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New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing

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PRIMA 2019: Principles and Practice of Multi-Agent Systems (PRIMA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11873))

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.

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Notes

  1. 1.

    While the figure illustrates an example with only one overloaded region, our description below generalizes to the case where there are multiple overloaded regions.

  2. 2.

    This indicator counts the number of hops a node is from the overloaded agent.

  3. 3.

    If an agent receives this information from more than one neighbor at the same time, it breaks ties by identifiers.

  4. 4.

    If there are multiple paths per client pool, we randomly choose one of them.

  5. 5.

    https://github.com/map-dcomp/map-code.

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Acknowledgment

This research is supported by Defense Advanced Research Projects Agency (DARPA) contract HR001117C0049. The views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. This document does not contain technology or technical data controlled under either U.S. International Traffic in Arms Regulation or U.S. Export Administration Regulations. Approved for public release, distribution unlimited (DARPA DISTAR 31530, 6/6/19).

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, USA

    Khoi D. Hoang, Christabel Wayllace & William Yeoh

  2. Raytheon BBN Technologies, Cambridge, USA

    Jacob Beal, Aaron Paulos & Jon Schewe

  3. Department of Electrical and Computer Engineering, University of Iowa, Iowa City, USA

    Soura Dasgupta & Yuanqiu Mo

Authors
  1. Khoi D. Hoang
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  2. Christabel Wayllace
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  3. William Yeoh
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  4. Jacob Beal
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  5. Soura Dasgupta
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  6. Yuanqiu Mo
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  7. Aaron Paulos
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  8. Jon Schewe
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Corresponding author

Correspondence to Khoi D. Hoang .

Editor information

Editors and Affiliations

  1. Università degli Studi di Torino, Turin, Italy

    Matteo Baldoni

  2. Utrecht University, Utrecht, The Netherlands

    Mehdi Dastani

  3. Zhejiang University, Hangzhou, China

    Beishui Liao

  4. National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

    Yuko Sakurai

  5. University of Texas at Dallas, Richardson, TX, USA

    Rym Zalila Wenkstern

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Hoang, K.D. et al. (2019). New Distributed Constraint Reasoning Algorithms for Load Balancing in Edge Computing. In: Baldoni, M., Dastani, M., Liao, B., Sakurai, Y., Zalila Wenkstern, R. (eds) PRIMA 2019: Principles and Practice of Multi-Agent Systems. PRIMA 2019. Lecture Notes in Computer Science(), vol 11873. Springer, Cham. https://doi.org/10.1007/978-3-030-33792-6_5

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  • DOI: https://doi.org/10.1007/978-3-030-33792-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33791-9

  • Online ISBN: 978-3-030-33792-6

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