S-CDCA: a semi-cluster directive-congestion protocol for priority-based data in WSNs

Marwan Ihsan Shukur

Abstract


The internet of things (IoT) protocols and regulations are being developed forvarious applications includes: habitat monitoring, machinery control, general health-care, smart-homes and more. A great part of I0T comprised of sensors nodes in connected networks (i.e. sensor networks.). A sensor network is a group of nodes with sensory module and computational elements connected through network interfaces. The most interesting type of sensor networks are wireless sensor networks. The nodes here are connected through wirless interfaces. The shared medium between these nodes, creates different challenges. Congestion in such network is ineavitable. Different models andmethods were proposed to alleviate congestion in wireless sensor networks.This paper presents a semi-cluster directive congestion method that allivatenetwork congestion forpriority-baseddata transmission. The method simprove the network performance by implementing temporary cluster forlow level priority data packets while providing a clear link between highpriority data source node and the network base station. Simulation resultsshow that. The proposed method outperformes ad hocOn-demand distance vector (AODV) reactive procotol approach and priority-based congestion control dynamic clustering (PCCDC) a cluster-based methodin network energy consumption and control packets overhead during network operation.The proposed method also shows comparative improvments in end-to-enddelays versus PCCDC.

Keywords


Congestion; Internet of things; Wireless networks; Wireless sensor networks

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v23.i1.pp438-444

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics