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A truthful online mechanism for resource allocation in fog computing

A truthful online mechanism for resource allocation in fog computing
A truthful online mechanism for resource allocation in fog computing
Fog computing is a promising Internet of Things (IoT) paradigm in which data is processed near its source. Here, efficient resource allocation mechanisms are needed to assign limited fog resources to competing IoT tasks. To this end, we consider two challenges: (1) near-optimal resource allocation in a fog computing system; (2) incentivising self-interested fog users to report their tasks truthfully. To address these challenges, we develop a truthful online resource allocation mechanism called flexible online greedy. The key idea is that the mechanism only commits a certain amount of computational resources to a task when it arrives. However, when and where to allocate resources stays flexible until the completion of the task. We compare our mechanism to four benchmarks and show that it outperforms all of them in terms of social welfare by up to 10% and achieves a social welfare of about 90% of the offline optimal upper bound.
mechanism design, Fog computing, IoT, Resource allocation
363-376
Springer, Cham
Bi, Fan
5ecbdfe9-7374-40ce-9160-b0193d085ca4
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Jennings, Nick
0d0a0add-2739-4521-8915-c1e5a1e320b5
La Porta, Thomas
ed53743f-f7fa-4179-80d6-5d7860d47a50
Nayak, A.
Sharma, A.
Bi, Fan
5ecbdfe9-7374-40ce-9160-b0193d085ca4
Stein, Sebastian
cb2325e7-5e63-475e-8a69-9db2dfbdb00b
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Jennings, Nick
0d0a0add-2739-4521-8915-c1e5a1e320b5
La Porta, Thomas
ed53743f-f7fa-4179-80d6-5d7860d47a50
Nayak, A.
Sharma, A.

Bi, Fan, Stein, Sebastian, Gerding, Enrico, Jennings, Nick and La Porta, Thomas (2019) A truthful online mechanism for resource allocation in fog computing. Nayak, A. and Sharma, A. (eds.) In PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. vol. 11672, Springer, Cham. pp. 363-376 . (doi:10.1007/978-3-030-29894-4_30).

Record type: Conference or Workshop Item (Paper)

Abstract

Fog computing is a promising Internet of Things (IoT) paradigm in which data is processed near its source. Here, efficient resource allocation mechanisms are needed to assign limited fog resources to competing IoT tasks. To this end, we consider two challenges: (1) near-optimal resource allocation in a fog computing system; (2) incentivising self-interested fog users to report their tasks truthfully. To address these challenges, we develop a truthful online resource allocation mechanism called flexible online greedy. The key idea is that the mechanism only commits a certain amount of computational resources to a task when it arrives. However, when and where to allocate resources stays flexible until the completion of the task. We compare our mechanism to four benchmarks and show that it outperforms all of them in terms of social welfare by up to 10% and achieves a social welfare of about 90% of the offline optimal upper bound.

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PRICAI-Submission - Accepted Manuscript
Restricted to Repository staff only until 23 August 2020.
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More information

Accepted/In Press date: 20 April 2019
e-pub ahead of print date: 23 August 2019
Venue - Dates: The 16th Pacific Rim International Conference on Artificial Intelligence, Fiji, 2019-08-26 - 2019-08-30
Keywords: mechanism design, Fog computing, IoT, Resource allocation

Identifiers

Local EPrints ID: 431819
URI: http://eprints.soton.ac.uk/id/eprint/431819
PURE UUID: 3d0cd9ca-5d74-4bcc-84e4-67ad554f3257
ORCID for Enrico Gerding: ORCID iD orcid.org/0000-0001-7200-552X

Catalogue record

Date deposited: 19 Jun 2019 16:30
Last modified: 27 Jan 2020 13:41

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Contributors

Author: Fan Bi
Author: Sebastian Stein
Author: Enrico Gerding ORCID iD
Author: Nick Jennings
Author: Thomas La Porta
Editor: A. Nayak
Editor: A. Sharma

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