Distributed online optimization of fog computing for selfish devices with out-of-date information

Lyu, X; Ni, W; Tian, H; Liu, RP; Wang, X; Giannakis, GB; Paulraj, A

Distributed online optimization of fog computing for selfish devices with out-of-date information

Lyu, X

Ni, W

Tian, H Liu, RP

Wang, X Giannakis, GB Paulraj, A

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Wireless Communications, 2018, 17 (11), pp. 7704 - 7717
Issue Date:: 2018-11-01

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Field	Value	Language
dc.contributor.author	Lyu, X https://orcid.org/0000-0003-0404-4310	en_US
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X	en_US
dc.contributor.author	Tian, H	en_US
dc.contributor.author	Liu, RP https://orcid.org/0000-0001-7001-6305	en_US
dc.contributor.author	Wang, X	en_US
dc.contributor.author	Giannakis, GB	en_US
dc.contributor.author	Paulraj, A	en_US
dc.date.issued	2018-11-01	en_US
dc.identifier.citation	IEEE Transactions on Wireless Communications, 2018, 17 (11), pp. 7704 - 7717	en_US
dc.identifier.issn	1536-1276	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131399
dc.description.abstract	© 2002-2012 IEEE. By performing fog computing, a device can offload delay-tolerant computationally demanding tasks to its peers for processing, and the results can be returned and aggregated. In distributed wireless networks, the challenges of fog computing include lack of central coordination, selfish behaviors of devices, and multi-hop signaling delays, which can result in outdated network knowledge and prevent effective cooperations beyond one hop. This paper presents a new approach to enable cooperations of N selfish devices over multiple hops, where selfish behaviors are discouraged by a tit-for-tat mechanism. The tit-for-tat incentive of a device is designed to be the gap between the helps (in terms of energy) the device has received and offered; and indicates how much help the device can offer at the next time slot. The tit-for-tat incentives can be evaluated at every device by having all devices broadcast how much help they offered in the past time slot, and used by all devices to schedule task offloading and processing. The approach achieves asymptotic optimality in a fully distributed fashion with a time-complexity of less than O(N2). The optimality loss resulting from multi-hop signaling delays and consequently outdated tit-for-tat incentives is proved to asymptotically diminish. Simulation results show that our approach substantially reduces the time-average energy consumption of the state of the art by 50% and accommodates more tasks, by engaging devices hops away under multi-hop delays.	en_US
dc.relation.ispartof	IEEE Transactions on Wireless Communications	en_US
dc.relation.isbasedon	10.1109/TWC.2018.2869764	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	Distributed online optimization of fog computing for selfish devices with out-of-date information	en_US
dc.type	Journal Article
utslib.citation.volume	11	en_US
utslib.citation.volume	17	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.issue	11	en_US
pubs.publication-status	Published	en_US
pubs.volume	17	en_US

Abstract:

© 2002-2012 IEEE. By performing fog computing, a device can offload delay-tolerant computationally demanding tasks to its peers for processing, and the results can be returned and aggregated. In distributed wireless networks, the challenges of fog computing include lack of central coordination, selfish behaviors of devices, and multi-hop signaling delays, which can result in outdated network knowledge and prevent effective cooperations beyond one hop. This paper presents a new approach to enable cooperations of N selfish devices over multiple hops, where selfish behaviors are discouraged by a tit-for-tat mechanism. The tit-for-tat incentive of a device is designed to be the gap between the helps (in terms of energy) the device has received and offered; and indicates how much help the device can offer at the next time slot. The tit-for-tat incentives can be evaluated at every device by having all devices broadcast how much help they offered in the past time slot, and used by all devices to schedule task offloading and processing. The approach achieves asymptotic optimality in a fully distributed fashion with a time-complexity of less than O(N2). The optimality loss resulting from multi-hop signaling delays and consequently outdated tit-for-tat incentives is proved to asymptotically diminish. Simulation results show that our approach substantially reduces the time-average energy consumption of the state of the art by 50% and accommodates more tasks, by engaging devices hops away under multi-hop delays.

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http://hdl.handle.net/10453/131399