NORMA eResearch @NCI Library

Delay vs power consumption in edge/fog computing

Rawat, Rakesh Singh (2020) Delay vs power consumption in edge/fog computing. Masters thesis, Dublin, National College of Ireland.

[thumbnail of Master of Science]
PDF (Master of Science)
Download (1MB) | Preview
[thumbnail of Configuration manual]
PDF (Configuration manual)
Download (1MB) | Preview


With the advent in cloud technologies a parallel rise has been seen on the use of IOT infrastructure. As part of this Edge/Fog computing paradigm we see devices like smartwatches, mobile phones and other devices constituting it. For issues like computational power, limited storage, limited power/battery and non scalable architecture are already known to be a part as deficiency in resource department of in Edge computing. One viable solution to tackle this resource problem is to offload the workload from edge/mobile to either a fog/cloudlet server or to a centralised main cloud server. So running workloads locally will drain the limited resources, and entirely executing workloads on the cloud which is called cyberforaging and has a drawback that it will incur communication cost and will have a delay as well. So a balanced approach among these two is needed. I am proposing a Novel approach for this yet open challenge of choosing what to offload to cloud and in what order for different conditions faced by a resource constraint edge/mobile device having different priority workloads. So, choices will be either to face delay by offloading to a cloud and incur communication costs compromising QoS of application or to execute this workloads on the edge/mobile devices which is power/energy(resource) constrained device. Will use a priority based queueing scheme for marking workloads with priority. Using EdgeCloudSim as a simulator to reproduce environment to prove the novel approach. After experimentation I got results which shows a lower failure percentages of high priority applications, thus increasing there QoS and also dealt with the trade off dilemma.

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 11:06
Last Modified: 29 Jan 2021 11:06

Actions (login required)

View Item View Item