TY  - JOUR
A1  - Amirinasab, Mehdi
A1  - Shamshirband, Shahaboddin
A1  - Chronopoulos, Anthony Theodore
A1  - Mosavi, Amir
A1  - Nabipour, Narjes
T1  - Energy‐Efficient Method for Wireless Sensor Networks Low‐Power Radio Operation in Internet of Things
JF  - electronics
N2  - The radio operation in wireless sensor networks (WSN) in Internet of Things (IoT)applications is the most common source for power consumption. Consequently, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. Among essential factors affecting radio operation, the time spent for checking the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in radio duty cycles and ContikiMAC. ContikiMAC is a low‐power radio duty‐cycle protocol in Contiki OS used in WakeUp mode, as a clear channel assessment (CCA) for checking radio status periodically. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Furthermore, we propose a lightweight CCA (LW‐CCA) as an extension to ContikiMAC to reduce the Radio Duty‐Cycles in false WakeUps and idle listening though using dynamic received signal strength indicator (RSSI) status check time. The simulation results in the Cooja simulator show that LW‐CCA reduces about 8% energy consumption in nodes while maintaining up to 99% of the packet delivery rate (PDR).
KW  - Internet der Dinge
KW  - Internet of things
KW  - wireless sensor networks
KW  - ContikiMAC
KW  - energy efficiency
KW  - duty-cycles
KW  - clear channel assessments
KW  - fog computing
KW  - smart sensors
KW  - signal processing
KW  - received signal strength indicator
KW  - OA-Publikationsfonds2020
KW  - RSSI
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40954
UR  - https://www.mdpi.com/2079-9292/9/2/320
VL  - 2020
IS  - volume 9, issue 2, 320
PB  - MDPI
ER  - 
TY  - JOUR
A1  - Homaei, Mohammad Hossein
A1  - Soleimani, Faezeh
A1  - Shamshirband, Shahaboddin
A1  - Mosavi, Amir
A1  - Nabipour, Narjes
A1  - Varkonyi-Koczy, Annamaria R.
T1  - An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System
JF  - IEEE Access
N2  - The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms.
KW  - Internet der dinge
KW  - IOT
KW  - Internet of things
KW  - wireless sensor network
KW  - congestion control
KW  - fuzzy decision making
KW  - back-pressure
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40805
UR  - https://ieeexplore.ieee.org/document/8967114
IS  - volume 8
SP  - 20628
EP  - 20645
PB  - IEEE
ER  -