Paper Abstract and Keywords |
Presentation |
2018-07-13 11:20
Computational Capability of MEC & UE and Wireless Channel Condition Based Resource Allocation for Data Processing Time Minimization Ryuji Kobayashi, Koichi Adachi (UEC) RCS2018-119 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Due to the rapid advancement of the computing power of mobile devices, the interest in mobile applications and services have been rapidly growing. Since the computing power of mobile devices are not yet to be sufficient to handle heavy applications such as augmented reality and image recognition, the concept of mobile edge computing
(MEC) has attracted huge attention. A MEC server which can handle such heavy applications are located at the edge of the radio access network such as base stations. Thus, user equipments (UEs) can request the MEC server to process the task and get the response within short time. If multiple UEs possess the data that need to be processed by MEC server, the radio and computational resources need to be allocated to each UE by taking into account the wireless channel condition and the computational power of UEs and MEC. In this paper, we consider the allocation method of the radio and computation resources to minimize the processing completion time of computation task when the tasks can be divided. The processing completion time of the tasks are composed of three phases, uploading the tasks, executing the computation tasks at the MEC server, and returning the computation result after the processing at the MEC server. In addition, the UE itself can compute locally. For the formulated optimization problem, we propose a radio and computational resources allocation method using binary search method and Johnson’s algorithm. Our simulation result show that the proposed algorithm can reduce the task completion time up to 37% compared to the
existing methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Mobile edge computing / cellular network / resource allocation / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 125, RCS2018-119, pp. 189-194, July 2018. |
Paper # |
RCS2018-119 |
Date of Issue |
2018-07-04 (RCS) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
RCS2018-119 |
Conference Information |
Committee |
ASN NS RCS SR RCC |
Conference Date |
2018-07-11 - 2018-07-13 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hakodate Arena |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc. |
Paper Information |
Registration To |
RCS |
Conference Code |
2018-07-ASN-NS-RCS-SR-RCC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Computational Capability of MEC & UE and Wireless Channel Condition Based Resource Allocation for Data Processing Time Minimization |
Sub Title (in English) |
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Mobile edge computing |
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cellular network |
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resource allocation |
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1st Author's Name |
Ryuji Kobayashi |
1st Author's Affiliation |
The University of Electro-Communications (UEC) |
2nd Author's Name |
Koichi Adachi |
2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
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Speaker |
Author-1 |
Date Time |
2018-07-13 11:20:00 |
Presentation Time |
25 minutes |
Registration for |
RCS |
Paper # |
RCS2018-119 |
Volume (vol) |
vol.118 |
Number (no) |
no.125 |
Page |
pp.189-194 |
#Pages |
6 |
Date of Issue |
2018-07-04 (RCS) |
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