NG-RPL for Efficient P2P Routing in Low-Power Multihop Wireless Networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Yongjun | - |
dc.contributor.author | Paek, Jeongyeup | - |
dc.date.accessioned | 2021-07-20T03:42:40Z | - |
dc.date.available | 2021-07-20T03:42:40Z | - |
dc.date.issued | 2020-10 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47652 | - |
dc.description.abstract | RPL, the standard IPv6 routing protocol for low-power and lossy networks in the emerging Internet of things (IoT), is designed mainly for efficient many-to-one data collection scenarios where the majority of the traffic flows from embedded devices to a gateway. Although RPL does support root-to-node downwards routing and peer-to-peer (P2P) communication, its P2P performance is inefficient and unsatisfactory due to excessively high churn and bottlenecks in the P2P path. However, P2P routing is important for machine-to-machine communication where nodes in IoT applications communicate with one another and control devices beyond simply collecting data. In this work, we propose a neighbor-graph-based RPL (NG-RPL) that significantly improves P2P routing performance. By including additional routing information when a packet passes through the root node for the first time in a P2P communication, NG-RPL finds efficient P2P routes opportunistically, when available, without significant overhead. We implement NG-RPL in Contiki-NG and evaluate its performance through extensive Cooja simulations. Results show that NG-RPL reduces routing churn, which improves packet reception ratio, round-trip time, and energy usage of P2P communication compared to standard RPL. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | NG-RPL for Efficient P2P Routing in Low-Power Multihop Wireless Networks | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/ACCESS.2020.3028771 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.8, pp 182591 - 182599 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 000577881900001 | - |
dc.identifier.scopusid | 2-s2.0-85102846851 | - |
dc.citation.endPage | 182599 | - |
dc.citation.startPage | 182591 | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 8 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Routing | - |
dc.subject.keywordAuthor | Peer-to-peer computing | - |
dc.subject.keywordAuthor | Standards | - |
dc.subject.keywordAuthor | Internet of Things | - |
dc.subject.keywordAuthor | Routing protocols | - |
dc.subject.keywordAuthor | Spread spectrum communication | - |
dc.subject.keywordAuthor | Data collection | - |
dc.subject.keywordAuthor | Low-power and lossy network (LLN) | - |
dc.subject.keywordAuthor | peer-to-peer (P2P) | - |
dc.subject.keywordAuthor | routing protocol | - |
dc.subject.keywordAuthor | RPL | - |
dc.subject.keywordAuthor | IPv6 | - |
dc.subject.keywordAuthor | machine-to-machine (M2M) communication | - |
dc.subject.keywordAuthor | Internet of Things (IoT) | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.