scholarly journals Maximizing network throughput by cooperative reinforcement learning in clustered solar-powered wireless sensor networks

2021 ◽  
Vol 17 (4) ◽  
pp. 155014772110074
Author(s):  
Yujia Ge ◽  
Yurong Nan ◽  
Xianhai Guo
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Network Throughput ◽  
Wireless Sensor ◽  
Learning Methods ◽  
Solar Powered

Power management in wireless sensor networks is very important due to the limited energy of batteries. Sensor nodes with harvesters can extract energy from environmental sources as supplemental energy to break this limitation. In a clustered solar-powered sensor network where nodes in the network are grouped into clusters, data collected by cluster members are sent to their cluster head and finally transmitted to the base station. The goal of the whole network is to maintain an energy neutrality state and to maximize the effective data throughput of the network. This article proposes an adaptive power manager based on cooperative reinforcement learning methods for the solar-powered wireless sensor networks to keep harvested energy more balanced among the whole clustered network. The cooperative strategy of Q-learning and SARSA( λ) is applied in this multi-agent environment based on the node residual energy, the predicted harvested energy for the next time slot, and cluster head energy information. The node takes action accordingly to adjust its operating duty cycle. Experiments show that cooperative reinforcement learning methods can achieve the overall goal of maximizing network throughput and cooperative approaches outperform tuned static and non-cooperative approaches in clustered wireless sensor network applications. Experiments also show that the approach is effective in response to changes in the environment, changes in its parameters, and application-level quality of service requirements.

scholarly journals Two Level Intrusion Detection Mechanism For Context and Trust in Wireless Sensor Network

2020 ◽  
Vol 8 (6) ◽  
pp. 65-71
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Trust Evaluation

21st century is considered as the era of communication, and Wireless Sensor Networks (WSN) have assumed an extremely essential job in the correspondence period. A wireless sensor network is defined as a homogeneous or heterogeneous system contains a large number of sensors, namely called nodes used to monitor different environments in cooperatives. WSN is composed of sensor nodes (S.N.), base stations (B.S.), and cluster head (C.H.). The popularity of wireless sensor networks has been increased day by day exponentially because of its wide scope of utilizations. The applications of wireless sensor networks are air traffic control, healthcare systems, home services, military services, industrial & building automation, network communications, VAN, etc. Thus the wide range of applications attracts attackers. To secure from different types of attacks, mainly intruder, intrusion detection based on dynamic state context and hierarchical trust in WSNs (IDSHT) is proposed. The trust evaluation is carried out in hierarchical way. The trust of sensor nodes is evaluated by cluster head (C.H.), whereas the trust of the cluster head is evaluated by a neighbor cluster head or base station. Hence the content trust, honest trust, and interactive trust are put forward by combining direct evaluation and feedback based evaluation in the fixed hop range. In this way, the complexity of trust management is carried in a hierarchical manner, and trust evaluation overhead is minimized.

Presenting the Hybrid Algorithm of Honeybee - Harmony in Clustering and Routing of Wireless Sensor Networks

2019 ◽  
Vol 9 (3) ◽  
pp. 357-371
Author(s):  
Mohammad Sedighimanesh ◽  
Hesam Zandhesami ◽  
Ali Sedighimanesh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Cluster Head ◽  
Rechargeable Batteries ◽  
Base Station ◽  
Wireless Sensor

Background: Wireless sensor networks are considered as one of the 21st century's most important technologies. Sensors in wireless sensor networks usually have limited and sometimes non-rechargeable batteries, which they are supposed to be preserved for months or even years. That's why the energy consumption in these networks is of a great importance. Objective: One way to improve energy consumption in a wireless sensor network is to use clustering. In clustered networks, one node is known as the cluster head and other nodes as normal members, which normal nodes send the collected data to the cluster head, and the cluster head sends the information to the base station either by a single step or by multiple steps. Method: Using clustering simplifies resource management and increases scalability, reliability, and the network lifetime. Although the cluster formation involves a time- overhead and how to choose the cluster head is another problem, but its advantages are more than its disadvantages. : The primary aim of this study is to offer a solution to reduce energy consumption in the sensor network. In this study, during the selection of cluster heads, Honeybee Algorithm is used and also for routing, Harmonic Search Algorithm is used. In this paper, the simulation is performed by using MATLAB software and the proposed method is compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) and the multi-objective fuzzy clustering algorithm (MOFCA). Result and Conclusion: By simulations of this study, we conclude that this research has remarkably increased the network lifetime with respect to EECS, LEACH, and MOFCA algorithms. In view of the energy constraints of the wireless sensor network and the non-rechargeable batteries in most cases, providing such solutions and using metaheuristic algorithms can result in a significant reduction in energy consumption and, consequently, increase in the network lifetime.

