scholarly journals Prioritized Uplink Resource Allocation in Smart Grid Backscatter Communication Networks via Deep Reinforcement Learning

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 622
Author(s):  
Zhixiang Yang ◽  
Lei Feng ◽  
Zhengwei Chang ◽  
Jizhao Lu ◽  
Rongke Liu ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Communication Networks ◽  
Smart Grids ◽  
Wireless Sensors ◽  
Green Technology ◽  
Wireless Sensor ◽  
Communication Model ◽  
Backscatter Communication ◽  
Exchange Information ◽  
Business Requirements

With the rapid increase in the number of wireless sensor terminals in smart grids, backscattering has become a very promising green technology. By means of backscattering, wireless sensors can either reflect energy signals in the environment to exchange information with each other or capture the energy signals to recharge their batteries. However, the changing environment around wireless sensors, limited radio frequency and various service priorities in uplink communications bring great challenges in allocation resources. In this paper, we put forward a backscatter communication model based on business priority and cognitive network. In order to achieve optimal throughput of system, an asynchronous advantage actor-critic (A3C) algorithm is designed to tackle the problem of uplink resource allocation. The experimental results indicate that the presented scheme can significantly enhance overall system performance and ensure the business requirements of high-priority users.

scholarly journals Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 567 ◽  
Author(s):  
Chatura Seneviratne ◽  
Patikiri Arachchige Don Shehan Nilmantha Wijesekara ◽  
Henry Leung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Smart Grid ◽  
Communication Networks ◽  
Smart Grids ◽  
Measurement Errors ◽  
Power Grid ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Grid Infrastructures

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.

scholarly journals Modified Backscatter Communication Model for Wireless Communication Network Applications

2021 ◽  
Vol 3 (2) ◽  
pp. 107-117
Author(s):  
Joy Iong Zong Chen
Keyword(s):  
Wireless Communication ◽  
Communication Networks ◽  
Large Scale ◽  
Simultaneous Increase ◽  
High Signal ◽  
Communication Model ◽  
Green Communication ◽  
Efficient Manner ◽  
Backscatter Communication ◽  
Security And Reliability

The green communication and large-scale connection issues will be faced by the wireless communication networks with futuristic sixth generation (6G) technology. The radio-frequency (RF) and spectrum sources may be shared simultaneously to achieve optimal communication in these networks by means of backscatter devices (BD) that may function in constrained spectrums as well as the stringent energy scenarios of green Internet-of-things (IoT) by means of the proposed novel modified backscatter communication model (BCM). Unlicensed eavesdroppers may interfere with the BD due to its vulnerability caused by the wireless communication channels and their broadcasting nature. The intrusion of an unlicensed eavesdropper is detected in an efficient manner by means of the proposed BCM. The analytical derivations of intercept probability (IP) and outage probability (OP) are invoked to analyze the security and reliability of the proposed architecture. Under high main-to-eavesdropper ratio (MER) regime, the IP and under high signal-to-noise ratio (SNR) regime, the OP asymptotic behaviors are estimated additionally. Based on the results of performance evaluation, it is evident that there is a decrease in the security of BD with the increase in MER while there is a simultaneous increase in the legitimate user security. Various system parameters may be adjusted for optimizing the security and reliability performance trade-off. For diverse orders, the existence of error floors are indicated by the non-zero fixed constant of BD and the legitimate user’s OP when high SNR value is observed at the system.

scholarly journals Resource Allocation in Cognitive Radio Wireless Sensor Networks with Energy Harvesting

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5115 ◽  
Author(s):  
Haitao Xu ◽  
Hongjie Gao ◽  
Chengcheng Zhou ◽  
Ruifeng Duan ◽  
Xianwei Zhou
Keyword(s):  
Resource Allocation ◽  
Wireless Sensor Networks ◽  
Cognitive Radio ◽  
Energy Harvesting ◽  
Information Transmission ◽  
Wireless Sensors ◽  
Wireless Sensor ◽  
Game Model ◽  
Equilibrium Solutions ◽  
Nash Equilibrium Solutions

The progress of science and technology and the expansion of the Internet of Things make the information transmission between communication infrastructure and wireless sensors become more and more convenient. For the power-limited wireless sensors, the life time can be extended through the energy-harvesting technique. Additionally, wireless sensors can use the unauthored spectrum resource to complete certain information transmission tasks based on cognitive radio. Harvesting enough energy from the environments, the wireless sensors, works as the second users (SUs) can lease spectrum resource from the primary user (PU) to finish their task and bring additional transmission cost to themselves. To minimize the overall cost of SUs and to maximize the spectrum profit of the PU during the information transmission period, we formulated a differential game model to solve the resource allocation problem in the cognitive radio wireless sensor networks with energy harvesting, considering the SUs as the game players. By solving the proposed resource allocation game model, we found the open loop Nash equilibrium solutions and feedback Nash equilibrium solutions for all SUs as the optimal control strategies. Ultimately, series numerical simulation experiments have been made to demonstrate the rationality and effectiveness of the game model.

PERFORMANCE EVALUATION ANALYSIS OF WIRELESS SENSOR NETWORKS ROUTING PROTOCOLS IN SMART GRIDS

2016 ◽  
Vol 26 (1) ◽  
pp. 17
Author(s):  
Carlos Deyvinson Reges Bessa
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Smart Grids ◽  
Network Routing ◽  
Base Station ◽  
Wireless Sensor ◽  
Delay Jitter ◽  
La Red

ABSTRACTThis work aims to study which wireless sensor network routing protocol is more suitable for Smart Grids applications, through simulation of AODV protocols, AOMDV, DSDV and HTR in the NS2 simulation environment. Was simulated a network based on a residential area with 47 residences, with one node for each residence and one base station, located about 25m from the other nodes. Many parameters, such as packet loss, throughput, delay, jitter and energy consumption were tested.  The network was increased to 78 and 93 nodes in order to evaluate the behavior of the protocols in larger networks. The tests proved that the HTR is the routing protocol that has the best results in performance and second best in energy consumption. The DSDV had the worst performance according to the tests.Key words.- Smart grid, QoS analysis, Wireless sensor networks, Routing protocols.RESUMENEste trabajo tiene como objetivo estudiar el protocolo de enrutamiento de la red de sensores inalámbricos es más adecuado para aplicaciones de redes inteligentes, a través de la simulación de protocolos AODV, AOMDV, DSDV y HTR en el entorno de simulación NS2. Se simuló una red basada en una zona residencial con 47 residencias, con un nodo para cada residencia y una estación base, situada a unos 25 metros de los otros nodos. Muchos parámetros, tales como la pérdida de paquetes, rendimiento, retardo, jitter y el consumo de energía se probaron. La red se incrementó a 78 y 93 nodos con el fin de evaluar el comportamiento de los protocolos de redes más grandes. Las pruebas demostraron que el HTR es el protocolo de enrutamiento que tiene los mejores resultados en el rendimiento y el segundo mejor en el consumo de energía. El DSDV tuvo el peor desempeño de acuerdo a las pruebas.Palabras clave.- redes inteligentes, análisis de calidad de servicio, redes de sensores inalámbricas, protocolos de enrutamiento.

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