model and solve the distributed load balancing problem in edge computing problems. Specifically, we (i) provide a mapping of the distributed load balancing problem in edge computing to a distributed constraint satisfaction and optimization problem; (ii) propose two DCR algorithms to solve such problems; and (iii) empirically evaluate our algorithms against a state-of-the-art DCR algorithm on random and scale-free networks.",

keywords = "DCOPs, DisCSPs, Edge computing, Multi-agent systems",

author = "Hoang, \{Khoi D.\} and Christabel Wayllace and William Yeoh and Jacob Beal and Soura Dasgupta and Yuanqiu Mo and Aaron Paulos and Jon Schewe",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 ; Conference date: 28-10-2019 Through 31-10-2019",

year = "2019",

doi = "10.1007/978-3-030-33792-6\_5",

language = "English",

isbn = "9783030337919",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Hoang, KD, Wayllace, C, Yeoh, W, Beal, J, Dasgupta, S, Mo, Y, Paulos, A & Schewe, J 2019, New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. in M Baldoni, M Dastani, B Liao, Y Sakurai & R Zalila Wenkstern (eds), PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11873 LNAI, Springer, pp. 69-86, 22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019, Turin, Italy, 10/28/19. https://doi.org/10.1007/978-3-030-33792-6_5

New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. / Hoang, Khoi D.; Wayllace, Christabel; Yeoh, William et al.
PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings. ed. / Matteo Baldoni; Mehdi Dastani; Beishui Liao; Yuko Sakurai; Rym Zalila Wenkstern. Springer, 2019. p. 69-86 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11873 LNAI).

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

TY - GEN

T1 - New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing

AU - Hoang, Khoi D.

AU - Wayllace, Christabel

AU - Yeoh, William

AU - Beal, Jacob

AU - Dasgupta, Soura

AU - Mo, Yuanqiu

AU - Paulos, Aaron

AU - Schewe, Jon

PY - 2019

Y1 - 2019

N2 - Edge computing is a paradigm for improving the performance of cloud computing systems by performing data processing at the edge of the network, closer to the users and sources of data. As data processing is traditionally done in large data centers, typically located far from their users, the edge computing paradigm will reduce the communication bottleneck between the user and the location of data processing, thereby improving overall performance. This becomes more important as the number of Internet-of-Things (IoT) devices and other mobile or embedded devices continues to increase. In this paper, we investigate the use of distributed constraint reasoning (DCR) techniques to model and solve the distributed load balancing problem in edge computing problems. Specifically, we (i) provide a mapping of the distributed load balancing problem in edge computing to a distributed constraint satisfaction and optimization problem; (ii) propose two DCR algorithms to solve such problems; and (iii) empirically evaluate our algorithms against a state-of-the-art DCR algorithm on random and scale-free networks.

AB - Edge computing is a paradigm for improving the performance of cloud computing systems by performing data processing at the edge of the network, closer to the users and sources of data. As data processing is traditionally done in large data centers, typically located far from their users, the edge computing paradigm will reduce the communication bottleneck between the user and the location of data processing, thereby improving overall performance. This becomes more important as the number of Internet-of-Things (IoT) devices and other mobile or embedded devices continues to increase. In this paper, we investigate the use of distributed constraint reasoning (DCR) techniques to model and solve the distributed load balancing problem in edge computing problems. Specifically, we (i) provide a mapping of the distributed load balancing problem in edge computing to a distributed constraint satisfaction and optimization problem; (ii) propose two DCR algorithms to solve such problems; and (iii) empirically evaluate our algorithms against a state-of-the-art DCR algorithm on random and scale-free networks.

KW - DCOPs

KW - DisCSPs

KW - Edge computing

KW - Multi-agent systems

UR - https://www.scopus.com/pages/publications/85076505869

U2 - 10.1007/978-3-030-33792-6_5

DO - 10.1007/978-3-030-33792-6_5

M3 - Conference contribution

AN - SCOPUS:85076505869

SN - 9783030337919

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 69

EP - 86

BT - PRIMA 2019

A2 - Baldoni, Matteo

A2 - Dastani, Mehdi

A2 - Liao, Beishui

A2 - Sakurai, Yuko

A2 - Zalila Wenkstern, Rym

PB - Springer

T2 - 22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019

Y2 - 28 October 2019 through 31 October 2019

ER -

Hoang KD, Wayllace C, Yeoh W, Beal J, Dasgupta S, Mo Y et al. New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. In Baldoni M, Dastani M, Liao B, Sakurai Y, Zalila Wenkstern R, editors, PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings. Springer. 2019. p. 69-86. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-33792-6_5

New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing

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