Enhanced Auxiliary Cluster Head Selection Routing Algorithm in Wireless Sensor Networks

2019 ◽  
Vol 12 ◽  
Author(s):  
Gaurav Kumar Nigam ◽  
Chetna Dabas
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection

Background & Objective: Wireless sensor networks are made up of huge amount of less powered small sensor nodes that can audit the surroundings, collect meaningful data, and send it base station. Various energy management plans that pursue to lengthen the endurance of overall network has been proposed over the years, but energy conservation remains the major challenge as the sensor nodes have finite battery and low computational capabilities. Cluster based routing is the most fitting system to help for burden adjusting, adaptation to internal failure, and solid correspondence to draw out execution parameters of wireless sensor network. Low energy adaptive clustering hierarchy is an efficient clustering based hierarchical protocol that is used to enhance the lifetime of sensor nodes in wireless sensor network. It has some basic flaws that need to be overwhelmed in order to reduce the energy utilization and inflating the nodes lifetime. Methods : In this paper, an effective auxiliary cluster head selection is used to propose a new enhanced GC-LEACH algorithm in order to minimize the energy utilization and prolonged the lifespan of wireless sensor network. Results & Conclusion: Simulation is performed in NS-2 and the outcomes show that the GC-LEACH outperforms conventional LEACH and its existing versions in the context of frequent cluster head rotation in various rounds, number of data packets collected at base station, as well as reduces the energy consumption 14% - 19% and prolongs the system lifetime 8% - 15%.

scholarly journals TLFW: A Three-Layer Framework in Wireless Rechargeable Sensor Network with a Mobile Base Station

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Anwen Wang ◽  
Xianjia Meng ◽  
Lvju Wang ◽  
Xiang Ji ◽  
Hao Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Sensor Network ◽  
Cluster Head ◽  
Mobile Station ◽  
Base Station ◽  
Wireless Sensor ◽  
Total Energy Consumption

Wireless sensor networks as the base support for the Internet of things have been a large number of popularity and application. Such as intelligent agriculture, we have to use the sensor network to obtain the growing environment data of crops and others. However, the difficulty of power supply of wireless nodes has seriously hindered the application and development of Internet of things. In order to solve this problem, people use low-power sleep scheduling and other energy-saving methods on the nodes. Although these methods can prolong the working time of nodes, they will eventually become invalid because of the exhaustion of energy. The use of solar energy, wind energy, and wireless signals in the environment to obtain energy is another way to solve the energy problem of nodes. However, these methods are affected by weather, environment, and other factors, and they are unstable. Thus, the discontinuity work of the node is caused. In recent years, the development of wireless power transfer (WPT) has brought another solution to this problem. In this paper, a three-layer framework is proposed for mobile station data collection in rechargeable wireless sensor networks to keep the node running forever, named TLFW which includes the sensor layer, cluster head layer, and mobile station layer. And the framework can minimize the total energy consumption of the system. The simulation results show that the scheme can reduce the energy consumption of the entire system, compared with a Mobile Station in a Rechargeable Sensor Network (MSiRSN).

scholarly journals Hybridized Fuzzy Based Clustering for Wireless Sensor Networks Based on Cognitive Internet of Things

