scholarly journals Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yuanjiang Huang ◽  
José-Fernán Martínez ◽  
Vicente Hernández Díaz ◽  
Juana Sendra

The sensor nodes in the Wireless Sensor Networks (WSNs) are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC), of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC), of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE) through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.

In underwater Wireless Sensor Networks (UWSN) the node mobility is higher as the nodes drift with the water so identifying the exact location of the nodes is a challenging task. Terrestrial WSN use Global Positioning System (GPS) to locate the nodes, but the same cannot be applied for UWSN as they do not propagate under water. Underwater uses acoustic channel for communication which suffers from low bandwidth, high propagation delay, high bit error rate, high node mobility and variable sound speed which makes localization a challenging task. Hence there is an evolving requirement for energy efficient localization algorithm. To overcome these problems we propose an Energy Efficient Cluster Based Localization Algorithm (EECBLA) to minimize the energy utilization and identify an accurate location of the sensor nodes. EECBLA is a cluster based localization protocol where the GPS enabled high power anchor nodes are utilized to estimate the location of the un localized sensor nodes. To improve the localization accuracy it is necessary to improve the network connectivity. Network connectivity can be improved by increasing the lifetime of the sensor nodes. EECBLA proposes an energy efficient localization scheme where the node operates in active and sleep mode to efficiently utilize the available energy. In this research work we take a sample example and demonstrate how the location is estimated through TOA and Euclidean distance. Accuracy of TOA is measured as 8.36, 4.76, 13.21, 14.85, 16.26 and 3.60. The average estimated localization error of EECBLA is around 4m to 6m. EECBLA localization error is compared with other localization algorithms like 3DUL whose average localization error is 5m to 10m, SDMA whose average localization error is around 24% and localization error of Hybrid RSS ranges from 4.69m to 15.85m. When compared with these methodologies there is a decrease in localization error by 3%, and the increase in accuracy by 5% in EECBLA protocol


Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 561 ◽  
Author(s):  
Abdulmughni Hamzah ◽  
Mohammad Shurman ◽  
Omar Al-Jarrah ◽  
Eyad Taqieddin

In wireless sensor networks, the energy source is limited to the capacity of the sensor node’s battery. Clustering in WSN can help with reducing energy consumption because transmission energy is related to the distance between sender and receiver. In this paper, we propose a fuzzy logic model for cluster head election. The proposed model uses five descriptors to determine the opportunity for each node to become a CH. These descriptors are: residual energy, location suitability, density, compacting, and distance from the base station. We use this fuzzy logic model in proposing the Fuzzy Logic-based Energy-Efficient Clustering for WSN based on minimum separation Distance enforcement between CHs (FL-EEC/D). Furthermore, we adopt the Gini index to measure the clustering algorithms’ energy efficiency in terms of their ability to balance the distribution of energy through WSN sensor nodes. We compare the proposed technique FL-EEC/D with a fuzzy logic-based CH election approach, a k-means based clustering technique, and LEACH. Simulation results show enhancements in energy efficiency in terms of network lifetime and energy consumption balancing between sensor nodes for different network sizes and topologies. Results show an average improvement in terms of first node dead and half nodes dead.


Author(s):  
A. Radhika ◽  
D. Haritha

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.


2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Khalid Mahmood ◽  
Muhammad Amir Khan ◽  
Mahmood ul Hassan ◽  
Ansar Munir Shah ◽  
Shahzad Ali ◽  
...  

Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on-demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the sensor nodes.


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


2014 ◽  
Vol 573 ◽  
pp. 407-411
Author(s):  
Chelliah Pandeeswaran ◽  
Natrajan Papa ◽  
Sundar G. Jayesh

MAC protocol design in Wireless sensor networks becomes vibrant research field for the past several years. In this paper an EE-Hybrid MAC protocol (Energy efficient hybrid Medium Access Control) has been proposed, which is energy efficient and low latency MAC protocol, which uses interrupt method to assign priority for certain wireless sensor nodes assumed to be present in critical loops of industrial process control domain. EE-Hybrid MAC overcomes some of the limitations in the existing approaches. Industrial wireless sensor network require a suitable MAC protocol which offers energy efficiency and capable of handling emergency situations in industrial automation domain. Time critical and mission critical applications demands not only energy efficiency but strict timeliness and reliability. Harsh environmental condition and dynamic network topologies may cause industrial sensor to malfunction, so the developed protocol must adapt to changing topology and harsh environment. Most of the existing MAC protocols have number of limitations for industrial application domain In industrial automation scenario, certain sensor loops are found to be time critical, where data’s have to be transferred without any further delay. The proposed EE-Hybrid MAC protocol is simulated in NS2 environment, from the result it is observed that proposed protocol provides better performance compared to the conventional MAC protocols.


Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.


Sign in / Sign up

Export Citation Format

Share Document