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Paper Abstract and Keywords
Presentation 2026-04-10 10:25
GA-based Task Offloading Destination Assignment for Reducing Total Energy Consumption in Multi-access Edge Computing
Yuki Katsumi, Ryo Yamamoto, Satoshi Ohzahata (UEC) NS2026-12
Abstract (in Japanese) (See Japanese page) 
(in English) Real-time and computation-intensive services such as cloud gaming and video streaming have become increasingly common.When user devices have limited resources, task offloading to the cloud is effective because cloud servers offer abundant computing capacity.However, cloud servers are often located far from user devices, which increases communication latency and the communication energy consumption of user devices.To address this issue, MEC has attracted attention because it processes tasks near users.
However, MEC servers have limited computing resources compared to cloud servers, and concentrated offloading increases processing time and degrades QoE.Therefore, a mechanism is required that selects appropriate offloading destinations based on users’ latency requirements and system-level objectives.In this paper, we propose FBE-CEGA, a task offloading destination decision algorithm that aims to reduce total system energy consumption.Our approach uses a genetic algorithm to search for task assignments and introduces a deadline constraint and a delay fairness constraint to maintain QoE.Furthermore, the objective function includes a term proportional to the number of active MEC servers because server operation increases total energy consumption.Performance evaluations demonstrate that FBE-CEGA reduces total energy consumption and distributes latency increases across multiple users.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-access Edge Computing / Task Offloading / Quality of Experience / / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 2, NS2026-12, pp. 64-69, April 2026.
Paper # NS2026-12 
Date of Issue 2026-04-02 (NS) 
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 NS2026-12

Conference Information
Committee NS  
Conference Date 2026-04-09 - 2026-04-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Yakushima Island Environmental and Cultural Village Center + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General 
Paper Information
Registration To NS 
Conference Code 2026-04-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) GA-based Task Offloading Destination Assignment for Reducing Total Energy Consumption in Multi-access Edge Computing 
Sub Title (in English)  
Keyword(1) Multi-access Edge Computing  
Keyword(2) Task Offloading  
Keyword(3) Quality of Experience  
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1st Author's Name Yuki Katsumi  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Ryo Yamamoto  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Satoshi Ohzahata  
3rd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2026-04-10 10:25:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2026-12 
Volume (vol) vol.126 
Number (no) no.2 
Page pp.64-69 
#Pages 6 
Date of Issue 2026-04-02 (NS) 

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