A Novel Network Coding Algorithm to Improve TCP in Wireless Networks

Jannesari, Azam; Sarram, Mehdi Agha; Sheikhpour, Razieh

doi:10.1007/s11277-019-06781-5

Cited by 4 publications

(3 citation statements)

References 31 publications

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“…Normally radio frequency modems are available with good accuracy rate but it consumes more power. Jannesari et al, the two IEEE standards Wi-Fi and Wireless Personal Network are established wide area network with less coverage constraints [8]. The Bluetooth based communication medium also available to handles the data processing.…”

Section: Related Workmentioning

confidence: 99%

DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

Gokulakannan¹

2023

Intelligent Automation &Amp; Soft Computing

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Deep learning is the subset of artificial intelligence and it is used for effective decision making. Wireless Sensor based automated irrigation system is proposed to monitor and cultivate crop. Our system consists of Distributed wireless sensor environment to handle the moisture of the soil and temperature levels. It is automated process and useful for minimizing the usage of resources such as water level, quality of the soil, fertilizer values and controlling the whole system. The mobile app based smart control system is designed using deep belief network. This system has multiple sensors placed in agricultural field and collect the data. The collected transmitted to cloud server and deep learning process is applied for making decisions. DeepQ residue analysis method is proposed for analyzing automated and sensor captured data. Here, we used 512 × 512 × 3 layers deep belief network and 10000 trained data and 2500 test data are taken for evaluations. It is automated process once data is collected deep belief network is generated. The performance is compared with existing results and our process method has 94% of accuracy factor. Also, our system has low cost and energy consumption also suitable for all kind of agricultural fields.

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Section: Related Workmentioning

confidence: 99%

DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

Gokulakannan¹

2023

Intelligent Automation &Amp; Soft Computing

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“…De esta manera se reducen: el uso del medio inalámbrico, la contienda por el medio y los errores de transmisión. Es así como se espera que este nuevo paradigma maximice los límites de desempeño de las redes inalámbricas actuales [8,9], incluyendo a las iWMNs.…”

Section: Capítulounclassified

“…Jannesari et al proponen un algoritmo de codificación de red denominado ENC (Efficiency Network Coding) [102]. ENC permite codificar paquetes con diferencias marginales en su tamaño, lo cual permite utilizar eficientemente el ancho de banda disponible en la red.…”

Section: Enc -Codificación De Red Eficienteunclassified

Codificación adaptativa de red para sistemas inalámbricos IEEE 802.11s en modo infraestructura

Arellano

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IEEE 802.11S INFRASTRUCTURE WIRELESS MESH NETWORKS (commonly known as iWMNs) are integrated by static wireless nodes capable of working in coordination to route data packets. In this way, the nodes collaborate to exchange information with each other. In addition, iWMNs can be interconnected with other network technologies and, in this way, help to wirelessly extend the coverage of these networks; for example, iWMNs are used today to extend the coverage of cellular or wired networks. Thanks to this feature, and also to their low infrastructure cost, iWMNs networks are considered today as an excellent option to offer wireless Internet connectivity services in geographical areas where the use of other network technologies is unfeasible. Despite the promising features of iWMNs, there are studies and results that cast doubt on their performance, since it has been documented that the performance of these networks can be affected by numerous factors; such as the use of TCP to transport information in wireless environments, the transmission errors in the wireless medium, as well as the access contention between network users. All these factors can degrade the performance of iWMNs and, consequently, affect the quality of the experience for the users. In this doctoral thesis, some of these performance problems are addressed through the technique called adaptive network coding. With this technique, the nodes of an iWMN are allowed to combine various data packets and thus build an encoded packet; this packet contains the information from the original packets, requiring only one wireless transmission to transport the original information, reducing the use of the wireless medium and, thereby, increasing the capacity of the network. The proposed technique also seeks to adapt the coding process to the traffic conditions in the network through the dynamic adjustment of the waiting time of the packets in a node before they can be combined. This proposal aims to substantially improve the performance of iWMNs, solving some problems that affect them. The evaluation of the proposal is carried out through simulations and numerical evaluations. After a detailed analysis of the results, we find that iWMNs can improve their performance by using the adaptive network coding technique, since the number of wireless transmissions in the network is considerably reduced, and, consequently, i) the medium access contention decreases, ii) the probability of errors in the medium is reduced, and iii) the capacity of the network increases.

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Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Manikandan

Chinnadurai

2021

Wireless Pers Commun

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A Novel Network Coding Algorithm to Improve TCP in Wireless Networks

Cited by 4 publications

References 31 publications

DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

Codificación adaptativa de red para sistemas inalámbricos IEEE 802.11s en modo infraestructura

Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

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