scholarly journals Comparative study between metaheuristic algorithms for internet of things wireless nodes localization

Author(s):  
Rana Jassim Mohammed ◽  
Enas Abbas Abed ◽  
Mostafa Mahmoud El-gayar

<p>Wireless networks are currently used in a wide range of healthcare, military, or environmental applications. Wireless networks contain many nodes and sensors that have many limitations, including limited power, limited processing, and narrow range. Therefore, determining the coordinates of the location of a node of the unknown location at a low cost and a limited treatment is one of the most important challenges facing this field. There are many meta-heuristic algorithms that help in identifying unknown nodes for some known nodes. In this manuscript, hybrid metaheuristic optimization algorithms such as grey wolf optimization and salp swarm algorithm are used to solve localization problem of internet of things (IoT) sensors. Several experiments are conducted on every meta-heuristic optimization algorithm to compare them with the proposed method. The proposed algorithm achieved high accuracy with low error rate (0.001) and low power <br />consumption.</p>

2020 ◽  
Vol 14 (4) ◽  
pp. 113-133
Author(s):  
Mary Shamala L. ◽  
Zayaraz G. ◽  
Vivekanandan K. ◽  
Vijayalakshmi V.

Internet of things (IoT) is a global network of uniquely addressable interconnected things, based on standard communication protocols. As the number of devices connected to the IoT escalates, they are becoming a likely target for hackers. Also, the limited resources of IoT devices makes the security on top of the actual functionality of the device. Therefore, the cryptographic algorithm for such devices has to be devised as small as possible. To tackle the resource constrained nature of IoT devices, this article presents a lightweight cryptography algorithm based on a single permutation and iterated Even-Mansour construction. The proposed algorithm is implemented in low cost microcontrollers, thus making it suitable for a wide range of IoT nodes.


2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988990
Author(s):  
Farooq Aftab ◽  
Ali Khan ◽  
Zhongshan Zhang

Recent technological improvements have revolutionized the wireless sensor network–based industrial sector with the emergence of Internet of Things. Internet of Drones, a branch of Internet of Things, is used for the communication among drones. As drones are mobile in nature, they cause frequent topological changes. This changing topology causes scalability, stability, and route selection issues in Internet of Drones. To handle these issues, we propose a bio-inspired clustering scheme using dragonfly algorithm for cluster formation and management. In this article, we propose cluster head election based on the connectivity with the base station along with the fitness function which consists of residual energy and position of the drones. Furthermore, for route selection we propose an optimal path selection based on the residual energy and position of drone for efficient communication. The proposed scheme shows better results as compared to other bio-inspired clustering algorithms on the basis of evaluation benchmarks such as cluster building time, network energy consumption, cluster lifetime, and probability of successful delivery. The results indicate that the proposed scheme has improved 60% and 38% with respect to ant colony optimization and grey wolf optimization, respectively, in terms of average cluster building time while average energy consumption has improved 23% and 33% when compared to the ant colony optimization and grey wolf optimization, respectively.


2021 ◽  
Vol 20 (Number 2) ◽  
pp. 213-248
Author(s):  
Narender Kumar ◽  
Dharmender Kumar

Grey wolf optimization (GWO) is a recent and popular swarm-based metaheuristic approach. It has been used in numerous fields such as numerical optimization, engineering problems, and machine learning. The different variants of GWO have been developed in the last 5 years for solving optimization problems in diverse fields. Like other metaheuristic algorithms, GWO also suffers from local optima and slow convergence problems, resulted in degraded performance. An adequate equilibrium among exploration and exploitation is a key factor to the success of meta-heuristic algorithms especially for optimization task. In this paper, a new variant of GWO, called inertia motivated GWO (IMGWO) is proposed. The aim of IMGWO is to establish better balance between exploration and exploitation. Traditionally, artificial neural network (ANN) with backpropagation (BP) depends on initial values and in turn, attains poor convergence. The metaheuristic approaches are better alternative instead of BP. The proposed IMGWO is used to train the ANN to prove its competency in terms of prediction. The proposed IMGWO-ANN is used for medical diagnosis task. Some benchmark medical datasets including heart disease, breast cancer, hepatitis, and parkinson's diseases are used for assessing the performance of IMGWO-ANN. The performance measures are described in terms of mean squared errors (MSEs), classification accuracies, sensitivities, specificities, the area under the curve (AUC), and receiver operating characteristic (ROC) curve. It is found that IMGWO outperforms than three popular metaheuristic approaches including GWO, genetic algorithm (GA), and particle swarm optimization (PSO). Results confirmed the potency of IMGWO as a viable learning technique for an ANN.


2019 ◽  
Vol 29 (07) ◽  
pp. 2050111
Author(s):  
Basma H. Mohamed ◽  
Ahmed Taha ◽  
Ahmed Shawky ◽  
Essraa Ahmed ◽  
Ali Mohamed ◽  
...  

With the new age of technology and the release of the Internet of Things (IoT) revolution, there is a need to connect a wide range of devices with varying throughput and performance requirements. In this paper, a digital transmitter of NarrowBand Internet of Things (NB-IoT) is proposed targeting very low power and delay-insensitive IoT applications with low throughput requirements. NB-IoT is a new cellular technology introduced by 3GPP in release 13 to provide wide-area coverage for the IoT. The low-cost receivers for such devices should have very low complexity, consume low power and hence run for several years. In this paper, the implementation of the data path chain of digital uplink transmitter is presented. The standard specifications are studied carefully to determine the required design parameters for each block. And the design is synthesized in UMC 130-nm technology.


Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 730 ◽  
Author(s):  
Li Sun ◽  
Qinghe Du

With the uninterrupted revolution of communications technologies and the great-leap-forward development of emerging applications, the ubiquitous deployment of Internet of Things (IoT) is imperative to accommodate constantly growing user demands and market scales. Communication security is critically important for the operations of IoT. Among the communication security provisioning techniques, physical layer security (PLS), which can provide unbreakable, provable, and quantifiable secrecy from an information-theoretical point of view, has drawn considerable attention from both the academia and the industries. However, the unique features of IoT, such as low-cost, wide-range coverage, massive connection, and diversified services, impose great challenges for the PLS protocol design in IoT. In this article, we present a comprehensive review of the PLS techniques toward IoT applications. The basic principle of PLS is first briefly introduced, followed by the survey of the existing PLS techniques. Afterwards, the characteristics of IoT are identified, based on which the challenges faced by PLS protocol design are summarized. Then, three newly-proposed PLS solutions are highlighted, which match the features of IoT well and are expected to be applied in the near future. Finally, we conclude the paper and point out some further research directions.


Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3626 ◽  
Author(s):  
Imanol Picallo ◽  
Hicham Klaina ◽  
Peio Lopez-Iturri ◽  
Aitor Sánchez ◽  
Leire Méndez-Giménez ◽  
...  

The advent of the Internet of Things (IoT) has led to embedding wireless transceivers into a wide range of devices, in order to implement context-aware scenarios, in which a massive amount of transceivers is foreseen. In this framework, cost-effective electronic and Radio Frequency (RF) front-end integration is desirable, in order to enable straightforward inclusion of communication capabilities within objects and devices in general. In this work, flexible antenna prototypes, based on screen-printing techniques, with conductive inks on flexible low-cost plastic substrates is proposed. Different parameters such as substrate/ink characteristics are considered, as well as variations in fabrication process or substrate angular deflection in device performance. Simulation and measurement results are presented, as well as system validation results in a real test environment in wireless sensor network communications. The results show the feasibility of using screen-printing antenna elements on flexible low-cost substrates, which can be embedded in a wide array of IoT scenarios.


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