scholarly journals Reinforcement Learning based Node Sleep or Wake-up Time Scheduling Algorithm for Wireless Sensor Network

2020 ◽  
Vol 5 (4) ◽  
pp. 707-731
Author(s):  
Parag Verma ◽  
Ankur Dumka ◽  
Dhawal Vyas ◽  
Anuj Bhardwaj
Keyword(s):  
Reinforcement Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Scheduling Algorithm ◽  
Data Packet ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Time Scheduling ◽  
Time Band

A wireless sensor network is a collection of small sensor nodes that have limited energy and are usually not rechargeable. Because of this, the lifetime of wireless sensor networks has always been a challenging area. One of the basic problems of the network has been the ability of the nodes to effectively schedule the sleep and wake-up time to overcome this problem. The motivation behind node sleep or wake-up time scheduling is to take care of nodes in sleep mode for as long as possible (without losing data packet transfer efficiency) and thus extend their useful life. This research going to propose scheduling of nodes sleeps and wake-up time through reinforcement learning. This research is not based on the nodes' duty cycle strategy (which creates a compromise between data packet delivery and nodes energy saving delay) like other existing researches. It is based on the research of reinforcement learning which gives independence to each node to choose its own activity from the transmission of packets, tuning or sleep node in each time band which works in a decentralized way. The simulation results show the qualified performance of the proposed algorithm under different conditions.

scholarly journals Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Santosh Soni ◽  
Manish Shrivastava
Keyword(s):  
Reinforcement Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Research Study ◽  
Hot Spot ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Hot Spot Problem

Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data. Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes. This problem is known as hot spot problem in wireless sensor network. In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network. The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power. In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads. Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly. These algorithms did not create the extra overhead on mobile sink and save the energy as well. Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.

scholarly journals Defending Against Denial of Sleep Attack in Wireless Sensor Network

2013 ◽  
Vol 9 (2) ◽  
pp. 1063-1067
Author(s):  
Manju Vc ◽  
Dr.Sasi Kumar.
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sleep Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Sleep Mode ◽  
Replay Attack ◽  
Jamming Attacks ◽  
Sleep Attack

A wireless sensor network is a wireless network organized with a large number of sensor nodes with specialized sensors that can monitor various physical attributes such as temperature, pressure, vibration, and sound. Sensor nodes are powered up with batteries. Due to unattended nature of the deployment, the sensor nodes’ batteries cannot be recharged. In such conditions, the nodes must optimally consume power. Various protocols are designed to reduce the energy consumption of sensor nodes by keeping the antenna in sleep mode 90% of time, so that power is saved. MAC protocols are designed to adaptively vary the sleep time based on the communication need. But attackers use their knowledge of their underlying MAC protocol, to reduce the sleep time for the node, so that the lifetime of a node reduces. This problem is popularly known as Denial of sleep attack. In this paper, we propose an effective solution }to defend against such attacks in  a sensor network. Our proposed solution introduces communication overhead only when the attack is suspected and also the defending mechanism is triggered only in the area of attack. Also the analysis shows that our solution is very strong against SYNC replay attack and jamming attacks.

scholarly journals Energy efficient chaotic whale optimization technique for data gathering in wireless sensor network

2020 ◽  
Vol 10 (4) ◽  
pp. 4176
Author(s):  
Sridhar R. ◽  
N. Guruprasad
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Packet Loss ◽  
Energy Efficient ◽  
Data Gathering ◽  
Data Packet ◽  
Sensor Nodes ◽  
Wireless Sensor

A Wireless Sensor Network includes the distributed sensor nodes using limited energy, to monitor the physical environments and forward to the sink node. Energy is the major resource in WSN for increasing the network lifetime. Several works have been done in this field but the energy efficient data gathering is still not improved. In order to amend the data gathering with minimal energy consumption, an efficient technique called chaotic whale metaheuristic energy optimized data gathering (CWMEODG) is introduced. The mathematical model called Chaotic tent map is applied to the parameters used in the CWMEODG technique for finding the global optimum solution and fast convergence rate. Simulation of the proposed CWMEODG technique is performed with different parameters such as energy consumption, data packet delivery ratio, data packet loss ratio and delay with deference to dedicated quantity of sensor nodes and number of packets. The consequences discussion shows that the CWMEODG technique progresses the data gathering and network lifetime with minimum delay as well as packet loss than the state-of-the-art methods.

