scholarly journals Spectrum Aware Cluster Formation Scheme for Cognitive Radio Sensor Network

2018 ◽  
Vol 7 (3.15) ◽  
pp. 105
Author(s):  
Noorhayati Mohamed Noor ◽  
Norashidah Md Din ◽  
Zolidah Kasiran
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Sensor Network ◽  
Network Lifetime ◽  
Sensor Node ◽  
Cluster Formation ◽  
Common Channel ◽  
Cognitive Radio Sensor Network ◽  
Robust Cluster

In Cognitive Radio Sensor Network (CRSN), a cognitive radio sensor node operated on a dynamic spectrum allocation with limited computational and energy resource. A cognitive radio sensor node must vacate an occupied channel degrading its performance due to reclustering as the common channel no longer available. Furthermore, energy is mostly consumed during data transmission mechanism. Clustering is the best architecture model to minimize energy consumption among the nodes. With the objective of a robust cluster while maximizing network lifetime, a fuzzy logic technique is proposed. A metric named relative common channel is also proposed. The fuzzy logic combines two input parameters, the relative common channel and residual energy to elect the best suitable cluster head to minimize reclustering and maximize the network lifetime. The performance of the proposed algorithm is compared with LEACH, SAFCA and CogLEACH. The results show that the CRSN has more extended network lifetime and more balanced energy consumption attributed to the robust cluster formation. 

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

SPECTRUM AWARE CLUSTERING ALGORITHM BASED ON FUZZY LOGIC FOR COGNITIVE RADIO SENSOR NETWORK

2020 ◽  
Vol 5 (1) ◽  
pp. 433
Author(s):  
Noorhayati Mohamed Noor ◽  
Norashidah Md Din ◽  
Shapina Abdullah ◽  
Nor Azimah Khalid ◽  
Zolidah Kasiran
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Radio ◽  
Clustering Algorithm ◽  
Cluster Formation ◽  
Data Gathering ◽  
Residual Energy ◽  
Cognitive Radio Sensor Network ◽  
Distribution Parameters ◽  
The Stability ◽  
Channel Availability

In this paper, a clustering solution for periodic data gathering over WSNs using cognitive radio technology is proposed. The cluster heads (CHs) are selected according to the channel availability, residual energy, communication cost and node distribution parameters. Fuzzy logic and weight based techniques combines the four parameters for the CH selection. The cluster formation is based on the relative channel availability between the cluster member (CM) and CH to ensure stable cluster connectivity from link failure. To evaluate the proposed clustering algorithm, the performance of sensor networks is compared with CogLEACH, LEACH and CHEF routing protocols. The simulation results show that the proposed clustering algorithm effectively has a significant improvement with respect to the network stability without reducing the network instability and network lifetime. In addition, the proposed clustering solution also has a low and almost consistent CH energy consumption during the stability period indicating an efficient cluster formation.

scholarly journals Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2997
Author(s):  
Md. Tahidul Islam ◽  
Sithamparanathan Kandeepan ◽  
Robin. J. Evans
Keyword(s):  
Cognitive Radio ◽  
Sensor Network ◽  
Dynamic Network ◽  
Optimal Number ◽  
Matlab Simulation ◽  
Cognitive Radio Sensor Network ◽  
Rendezvous Technique ◽  
Central Controller ◽  
Blind Rendezvous ◽  
Analytical Expressions

In a distributed cognitive radio (CR) sensor network, transmission and reception on vacant channels require cognitive radio nodes to achieve rendezvous. Because of the lack of adequate assistance from the network environment, such as the central controller and other nodes, assisted rendezvous for distributed CR is inefficient in a dynamic network. As a result, non-assisted blind rendezvous, which is unaware of its counterpart node, has recently led to a lot of interest in the research arena. In this paper, we study a channel rendezvous method based on prime number theory and propose a new multi-radio-based technique for non-assisted rendezvous with the blind and heterogeneous condition. The required time and the optimal number of radios for the guaranteed rendezvous are calculated using probability-based measurement. Analytical expressions for probabilistic guaranteed rendezvous conditions are derived and verified by Monte Carlo simulation. In addition, the maximum time to rendezvous (MTTR) is derived in closed form using statistical and probabilistic analysis. Under different channel conditions, our proposed solution leads to a substantial time reduction for guaranteed rendezvous. For the sake of over-performance of our proposed system, the simulation outcome is compared to a recently proposed heterogeneous and blind rendezvous method. The Matlab simulation results show that our proposed system’s MTTR gains range from 11% to over 95% for various parametric values of the system model.

