TY - GEN
T1 - DEVS-RPL
T2 - IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024
AU - Albinali, Hussah
AU - Azzedin, Farag
AU - Riaz, Muhammad
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The Internet of Things is rapidly advancing, enabling interactions with the physical world and presenting various applications. Routing Protocol over Low-Power and Lossy Networks (RPL) is the routing protocol introduced by the IETF for IoT environments. RPL has been subjected to multiple attacks, making it essential to develop a model that defines its behavior. To achieve this, we propose DEVS-RPL, which employs the discrete event model to specify the normal behavior of network nodes in generating RPL messages. DEVS-RPL estimates the mean and frequency of each generated RPL message by defining the participant states and utilizing the time advance function. As a proof of concept, the normal network traffic produced by the Cooja simulator is compared to the RPL messages generated by the DEVS-RPL model. We find that the mean absolute percentage error (MAPE) of DEVS-RPL is less than 9%, indicating the high accuracy of the proposed model.
AB - The Internet of Things is rapidly advancing, enabling interactions with the physical world and presenting various applications. Routing Protocol over Low-Power and Lossy Networks (RPL) is the routing protocol introduced by the IETF for IoT environments. RPL has been subjected to multiple attacks, making it essential to develop a model that defines its behavior. To achieve this, we propose DEVS-RPL, which employs the discrete event model to specify the normal behavior of network nodes in generating RPL messages. DEVS-RPL estimates the mean and frequency of each generated RPL message by defining the participant states and utilizing the time advance function. As a proof of concept, the normal network traffic produced by the Cooja simulator is compared to the RPL messages generated by the DEVS-RPL model. We find that the mean absolute percentage error (MAPE) of DEVS-RPL is less than 9%, indicating the high accuracy of the proposed model.
KW - DEVS formalism
KW - IoT
KW - Modeling and simulation
KW - Routing
KW - RPL
UR - https://www.scopus.com/pages/publications/85210556389
U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00067
DO - 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics62450.2024.00067
M3 - Conference contribution
AN - SCOPUS:85210556389
T3 - Proceedings - IEEE Congress on Cybermatics: 2024 IEEE International Conferences on Internet of Things, iThings 2024, IEEE Green Computing and Communications, GreenCom 2024, IEEE Cyber, Physical and Social Computing, CPSCom 2024, IEEE Smart Data, SmartData 2024
SP - 294
EP - 299
BT - Proceedings - IEEE Congress on Cybermatics
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 August 2024 through 22 August 2024
ER -