2019 ◽  
Vol 8 (4) ◽  
pp. 7876-7881
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Full Range ◽  
Cluster Head ◽  
Radio Spectrum ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless sensor network explosive growth has increased demand for radio spectrum and has created problems with spectrum shortage since different wireless services and technologies have already been assigned the full range of wireless sensor networks. Cognitive radio has become a promising solution for resource-controlled wireless sensor network to access the reserved under-used frequency bands resourcefully. Artificial intelligence algorithms allow sensor nodes to avoid crowded congested bands by detecting under utilized licensed bands and to decide to adapt their transmission parameters. However, clusters are based on fixed spectrum distribution and cannot deal with the dynamic spectrum allocation required for future generation networks. Clusters are used to reduce power usage and support scalability of sensor networks. This article proposes an Hybridized Fuzzy Clustering (HFC), which groups adjacent nodes with comparable sets of idle channels and optimally forming power-efficient clusters based on three fuzzy energy parameters, proximity to the base station, and the level of the node to determine the possibility of each node being a cluster head.

scholarly journals Searching Algorithm of Dormant Node in Wireless Sensor Networks

2017 ◽  
Vol 13 (05) ◽  
pp. 122 ◽  
Author(s):  
Bo Feng ◽  
Wei Tang ◽  
Guofa Guo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sensor Network ◽  
Delaunay Triangulation ◽  
Base Station ◽  
Wireless Sensor ◽  
Effective Mechanism ◽  
Dormant State ◽  
Important Nodes

In wireless sensor networks, the nodes around the base station have higher energy consumption due to the forwarding task of all the detected data. In order to balance the energy consumption of the nodes around the base station, a reasonable and effective mechanism of node rotation dormancy is put forward. In this way, a large number of redundant nodes in the network are in a dormant state, so as to reduce the load of important nodes around the base station. The problems of the redundant nodes in the sensor network are analyzed, and a new method is proposed to distinguish the redundant nodes based on local Delaunay triangulation and multi node election dormancy mechanism. The experimental results showed that this method could effectively distinguish the redundant nodes in the network; at the same time, through the multi round election mechanism, parts of redundant nodes are made dormant. In summary, they can reduce the network energy consumption on the condition of guaranteeing the original coverage.

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

scholarly journals A Novel Framework to Secure CBWSNS Against the Selfishness Problem

2019 ◽  
Vol 7 (2) ◽  
pp. 7-16
Author(s):  
Poonam Mittal ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Defense Mechanism ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Security Level ◽  
Stochastic Algorithm ◽  
Worst Case ◽  
Cluster Heads

Dynamic and cooperative nature of sensor nodes in Wireless Sensor Networks raises question on security. Various researchers work in this direction to spot malicious, selfish and compromised nodes. Various mechanisms followed are uniqueness of clustering, reputation system and an operation at specific nodes. LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station (sink). Each node uses a stochastic algorithm at each round to determine whether it will become a cluster head in this round. Clustering process carried out in two stages takes the role of the reputation scheme and reveals specific operation at CH, IN and MNs beside their usual activities in cluster based wireless sensor networks. This paper mentioned the final structure of the security framework, corresponding attacks and defense mechanism of the model. It also discusses various security level processes of wireless sensor networks. Results implies that in a cluster-based protocol such as LEACH in which optimally 5% of the nodes are cluster heads it is likely that a significant portion of the network can be paralyzed or the entire network disabled, in the worst-case scenario, if these cluster heads are compromised. Our main contribution in this paper is our novel approach in maintaining trusted clusters through a trust-based decision-making cluster head election algorithm.

scholarly journals A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchun Qu ◽  
Libiao Lei ◽  
Xiaoming Tang ◽  
Ping Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Detection Method ◽  
Base Station ◽  
Simulation Software ◽  
Wireless Sensor ◽  
Sensor Monitoring

For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

Deep Reinforcement Learning Methods for Energy-Efficient Underwater Wireless Networking

2021 ◽  
pp. 212-223
Author(s):  
Ahmed Ali Saihood ◽  
Laith Alzubaidi
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Sensor Networks ◽  
Natural Disasters ◽  
Energy Efficient ◽  
Wireless Networking ◽  
Wireless Sensor ◽  
Learning Methods ◽  
Underwater Environment ◽  
Learning Techniques

The wireless sensor networks have been developed and extended to more expanded environments, and the underwater environment needs to develop more applications in different fields, such as sea animals monitoring, predict the natural disasters, and data exchanging between underwater and ground environments. The underwater environment has almost the same infrastructure and functions with ground environment with some limitations, such as processing, communications, and battery limits. In terms of battery limits, many techniques have been proposed; in this chapter, the authors will focus in deep reinforcement learning techniques.

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