An Improved Group Teaching Optimization based Localization Scheme for WSN

2021 ◽  
pp. 08-16
Author(s):  
Rabie A. Ramadan ◽  
Keyword(s):  
Hill Climbing ◽  
Wireless Sensor ◽  
Present Position ◽  
Node Localization ◽  
Dense Networks ◽  
Current State ◽  
Localization Scheme ◽  
Np Hard Problem ◽  
Node Count ◽  
State Of Art

Localization is widely employed in wireless sensor networks (WSN) to detect the present position of the nodes. Generally, WSN comprises numerous sensors, which makes the deployment of GPS in all nodes cost and fails to provide precise localization outcomes in several cases. The manual configuration of the position reference of the sensors is not feasible under dense networks. Therefore, the NL process can be treated as an NP-hard problem and solved by metaheuristic algorithms. In this aspect, this paper presents an improved group teaching optimization algorithm-based NL technique called IGTOA-NL for WSN. The IGTOA technique is derived by integrating the basic concepts of GTOA with the β-hill-climbing technique to improve the overall node localization process. The IGTOA-NL technique can effectually localize the nodes in WSN under varying anchor node count. To showcase the productive outcome of the IGTOA technique, a series of simulations take place under a diverse number of anchors. The resultant values highlighted the proficient NL outcome of the IGTOA technique over the current state of art NL techniques in terms of different measures.

scholarly journals A 3D node localization scheme for wireless sensor networks

2009 ◽  
Vol 6 (3) ◽  
pp. 167-172 ◽  
Author(s):  
Q. Shi ◽  
H. Huo ◽  
T. Fang ◽  
D. Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Node Localization ◽  
Localization Scheme

Solving the k-Coverage and m-Connected Problem in Wireless Sensor Networks through the Imperialist Competitive Algorithm

2020 ◽  
Vol 20 (01) ◽  
pp. 2050002
Author(s):  
HEMMAT SHEIKHI ◽  
WAFA BARKHODA
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Mathematical Formulation ◽  
Imperialist Competitive Algorithm ◽  
Wireless Sensor ◽  
Placement Problem ◽  
Competitive Algorithm ◽  
Np Hard Problem ◽  
Node Count

This study presents a new method based on the imperialist competitive algorithm (ICA-based) to solve the k-coverage and m-connected problem in wireless sensor networks (WSNs) through the least sensor node count, where the candidate positions for placing nodes are pre-specified. This dual featured problem in WSNs is a nondeterministic polynomial (NP)-hard problem therefore, ICA the social-inspired evolutionary algorithm is assessed and ICA-based scheme is designed to solve the problem. This newly proposed ICA-based scheme provides an efficient algorithm for representing the imperialistic competition among some of the best solutions to the problem in order to decrease the network cost. The mathematical formulation is presented for the node placement problem. The main issue of concern here is the deployed sensor node count. The simulation results confirm that ICA-based method can reduce the required sensor node count unlike other genetic-based and biogeography-based evolutionary algorithms. The experimental results are presented for WSN_Random and WSN_Grid scenarios.

scholarly journals Salp Swarm Algorithm for Node Localization in Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Huthaifa M. Kanoosh ◽  
Essam Halim Houssein ◽  
Mazen M. Selim
Keyword(s):  
Computing Time ◽  
Wireless Sensor ◽  
Grey Wolf Optimizer ◽  
Localization Algorithm ◽  
Node Localization ◽  
Localization Accuracy ◽  
Salp Swarm Algorithm ◽  
Localization Scheme ◽  
Swarm Algorithm ◽  
Better Than

Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of known nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization scheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is compared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm (BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. The simulation results show that the proposed localization algorithm is better than the other algorithms in terms of mean localization error, computing time, and the number of localized nodes.

SecRET

2021 ◽  
Vol 15 (1) ◽  
pp. 1-26
Author(s):  
Sudip Misra ◽  
Tamoghna Ojha ◽  
Madhusoodhanan P
Keyword(s):  
Sensor Networks ◽  
Error Rates ◽  
Location Information ◽  
Underwater Sensor Networks ◽  
Node Localization ◽  
Limited Bandwidth ◽  
Secure Localization ◽  
Localization Scheme ◽  
Monitoring Application ◽  
Fundamental Requirement

Node localization is a fundamental requirement in underwater sensor networks (UWSNs) due to the ineptness of GPS and other terrestrial localization techniques in the underwater environment. In any UWSN monitoring application, the sensed information produces a better result when it is tagged with location information. However, the deployed nodes in UWSNs are vulnerable to many attacks, and hence, can be compromised by interested parties to generate incorrect location information. Consequently, using the existing localization schemes, the deployed nodes are unable to autonomously estimate the precise location information. In this regard, similar existing schemes for terrestrial wireless sensor networks are not applicable to UWSNs due to its inherent mobility, limited bandwidth availability, strict energy constraints, and high bit-error rates. In this article, we propose SecRET , a <underline>Sec</underline>ure <underline>R</underline>ange-based localization scheme empowered by <underline>E</underline>vidence <underline>T</underline>heory for UWSNs. With trust-based computations, the proposed scheme, SecRET , enables the unlocalized nodes to select the most reliable set of anchors with low resource consumption. Thus, the proposed scheme is adaptive to many attacks in UWSN environment. NS-3 based performance evaluation indicates that SecRET maintains energy-efficiency of the deployed nodes while ensuring efficient and secure localization, despite the presence of compromised nodes under various attacks.

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