A robust approach for barrier-reinforcing in wireless sensor networks

Saraereh, Omar A.; Ali, Ashraf; Al-Tarawneh, Luae; Khan, Imran Khan Imran

doi:10.1016/j.jpdc.2020.12.007

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…The Internet of Everything has developed rapidly, and wireless Internet of Things applications have shown an explosive growth trend, and a huge number of M2M terminals have appeared [1][2][3][4][5][6][7][8][9][10]. Research predicts that the number of M2M terminals will increase at an annual rate of 20% [11][12][13][14][15][16][17][18][19]. The current low-power IoT communication technologies are mainly divided into two categories, namely, personal wireless local area network (WPAN) and lowpower wide area network (LWPAN) [20].…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Scheme for IoT Networks

Alhussain

2022

Int. j. commun. netw. inf. secur.

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With the advent of the Internet of Things era, "things-things interconnection" has become a new concept, that is, through the informatization and networking of the physical world, the traditionally separated physical world and the information world are interconnected and integrated. Different from the concept of connecting people in the information world in the Internet, the Internet of Things extends its tentacles to all aspects of the physical world. The proposed algorithm considers the periodical uplink data transmission in IEEE 802.11ah LWPAN and a real-time raw settings method is used. The uplink channel resources were divided into Beacon periods after the multiple nodes send data to the access point. First, the access point predicted the next data uploading time during the Beacon period. In the next Beacon period, the total number of devices that will upload data is predicted. Then, the optimal read-and-write parameters were calculated for minimum energy cost and broadcasted such information to all nodes. After this, the data is uploaded according the read-and-write scheduling by all the devices. Simulation results show that the proposed algorithm effectively improved the network state prediction accuracy and dynamically adjusted the configuration parameters which results in improved network energy efficiency in the IoT environment.

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