scholarly journals Design of an Energy Efficient Cluster based Localization Algorithm (EECBLA) for Underwater Wireless Sensor Networks

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

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 498 ◽  
Author(s):  
Sahar Shah ◽  
Anwar Khan ◽  
Ihsan Ali ◽  
Kwang-Man Ko ◽  
Hasan Mahmood

Mitigation of channel unfavorable circumstances during data routing in underwater wireless sensor networks (UWSNs) has utmost significance. It guarantees saving packet corruption along unfavorable channels so that vital data is not lost or become meaningless. This paper proposes two routing protocols for UWSNs: localization free energy efficient routing (LFEER) and its improved version, localization free energy efficient cooperative routing (Co-LFEER). The LFEER makes decision of choosing a relay based on its maximum residual energy, number of hops and the bit error rate of the link over which packets are transmitted. These metrics are chosen to save packets from corruption to the maximum limit and maintain stable paths (where nodes do not die soon). Since a single link is used in the LFEER for packets forwarding, the link may become worse with changing circumstances of the channel. To deal with this issue, cooperative routing is added to the LFFER to construct the Co-LFEER protocol, in which some copies of packets are received by destination to decide about packets quality. Converse to some prevalent protocols, both LFEER and Co-LFEER are independent of knowing the sensor nodes’ positions, which increases computational complexity and wasteful utilization of resources. Based on extensive simulations, the proposed schemes are better than Co-DBR in reducing energy utilization and advancing packets to the desired destination.


2012 ◽  
Vol 8 (4) ◽  
pp. 307246 ◽  
Author(s):  
Abdul Wahid ◽  
Dongkyun Kim

Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention from both academia and industry, in order to explore the vast underwater environment. UWSNs have peculiar characteristics; that is, they have large propagation delay, high error rate, low bandwidth, and limited energy. Therefore, designing network/routing protocols for UWSNs is very challenging. Also, in UWSNs, improving the energy efficiency is one of the most important issues since the replacement of the batteries of underwater sensor nodes is very expensive due to the unpleasant underwater environment. In this paper, we therefore propose an energy efficient routing protocol, named (energy-efficient depth-based routing protocol) EEDBR for UWSNs. EEDBR utilizes the depth of sensor nodes for forwarding data packets. Furthermore, the residual energy of sensor nodes is also taken into account in order to improve the network lifetime. Based on the comprehensive simulation using NS2, we observe that EEDBR contributes to the performance improvements in terms of the network lifetime, energy consumption, and end-to-end delay. A previous version of this paper was accepted in AST-2011 conference.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4152
Author(s):  
Sana Messous ◽  
Hend Liouane ◽  
Omar Cheikhrouhou ◽  
Habib Hamam

As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature. There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes. One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop). Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper. The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation. Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation. Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.


2011 ◽  
Vol 8 (1) ◽  
pp. 260302 ◽  
Author(s):  
Kezhong Lu ◽  
Xiaohua Xiang ◽  
Dian Zhang ◽  
Rui Mao ◽  
Yuhong Feng

Many applications and protocols in wireless sensor networks need to know the locations of sensor nodes. A low-cost method to localize sensor nodes is to use received signal strength indication (RSSI) ranging technique together with the least-squares trilateration. However, the average localization error of this method is large due to the large ranging error of RSSI ranging technique. To reduce the average localization error, we propose a localization algorithm based on maximum a posteriori. This algorithm uses the Baye's formula to deduce the probability density of each sensor node's distribution in the target region from RSSI values. Then, each sensor node takes the point with the maximum probability density as its estimated location. Through simulation studies, we show that this algorithm outperforms the least-squares trilateration with respect to the average localization error.


2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771718 ◽  
Author(s):  
Arshad Sher ◽  
Nadeem Javaid ◽  
Irfan Azam ◽  
Hira Ahmad ◽  
Wadood Abdul ◽  
...  

In this article, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks. First one is sparsity-aware energy-efficient clustering, second one is circular sparsity-aware energy-efficient clustering, and the third one is circular depth–based sparsity-aware energy-efficient clustering routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions, whereas sparsity search algorithm is proposed to find sparse regions and density search algorithm is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet, while sink mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold [Formula: see text] value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counter-part schemes (depth-based routing and energy-efficient depth-based routing) in terms of energy efficiency.


2021 ◽  
Author(s):  
Hend Liouane ◽  
Sana Messous ◽  
Omar Cheikhrouhou

Abstract Multi-hop localization is a an important technique for Wireless Sensor Networks. Location awareness is very crucial for almost existing sensor network applications. However, using Global Positioning System (GPS) receivers to every node is very expensive. Therefore, the Distance Vector-Hop algorithm (DV-Hop) is proposed and very famous for its simplicity and localization accuracy for Wireless Sensor Networks. The cited algorithm uses a small number of anchor nodes, which are equipped with GPS, thus their locations are known, while other nodes estimate their location from the network connectivity information. However, DV-Hop presents some deficiencies and drawbacks in terms of localization accuracy. Therefore, we propose in this paper an improvement of DV-Hop algorithm, called Regularized Least Square DV-Hop Localization Algorithm for multihop wireless sensors networks. The proposed solution improves the location accuracy of sensor nodes within their sensing field in both isotropic and anisotropic networks. Simulation results prove that the proposed algorithm outperforms the original DV-Hop algorithm with up to 60%, as well as other related works, in terms of localization accuracy.


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.


2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Nadeem Javaid ◽  
Hammad Maqsood ◽  
Abdul Wadood ◽  
Iftikhar Azim Niaz ◽  
Ahmad Almogren ◽  
...  

Localization is one of the major aspects in underwater wireless sensor networks (UWSNs). Therefore, it is important to know the accurate position of the sensor node in large scale applications like disaster prevention, tactical surveillance, and monitoring. Due to the inefficiency of the global positioning system (GPS) in UWSN, it is very difficult to localize a node in underwater environment compared to terrestrial networks. To minimize the localization error and enhance the localization coverage of the network, two routing protocols are proposed; the first one is mobile autonomous underwater vehicle (MobiL-AUV) and the second one is cooperative MobiL (CO-MobiL). In MobiL-AUV, AUVs are deployed and equipped with GPS and act as reference nodes. These reference nodes are used to localize all the nonlocalized ordinary sensor nodes in order to reduce the localization error and maximize the network coverage. CO-MobiL is presented in order to improve the network throughput by using the maximal ratio combining (MRC) as diversity technique which combines both signals, received from the source and received from the relay at the destination. It uses amplify-and-forward (AF) mechanism to improve the signal between the source and the destination. To support our claims, extensive simulations are performed.


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.


Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.


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