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Online resource allocation in edge computing using distributed bidding approaches

Online resource allocation in edge computing using distributed bidding approaches
Online resource allocation in edge computing using distributed bidding approaches
Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. We focus on a distributed resource allocation method in which servers operate independently and do not communicate with each other, but interact with clients (tasks) to make allocation decisions. This provides robustness and does not require service providers to share information about their configurations or workloads. We propose a two-round bidding approach of assigning tasks to edge cloud servers, while taking into account various processing requirements and server constraints. We consider cases in which all jobs have equal utility, cases where jobs have different utilities but users do not disclose these utilities to servers, and cases where users disclose the utility of their jobs to servers. We evaluate the performance using extensive realistic simulations. Results show that our approach is very close to an optimal assignment, with discrepancy not exceeding 5%.
Rublein, Caroline
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Mehmeti, Fidan
072c95d8-c595-462c-9c1e-c80adfb731d3
Towers, Mark
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Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
La Porta, Thomas
ed53743f-f7fa-4179-80d6-5d7860d47a50
Rublein, Caroline
96263ac5-f17a-45b1-ae0c-6527c314b068
Mehmeti, Fidan
072c95d8-c595-462c-9c1e-c80adfb731d3
Towers, Mark
18e6acc7-29c4-4d0c-9058-32d180ad4f12
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
La Porta, Thomas
ed53743f-f7fa-4179-80d6-5d7860d47a50

Rublein, Caroline, Mehmeti, Fidan, Towers, Mark, Stein, Sebastian and La Porta, Thomas (2021) Online resource allocation in edge computing using distributed bidding approaches. In 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS). 9 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. We focus on a distributed resource allocation method in which servers operate independently and do not communicate with each other, but interact with clients (tasks) to make allocation decisions. This provides robustness and does not require service providers to share information about their configurations or workloads. We propose a two-round bidding approach of assigning tasks to edge cloud servers, while taking into account various processing requirements and server constraints. We consider cases in which all jobs have equal utility, cases where jobs have different utilities but users do not disclose these utilities to servers, and cases where users disclose the utility of their jobs to servers. We evaluate the performance using extensive realistic simulations. Results show that our approach is very close to an optimal assignment, with discrepancy not exceeding 5%.

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Online Resource Allocation in Edge Computing Using Distributed Bidding Approaches - Author's Original
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Accepted/In Press date: 8 July 2021

Identifiers

Local EPrints ID: 450754
URI: http://eprints.soton.ac.uk/id/eprint/450754
PURE UUID: da2528d1-e61e-4003-8178-f912e298b8fc
ORCID for Sebastian Stein: ORCID iD orcid.org/0000-0003-2858-8857

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Date deposited: 10 Aug 2021 16:30
Last modified: 11 Aug 2021 01:39

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Contributors

Author: Caroline Rublein
Author: Fidan Mehmeti
Author: Mark Towers
Author: Sebastian Stein ORCID iD
Author: Thomas La Porta

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