scholarly journals Security from Denial of Sleep Attack in Wireless Sensor Network

2005 ◽  
Vol 4 (2) ◽  
pp. 419-425 ◽  
Author(s):  
Simerpreet Kaur ◽  
Md. Ataullah ◽  
Monika Garg
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Physical World ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Sleep Attack ◽  
Energy Constrained

With the advancement in Wireless Sensor Network (WSN) sensors are gaining importance in the physical world. Besides the low power of sensor nodes used, sensors are widely used in detecting temperature, pollution, pressure and other various applications. Energy-constrained sensor networks periodically place nodes to sleep in order to extend the network Lifetime. Denial of sleep attacks are a great threat to lifetime of sensor networks as it prevents the nodes from going into sleep mode. In this paper we are describing prevention against Denials of sleep attack. We have analyzed each of proposed solutions, identify their strengths and limitations.

An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network

2020 ◽  
Vol 13 (8) ◽  
pp. 1166-1174
Author(s):  
Chao Wang
Keyword(s):  
Wireless Sensor Network ◽  
Congestion Control ◽  
Sensor Network ◽  
Traffic Assignment ◽  
Transmission Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Detection ◽  
Detection Technology ◽  
Average Transmission

Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure the data in the congestion areas can be transferred to noncongestion areas as soon as possible. Results: The simulation results indicate that the proposed scheme can reduce the number of loss packets, improve the throughput, stabilize the average transmission rate of source node and reduce the end-to-end delay. Conclusion: : So the proposed scheme can enhance the overall performance of the network. Keywords: wireless sensor network; congestion control; congestion detection; congestion mitigation; traffic assignment; traffic reassignment.

scholarly journals A Remote Monitoring System of Logistics Carrier Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Monitoring Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Monitoring Center

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.

scholarly journals Investigating Master–Slave Architecture for Underwater Wireless Sensor Network

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3000
Author(s):  
Sadeeq Jan ◽  
Eiad Yafi ◽  
Abdul Hafeez ◽  
Hamza Waheed Khatana ◽  
Sajid Hussain ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Propagation Delay ◽  
Data Packet ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Term Survival ◽  
Limited Bandwidth ◽  
Delay Tolerant

A significant increase has been observed in the use of Underwater Wireless Sensor Networks (UWSNs) over the last few decades. However, there exist several associated challenges with UWSNs, mainly due to the nodes’ mobility, increased propagation delay, limited bandwidth, packet duplication, void holes, and Doppler/multi-path effects. To address these challenges, we propose a protocol named “An Efficient Routing Protocol based on Master–Slave Architecture for Underwater Wireless Sensor Network (ERPMSA-UWSN)” that significantly contributes to optimizing energy consumption and data packet’s long-term survival. We adopt an innovative approach based on the master–slave architecture, which results in limiting the forwarders of the data packet by restricting the transmission through master nodes only. In this protocol, we suppress nodes from data packet reception except the master nodes. We perform extensive simulation and demonstrate that our proposed protocol is delay-tolerant and energy-efficient. We achieve an improvement of 13% on energy tax and 4.8% on Packet Delivery Ratio (PDR), over the state-of-the-art protocol.

Handling Failures of Static Sensor Nodes in Wireless Sensor Network by Use of Mobile Sensors

2011 ◽  
Author(s):  
Edison Pignaton de Freitas ◽  
Tales Heimfarth ◽  
Ivayr Farah Netto ◽  
Carlos Eduardo Pereira ◽  
Armando Morado Ferreira ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Mobile Sensors ◽  
Wireless Sensor
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