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Optimizing RPL performance based on the selection of best route between child and root node using E-MHOF method

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 11 No. 1 (2021)

DOI
10.11591/ijece.v11i1.pp224-231
ISSN
2722-2578, 2088-8708
Published
2021-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

IETF has proposed the routing protocol for low power and lossy networks (RPL) for IOT as view as light weight routing protocol. In RPL, the objective function (OF) is used to select the best route between child and root node. Several researches have been conducted in order to, enhance OF according to number parameters such as number of hops, remaining energy and expected number of transmissions (ETX), without a consideration to other challenges such as congestion node problem and latency. So, to overcome these challenges a new technique called “Enhance-Minimum Rank with Hysteresis Objective Function (MHOF)” is proposed in this paper, to select the ideal path between the child and root node. The technique is consisted of three layers: parent selection layer in which parent is selected based on three parameters (ETX, RSSI and nodes’ residual energy), path selection layer in which the best route is chosen according to the minimum of (average ETX value) and maximum of (average remaining energy value) of all nodes in the selected route. The last layer is child node minimization, which utilized to solve the congestion node energy problem by using two parameters (RSSI reference and threshold value). The proposed method has been implemented and evaluated by using Cooja simulator software. The simulation results have shown that selected path with E-MHOF is increased the network lifetime and reduced latency in comparison with MHOF.

Collaboration network of the authors

4 authors · 5 co-authorship links · 1 across different organisations

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  • University of Baghdad
  • Mustansiriyah University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Nadia Adnan Shiltagh Al‐JamaliUniversity of Baghdad2
Mahmood Zaki AbdullahMustansiriyah University1
Dina A. Abdul QaderAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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