Augmenting The Performance Of Mobile Devices Through The Use of Dynamic Partition Offloading With Heterogeneous Mobile Clouds

Weje, Emmanuel Okechukwu (2020) Augmenting The Performance Of Mobile Devices Through The Use of Dynamic Partition Offloading With Heterogeneous Mobile Clouds. Masters thesis, Dublin, National College of Ireland.

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Abstract

Smart mobile devices (SMD) are a part of our daily lives and sometimes we cannot do without them. With this, they are expected to have high functionalities and resources which is sometimes not the case i.e they are resource constrained. The Mobile Cloud Computing (MCC) paradigm was introduced to solve this issue and previous works have been implemented but are not without their flaws. Most works do not consider the context of the SMD when making offloading decisions and utilize only one offloading resource option which is not particularly ideal and limits the usage of the paradigm. In this paper, we present a context aware heterogeneous approach to the MCC paradigm. We apply heterogeneity by using serverless computing functions and remote mobile clients as our offloading options. We make offloading decisions based on the SMDs context (battery, network & memory) during runtime by applying dynamic partitioning. The core of our system is the decision making engine and remote configurations. Remote configurations have been implemented to change parameters in our approach without having to modify source code. This provides flexibility. Results gotten from experiments carried out showed our system was able to make offloading decisions based on changing context and also up to 66% reduced execution time (Zhou et al. produced around 65%) for offloaded tasks as compared to local executions thus reducing power utilization. Our solution also proved to be cost efficient when utilizing serverless computing as opposed to using cloud VMs as an offload resource.

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
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Dan English
Date Deposited:	29 Jan 2021 12:05
Last Modified:	29 Jan 2021 12:05
URI:	https://norma.ncirl.ie/id/eprint/4554

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