scholarly journals HADR: A Hybrid Adaptive Data Rate in LoRaWAN for Internet of Things

ICT Express ◽  
2022 ◽  
Author(s):  
Arshad Farhad ◽  
Jae-Young Pyun
Keyword(s):  
Internet Of Things ◽  
Data Rate

scholarly journals Improved Proportional Fair Algorithm for Transportation of 5G Signals in Internet of Medical Things

2020 ◽  
Vol 9 (2) ◽  
pp. 1810-1814
Keyword(s):  
Internet Of Things ◽  
Performance Metrics ◽  
Path Loss ◽  
Data Rate ◽  
Hybrid Network ◽  
The Internet ◽  
Battery Life ◽  
Proportional Fair ◽  
Internet Of Medical Things ◽  
Medical Healthcare

The Internet of medical things (IoMT) is a hybrid network inwhich numerous technologies like Bluetooth, Wi-Fi, and Cellular technology are integrated on a single platform. The internet of things applied to the medical healthcare necessitates enormous data rate and tremendous bandwidth along with better battery life with reliable and versatile connectivity. The use of 5G network satisfies these prerequisite with its tremendous data rate capabilities and assists human health services diagnosis and treatment. In this paper, improved proportional fair algorithm is introduced and is compared with existing scheduling algorithm for developing revolutionary changes in the medical healthcare.5G networks represent a contemporary approach which encounter a hybrid digital network for developing Internet of things. Performance metrics considered for simulation studies are throughput, path-loss and SNR

scholarly journals Neighbor-Aware Non-Orthogonal Multiple Access Scheme for Energy Harvesting Internet of Things

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 448
Author(s):  
Yumi Kim ◽  
Mincheol Paik ◽  
Bokyeong Kim ◽  
Haneul Ko ◽  
Seung-Yeon Kim
Keyword(s):  
Internet Of Things ◽  
Outage Probability ◽  
Multiple Access ◽  
Stochastic Game ◽  
Average Energy ◽  
Base Station ◽  
Data Rate ◽  
Transmission Power ◽  
Response Dynamics ◽  
Iot Devices

In a non-orthogonal multiple access (NOMA) environment, an Internet of Things (IoT) device achieves a high data rate by increasing its transmission power. However, excessively high transmission power can cause an energy outage of an IoT device and have a detrimental effect on the signal-to-interference-plus-noise ratio of neighbor IoT devices. In this paper, we propose a neighbor-aware NOMA scheme (NA-NOMA) where each IoT device determines whether to transmit data to the base station and the transmission power at each time epoch in a distributed manner with the consideration of its energy level and other devices’ transmission powers. To maximize the aggregated data rate of IoT devices while keeping an acceptable average energy outage probability, a constrained stochastic game model is formulated, and the solution of the model is obtained using a best response dynamics-based algorithm. Evaluation results show that NA-NOMA can increase the average data rate up to 22% compared with a probability-based scheme while providing a sufficiently low energy outage probability (e.g., 0.05).

scholarly journals Reducing the Data Rate in Internet of Things Applications by Using Wireless Sensor Network

2020 ◽  
Vol 16 (03) ◽  
pp. 107
Author(s):  
Omar Hashim Yahya ◽  
Haider Alrikabi ◽  
Ibtisam A. Aljazaery
Keyword(s):  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Data Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Internet ◽  
Sink Node ◽  
Ip Network ◽  
Transceiver Module

<p>Du to the raising  number  of  using Internet of Things (I O T) for personal and commercial devices and applications, as well as the continues needs for improving the quality of the performance for the internet – connected devices enhance the researchers to investigate solutions for managing the data through the network Because of the fact that  the internet-connected devices needs addresses for each sensor node uses the IP-network and a large number of electronic modules is fabricated to be compatible with IPv4 only like NodeMcu, ESP8266, Arduino WIFI, and ESP32  with knowing that the IPv4 has a limited addresses number that will not be enough for the needs of  IOT developments, Many researchers turned to IPv6. In the  proposed system, another solution is suggested instead of the IPV6. The proposed idea is based on Non-IP Wireless Sensor Network (WSN) by connecting many sensing nodes to the sink-node that has an IP to forward the data to the server to be visualized in a web-portal. By this method, it is able to connect more than one node to the internet over only one IP, there for the data rate that are needed will be decreased. In addition, by using the non-IP network, the data rate and the power consuming by the sensor nodes have been reduced, the practical results are discussed for connecting four nodes over one IP4 and how it will reduce the data rate and the power consuming. In this work, the esp33 has been used as a Sink-node, and the wireless transceiver module( NRF24) has been utilized to transmit the data from nodes to esp32.</p>

Data Rate Utility Analysis for Uplink Two-Hop Internet of Things Networks

2019 ◽  
Vol 6 (2) ◽  
pp. 3601-3619 ◽  
Author(s):  
Hazem Ibrahim ◽  
Wei Bao ◽  
Uyen Trang Nguyen
Keyword(s):  
Internet Of Things ◽  
Data Rate ◽  
Utility Analysis

scholarly journals Unified Channel Management for Cognitive Radio Sensor Networks Aided Internet of Things

