Verification of participants in task offloading to volunteered mobile devices using a Blockchain-based incentive mechanism

Miebaka-Ogan, Tamunobelema (2022) Verification of participants in task offloading to volunteered mobile devices using a Blockchain-based incentive mechanism. Masters thesis, Dublin, National College of Ireland.

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Abstract

Over the years, there has been an increase in the complexity of tasks that mobile application developers and mobile device users wish to perform on mobile devices. Sadly, this increase in the complexity of tasks has not been matched by the capabilities of most mobile devices. This is because mobile devices still suffer resource constraints in terms of memory, battery capacity, and computational capacity. Furthermore, in this era of machine learning and data mining, certain use cases like computational photography, optical character recognition, text and image labeling have made their way to mobile devices, but a high percentage of mobile devices are unable to perform these tasks. To address this issue, task offloading to volunteered mobile devices that are capable of performing these complex tasks has been identified as a possible solution. However, this comes with the challenge of incentivizing the owners of capable devices to volunteer their devices, and addressing concerns regarding security, trustworthiness, and privacy among both parties involved in the task offload process. This paper explored using a blockchain-based incentive mechanism to verify the participants in task offloading to volunteered mobile devices without compromising their privacy in order to address these concerns while enabling resource constrained devices to offload tasks. The evaluations conducted showed that the developed blockchain-based incentive mechanism enabled the verification of both parties involved in the task offloading without compromising their privacy based on pseudo-anonymity, and without adding any significant overhead to any of the stages involved in the task offloading process.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Mobile Phone Applications T Technology > T Technology (General) > Information Technology > Computer software > Mobile Phone Applications
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Tamara Malone
Date Deposited:	16 Dec 2022 11:23
Last Modified:	16 Dec 2022 11:23
URI:	https://norma.ncirl.ie/id/eprint/5992

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