An Energy Efficient Estimation Algorithm for Wireless Sensor Network

2011 ◽  
Vol 216 ◽  
pp. 176-180
Author(s):  
Yong Ding ◽  
Yue Mei Su
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Estimation Algorithm ◽  
Efficient Estimation ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Current Energy

Wireless Sensor Networks functionality is closely related to network lifetime which depends on the energy consumption, so require energy- efficient protocols to improve the network lifetime. According to the analysis and summary of the current energy efficient estimation algorithms in wireless sensor network An energy-efficient algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional diffusion routing protocol. Simulation results show that this algorithm is to effectively balance the network energy consumption, improve the network life-cycle and ensure the communication quality.

Type 2 Fuzzy Logic based Unequal Clustering algorithm for multi-hop wireless sensor networks

2020 ◽  
pp. 33-46
Author(s):  
A. Sariga ◽  
◽  
◽  
J. Uthayakumar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Clustering Protocols ◽  
Hot Spot Problem

Wireless sensor network (WSN) is an integral part of IoT and Maximizing the network lifetime is a challenging task. Clustering is the most popular energy efficient technique which leads to increased lifetime stability and reduced energy consumption. Though clustering offers several advantages, it eventually raises the burden of CHs located in proximity to the Base Station (BS) in multi-hop data transmission which makes the CHs near BS die earlier than other CHs. This issue is termed as hot spot problem and unequal clustering protocols were introduced to handle it. Presently, some of the clustering protocols are developed using Type-2 Fuzzy Logic (T2FL) but none of them addresses hot spot problem. This paper presents a Type-2 Fuzzy Logic based Unequal Clustering Algorithm (T2FLUCA) for the elimination of hot spot problem and also for lifetime maximization of WSN. The proposed algorithm uses residual energy, distance to BS and node degree as input to T2FL to determine the probability of becoming CHs (PCH) and cluster size. For experimentation, T2FLUCA is tested on three different scenarios and the obtained results are compared with LEACH, TEEN, DEEC and EAUCF in terms of network lifetime, throughput and average energy consumption. The experimental results ensure that T2FLUCA outperforms state of art methods in a significant way.

Cognitive Radio Sensor Networks

2014 ◽  
pp. 160-195 ◽  
Author(s):  
Ejaz Ahmed ◽  
Salman Ali ◽  
Adnan Akhunzada ◽  
Ibrar Yaqoob
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Sensor Network ◽  
Ad Hoc ◽  
Network Communication ◽  
Ad Hoc Routing ◽  
Medium Access ◽  
Cognitive Radio Sensor Networks ◽  
Cognitive Radio Sensor Network ◽  
Network Operation

This chapter provides a review of design practices in network communication for Cognitive Radio Sensor Networks. The basics of networking and Medium Access Control functionalities with focus on data routing and spectrum usage are discussed. Technical differences manifest in various network layouts, hence the role of various specialized nodes, such as relay, aggregator, or gateway in Cognitive Radio Sensor Networks need analysis. Optimal routing techniques suitable for different topologies are also summarized. Data delivery protocols are categorized under priority-based, energy-efficient, ad hoc routing-based, attribute-based, and location-aware routing. Broadcast, unicast, and detection of silence periods are discussed for network operation with slotted or unslotted time. Efficient spectrum usage finds the most important application here involving use of dynamic, opportunistic, and fixed spectrum usage. Finally, a thorough discussion on the open issues and challenges for Cognitive Radio Sensor Network communication and internetworking in Cognitive Radio Sensor Network-based deployments and methods to address them are provided.

Power Layer Energy Efficient Routing Protocol in Wireless Sensor Network (PLRP)

2013 ◽  
Vol 5 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Sardjoeni Moedjiono ◽  
Aries Kusdaryono
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Sensor Node ◽  
Base Station ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Energy Efficient Routing

Preserving energy of sensor node in wireless sensor network is an effort to prolong the lifetime of network. Energy of sensor node is very crucial because battery powered and irreplaceable. Energy conservation of sensor node is an effort to reduce energy consumption in order to preserve resource for network lifetime. It can be achieved through efficient energy usage by reducing consumption of energy or decrease energy usage while achieving a similar outcome. In this paper, the authors propose power layer energy efficient routing protocol in wireless sensor network, named PLRP, which use power control and multi-hop routing protocol to control overhead of sensor node and create clustering to distribute energy dissipation and increase energy efficiency of all sensor node. The main idea of PLRP is the use of power control, which divide sensor node into group by base station uses layer of energy and maximize the computation energy in base station to reduce computational energy in sensor node for conservation of network lifetime. The performance of PLRP compared to BCDCP and BIDRP based of hierarchical routing protocol. The simulation results show that PLRP achieve 25% and 30% of improvement on network lifetime.

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