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2665 ◽  
Author(s):  
Saleem Aslam ◽  
Ansar-ul-Haq ◽  
Ju Jang ◽  
Kyung-Geun Lee
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Spectrum Management ◽  
Data Rate ◽  
Idle Time ◽  
Collision Probability ◽  
Channel Management ◽  
Cognitive Radio Sensor Networks ◽  
Iot Devices

Cognitive capabilities are indispensable for the Internet of Things (IoT) not only to equip them with learning, thinking, and decision-making capabilities but also to cater to their unprecedented huge spectrum requirements due to their gigantic numbers and heterogeneity. Therefore, in this paper, a novel unified channel management framework (CMF) is introduced for cognitive radio sensor networks (CRSNs), which comprises an (1) opportunity detector (ODR), (2) opportunity scheduler (OSR), and (3) opportunity ranker (ORR) to specifically address the immense and diverse spectrum requirements of CRSN-aided IoT. The unified CMF is unique for its type as it covers all three angles of spectrum management. The ODR is a double threshold based multichannel spectrum sensor that allows an IoT device to concurrently sense multiple channels to maximize spectrum opportunities. OSR is an integer linear programming (ILP) based channel allocation mechanism that assigns channels to heterogeneous IoT devices based on their minimal quality of service (QoS) requirements. ORR collects feedback from IoT devices about their transmission experience and generates special channel-sensing order (CSO) for each IoT device based on the data rate and idle-time probabilities. The simulation results demonstrate that the proposed CMF outperforms the existing ones in terms of collision probability, detection probability, blocking probability, idle-time probability, and data rate.

scholarly journals A Hierarchical Congestion Control Method in Clustered Internet of Things

2021 ◽  
Author(s):  
Sadaf Mokhtari ◽  
Hamid Barati ◽  
Alli Barati
Keyword(s):  
Internet Of Things ◽  
Congestion Control ◽  
Computer Network ◽  
Control Method ◽  
Cluster Head ◽  
Empty Space ◽  
Modern Technology ◽  
Data Rate ◽  
Second Phase ◽  
Two Parameters

Abstract Internet of things (IoT) is a modern technology where data can be transmitted to any things (human, animal, or object) over communications networks, whether Internet or intranet. Congestion occurs when the input data rate to the node, higher than the output data rate of node. Congestion control in computer network modulates traffic entry into a network in order to avoid congestive. This paper suggests a method for congestion control in the internet of things in two phases. The first phase is intra-cluster congestion control, which uses two parameters congestion score (CS) and buffer empty space (BES) to congestion avoidance. In this phase based on these two parameters, 9 states are defined to determine the congestion status of each node, and based on these 9 states the appropriate decision is made to the node. The second phase is inter-clusters congestion control. In this phase, after determined cluster head priority, the parameters of back off timer (BFT), waiting time to receive acknowledgment (WTTRACK), sequence number (SEQ) and retransmission counter (RC) are used for congestion control. The proposed congestion control method is simulated by NS-2 software. A comparison between the performance of proposed method and conventional methods shows that applying proposed method results in a significant improvement in average congestion score (CS), packet lost rate, energy consumption and end-to-end delay.

scholarly journals Enhanced LoRaWAN Adaptive Data Rate for Mobile Internet of Things Devices

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6466 ◽  
Author(s):  
Arshad Farhad ◽  
Dae-Ho Kim ◽  
Santosh Subedi ◽  
Jae-Young Pyun
Keyword(s):  
Internet Of Things ◽  
Signal To Noise Ratio ◽  
Moving Average ◽  
Data Rate ◽  
Mobile Internet ◽  
Area Network ◽  
Wide Area Network ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Efficient Resource

A long-range wide area network (LoRaWAN) is one of the leading communication technologies for Internet of Things (IoT) applications. In order to fulfill the IoT-enabled application requirements, LoRaWAN employs an adaptive data rate (ADR) mechanism at both the end device (ED) and the network server (NS). NS-managed ADR aims to offer a reliable and battery-efficient resource to EDs by managing the spreading factor (SF) and transmit power (TP). However, such management is severely affected by the lack of agility in adapting to the variable channel conditions. Thus, several hours or even days may be required to converge at a level of stable and energy-efficient communication. Therefore, we propose two NS-managed ADRs, a Gaussian filter-based ADR (G-ADR) and an exponential moving average-based ADR (EMA-ADR). Both of the proposed schemes operate as a low-pass filter to resist rapid changes in the signal-to-noise ratio of received packets at the NS. The proposed methods aim to allocate the best SF and TP to both static and mobile EDs by seeking to reduce the convergence period in the confirmed mode of LoRaWAN. Based on the simulation results, we show that the G-ADR and EMA-ADR schemes reduce the convergence period in a static scenario by 16% and 68%, and in a mobility scenario by 17% and 81%, respectively, as compared to typical ADR. Moreover, we show that the proposed schemes are successful in reducing the energy consumption and enhancing the packet success ratio.

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