2019
DOI: 10.1049/el.2019.1864
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Reinforcement learning based routing for energy sensitive wireless mesh IoT networks

Abstract: With the huge growth of the Internet of Things (IoT) in manufacturing, agricultural and numerous other applications, connectivity solutions have become increasingly important especially for those covering wide remote area in the scale of kilometre squares. Although many low-power widearea network (LPWAN) technologies such as Long Range (LoRa) are supposed to support long-range low-power wireless communication, the underneath star topology limits the scalability of the networks due to the need of a central hub.… Show more

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Cited by 13 publications
(10 citation statements)
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“…However, it is not su cient for WMN due to a stable backbone system. The reinforcement learning technique is used for energy-sensitive mesh networks [12]. The reinforcement learning technique populates and updates the routing table constantly to nd a better route.…”
Section: Multi-path Routing Protocolsmentioning
confidence: 99%
“…However, it is not su cient for WMN due to a stable backbone system. The reinforcement learning technique is used for energy-sensitive mesh networks [12]. The reinforcement learning technique populates and updates the routing table constantly to nd a better route.…”
Section: Multi-path Routing Protocolsmentioning
confidence: 99%
“…In order to verify the performance of this method, protocols such as MREBR (Maximum Residual Energy Based Routing), MEC and SOR were selected to compare with the UCEEC protocol. According to the simulation settings of these comparison protocols [3,4,[10][11][12][13]25] , the network setting is listed in Table 2.…”
Section: Simulation Data and Network Settingmentioning
confidence: 99%
“…In addition, signal strength, quality of service parameters, network power efficiency are also considered in agricultural WSN data transmission routing. The related research shows that the communication qualities of nodes in different crop growing areas are different due to the different planting and growing density [23][24][25] . By analyzing the strengths of the signals of sensor nodes, nodes are clustered according to the idea of image segmentation, and nodes that in the same connected area and ventilation are classified as a cluster.…”
Section: Introduction mentioning
confidence: 99%
“…The solution is offered in the form of an analytical model where the k-connected network model is implemented. The work carried out by Liu et al [20] has addressed the problem of energy-based routing when wireless mesh network is used with the Internet-of-Things. The presented solution is based on a unique mesh topology where the energy efficiency is carried out using a distributed manner.…”
Section: Related Workmentioning
confidence: 99%