Unifying of frequency channel for spectrum sharing in wireless sensor networks with star topology

2015 ◽  
Author(s):  
Takumi Kimura ◽  
Osamu Takyu ◽  
Fumihito Sasamori ◽  
Shiro Handa
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spectrum Sharing ◽  
Wireless Sensor ◽  
Frequency Channel ◽  
Star Topology

A Neural-Q-Learning Based Approach for Delay Tolerant Underwater Acoustic Wireless Sensor Networks

2014 ◽  
Vol 548-549 ◽  
pp. 1530-1535
Author(s):  
Lin Zou ◽  
De Feng Huang ◽  
Roberto Togneri
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Learning Algorithm ◽  
Wireless Sensor ◽  
Underwater Acoustic Communications ◽  
Frequency Channel ◽  
Underwater Acoustic ◽  
Continuous Space ◽  
Q Learning ◽  
Delay Tolerant

Delay tolerance is a major design concern for supporting underwater acoustic wireless sensor networks (UA-WSNs) to carry out tasks in harsh subsea environments. Due to the great difference between the underwater acoustic channel and the radio frequency channel, most of the existing routing protocols developed for terrestrial wireless sensor networks perform poorly in underwater acoustic communications. In this work, we present a Neural-Q-Learning algorithm based delay tolerant protocol for UA-WSNs. Due to the advantages of the artificial neural network along with the Q-Learning algorithm, the ferry node is capable of determining an optimal route in a two-dimensional continuous space to relay packets effectively and efficiently between sensors. Simulation results show that the delivery delay and delivery cost of the network significantly decrease by maximizing the meeting probability between the ferry node and sensors.

scholarly journals Energy Reckoning Distance Based Clustering for Spectrum Aware Cognitive Radio Wireless Sensor Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 842-850
Keyword(s):  
Wireless Sensor Networks ◽  
Cognitive Radio ◽  
Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Spectrum Sharing ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cognitive Radio Sensor Network

Implementing cognitive radio sensor nodes in wireless sensor networks introduced a smart combination called cognitive radio sensor network (CRSN) which creates new challenges in the design of network topology. Conserving the nodes energy helps to extend the lifetime of the network. This stands as an important criterion while designing any algorithm. In order to achieve the same, two important criteria are to be considered – the communicating distance between the nodes or node to base station and proper spectrum sharing technique. In the proposed work, Energy Reckoning Distance-Based Clustering (ERDBC) algorithm, both the criterion is taken into consideration and designed in order to increase the lifetime of a cognitive radio sensor network. In the ERDBC algorithm, the whole network area is divided into three regions according to the distance and the cluster heads are elected based on energy, distance and common channel creates a greater impact on retaining the nodes energy. Also, implementing multi-hop routing using proper spectrum sharing technique helps to avoid data collision and retransmission thereby; the energy consumption of the nodes are reduced to a greater extent. The performance of the proposed ERDBC algorithm is measured on the basis of residual energy, throughput, channel usage, first node death, last node death, and network lifetime, and compared with the already existing LEACH, CogLEACH, LEAUCH and CEED algorithms. Thus the network lifetime of the proposed ERDBC algorithm is 78.18% more than LEACH, 73.6% more than CogLEACH, 29.88% more than CEED and 17.98% more than LEAUCH algorithms

NACRP: A Connectivity Protocol for Star Topology Wireless Sensor Networks

2016 ◽  
Vol 5 (2) ◽  
pp. 120-123 ◽  
Author(s):  
Leonardo Goratti ◽  
Tuncer Baykas ◽  
Tinku Rasheed ◽  
Shuzo Kato
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Star Topology
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