Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 정형수 | - |
dc.date.accessioned | 2022-09-26T04:26:09Z | - |
dc.date.available | 2022-09-26T04:26:09Z | - |
dc.date.issued | 2020-12 | - |
dc.identifier.citation | IEEE ACCESS, v. 8, page. 216593-216606 | en_US |
dc.identifier.issn | 2169-3536 | en_US |
dc.identifier.uri | https://ieeexplore.ieee.org/document/9276401 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/173858 | - |
dc.description.abstract | The Internet of Things (IoT) is evolving rapidly and requires IoT devices to have more resources to meet the growing needs in diverse application domains. Despite increasing demands, modern IoT devices do not fully utilize somewhat over-provisioned computing resources. In this work, we introduce a new concept of IoT-assisted Edge Computing which makes use of consolidated idle resources in IoT devices for edge services through offloading edge tasks to nearby IoT devices. For the IoT-assisted edge computing be beneficent, two important conditions should be satisfied: 1) offloaded edge tasks to IoT devices do not hurt normal execution of local IoT tasks, and 2) computing resources in IoT devices should be effectively exploited to increase the throughput of edge services. To that end, we propose a collaborative task scheduling for IoT-assisted edge computing, in which an edge node determines where to offload edge tasks among participating IoT devices based on the offloaded execution time and energy consumption, and each IoT device determines when to execute the offloaded tasks considering local tasks execution. Experimental results show that the proposed scheme not only achieves near-optimal task throughput but also outperforms other scheduling algorithms in terms of deadline satisfaction ratio of time critical tasks, while guaranteeing deadlines of local tasks in IoT devices. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) funded by the Korea Government (MSIP) under Grant 2019R1A2C1011009. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_US |
dc.subject | Edge service; IoT-assisted edge computing; IoT service; task scheduling | en_US |
dc.title | Collaborative Task Scheduling for IoT-Assisted Edge Computing | en_US |
dc.type | Article | en_US |
dc.relation.volume | 8 | - |
dc.identifier.doi | 10.1109/ACCESS.2020.3041872 | en_US |
dc.relation.page | 216593-216606 | - |
dc.relation.journal | IEEE ACCESS | - |
dc.contributor.googleauthor | Kim, Youngjin | - |
dc.contributor.googleauthor | Song, Chiwon | - |
dc.contributor.googleauthor | Han, Hyuck | - |
dc.contributor.googleauthor | Jung, Hyungsoo | - |
dc.contributor.googleauthor | Kang, Sooyong | - |
dc.relation.code | 2020045465 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF COMPUTER SCIENCE | - |
dc.identifier.pid | hyungsoo.jung | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.