Optimized Cloudlet Scheduling Based Method for Mobile Phones

DOI

10.2991/pntim-19.2019.87How to use a DOI?

Keywords

Cloudlet Computing; Consumer; Cloud Architecture; AES Algorithm; Encryption and Decryption

Abstract

The improvement in communication technology incorporates sophisticated electronic gadgets that rely on wireless technique to support the signal transmission from the emitter to the receiver points. The cloudlet scheduling method relies on the environment and task type to accomplish the scheduling process in an algorithm supported by the visual machine programs. The paper captures the cloudlet network gains attributed to the increased use of cloudlet scheduling technique in tablets and mobile phones operated within the communication and data delivery platform. The system relies on improved storage space and processing speed with which the systems works with reference of minimizing power usage. The platform sustains efficient programming of tasks through the application of meta-heuristic algorithms. The paper focuses on AES algorithm and how it solves a given task at every instance while optimizing system efficiency. The beauty of the algorithm is efficient energy consumption in the data transfer platform that adopts the analysis in response to the task completion based on first-come-first-serve. The concept sustains the sequences of service delivery in the computing networks. The algorithm anchored in the cloudlet platform facilitates the use of the internet to support data transmission between different users and the server that rely on the same computing infrastructure.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Alshamaileh Mohammad
AU  - Li Chunlin
PY  - 2019/11
DA  - 2019/11
TI  - Optimized Cloudlet Scheduling Based Method for Mobile Phones
BT  - Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)
PB  - Atlantis Press
SP  - 425
EP  - 429
SN  - 2589-4943
UR  - https://doi.org/10.2991/pntim-19.2019.87
DO  - 10.2991/pntim-19.2019.87
ID  - Mohammad2019/11
ER  -