Authors:
Yousra Ben Aissa
1
;
Hanen Grichi
2
;
Mohamed Khalgui
3
;
Anis Koubaa
4
and
Abdelmalik Bachir
5
Affiliations:
1
School of Intelligence Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070, China, National Institute of Applied Sciences and Technology (INSAT), University of Carthage, Tunisia, Information Faculty of Mathematical Physical and Natural Sciences, University of Tunis El Manar, Tunis, Tunisia, Computer Science Department, University of Biskra and Algeria
;
2
LISI Laboratory, Tunisia Polytechnic School, INSAT Institute, University of Carthage, Tunis and Tunisia
;
3
School of Intelligence Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070 and China
;
4
Prince Sultan University, Saudi Arabia, CISTER/INESC TEC and ISEP-IPP, Porto and Portugal
;
5
Computer Science Department, University of Biskra and Algeria
Keyword(s):
RPL Objective Function, DODAG Construction, Low Power and Lossy Network (LLN), Congestion-aware, New DODAG Request Messages (NDR and NDR-Ack).
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Real-Time Systems
Abstract:
Low power and lossy networks (LLNs) require a routing protocol under real-time and energy constraints, congestion aware and packet priority. Thus, Routing Protocol for Low power and lossy network (RPL) is recommended by Internet Engineering Task force (IETF) for LLN applications. In RPL, nodes select their optimal paths towards their preferred parents after meeting routing metrics that are injected in the objective function (OF). However, RPL did not impose any routing metric and left it open for implementation. In this paper, we propose a new RPL objective function which is based on the quality of service (QoS) and congestion-aware. In the case paths fail, we define new RPL control messages for enriching the network by adding more routing nodes. Extensive simulations show that QCOF achieves significant improvement in comparison with the existing objective functions, and appropriately satisfies real-time applications under QoS and network congestion.