Sensor node tracking using semi-supervised Hidden Markov Models

Kumar, Sudhir; Tiwari, Shriman Narayan; Hegde, Rajesh M.

doi:10.1016/j.adhoc.2015.04.004

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…They design a safe WSN routing model based-on HMM and block attacks like blackholes. Many others techniques had used hidden Markov models in WSN to improve the performance of an existing model [33,34,35,36,37] .…”

Section: Related Workmentioning

confidence: 99%

Antnet Pheromone-Based Stochastic Multipath Routing Protocols using Hidden Markov Models for Energy Enhancement in Wireless Sensor Networks

Moundounga

Satori

Sanhaji

et al. 2022

Preprint

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Evolving of Wireless Sensor Network (WSNs) a type of infrastructure-less networks by tens, hundreds, thousandths, or billions of devices that provide indispensable services for the phenomenon study become more used in many industries with many applications. Forest fire tracking, environmental monitor, healthcare, seismic and volcano surveillance, Internet of Devices and everything, and now internet of vehicles is the new trend of network of devices. These devices and things mostly exchange data between many sources and destinations using a special computer mechanism, the routing protocols to optimized the using of network and devices resource to retrieve their path.Additionally, constraints like network capabilities, storage, computational, energy consumption, and so on, many researches were conducted to proposed routing protocols that limited the network effort and the all of things’ interaction to extend the lifetime. In the present paper Antnet routing protocol which is classed in the Ant Colony Optimization heuristic is inspired on the ants behavior to define a stochastic based model permitting to predict the ants path to reach final destination using biological substance deposit on all visited paths to establish a new form of routing table that can be exploit for the purpose of the optimization objective. Conducted experimentation and obtained results show that the using of the pheromone in multiple paths by ants during trips permit to conserve effectively the available resources, reduce control overhead, residual overall, and optimize the energy consumption. Our new routing mechanism based on stochastic models performs well that compared existing routing.

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Section: Related Workmentioning

confidence: 99%

Antnet Pheromone-Based Stochastic Multipath Routing Protocols using Hidden Markov Models for Energy Enhancement in Wireless Sensor Networks

Moundounga

Satori

Sanhaji

et al. 2022

Preprint

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show abstract

“…For example, proposed mechanism [51] combined the semisupervised machine learning technique and support vector regression to find out the target nodes locations. Protocol [52] used semi-supervised hidden Markov model to solve the localization problem for mobile nodes in WSNs.…”

Section: Problems and Challenges In Wsn And Iotmentioning

confidence: 99%

Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

et al. 2020

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As we all know that the technology is projected to be next to humans very soon because of its holistic growth. Now-a-days, we see a lot of applications that are making our lives comfortable such as smart cars, smart homes, smart traffic management, smart offices, smart medical consultation, smart cities, etc. All such facilities are in the reach of a common man because of the advancement in Information and Communications Technology (ICT). Because of this advancement, new computing and communication environment such as Internet of Things (IoT) came into picture. Lot of research work is in progress in IoT domain which helps for the overall development of the society and makes the lives easy and comfortable. But in the resource constrained environment of Wireless Sensor Network (WSN) and IoT, it is almost inconceivable to establish a fully secure system. As we are moving forward very fast, technology is becoming more and more vulnerable to the security threats. In future, the number of Internet connected people will be less than the smart objects so we need to prepare a robust system for keeping the above mentioned environments safe and standardized it for the smooth conduction of communication among IoT objects. In this survey paper, we provide the details of threat model applicable for the security of WSN and IoT based communications. We also discuss the security requirements and various attacks possible in WSN and IoT based communication environments. The emerging projects of WSNs integrated to IoT are also briefed. We then provide the details of different architectures of WSN and IoT based communication environments. Next, we discuss the current issues and challenges related to WSN and IoT. We also provide a critical literature survey of recent intrusion detection protocols for IoT and WSN environments along with their comparative analysis. A taxonomy of security and privacy-preservation protocols in WSN and IoT is also highlighted. Finally, we discuss some research challenges which need to be addressed in the coming future. INDEX TERMS Wireless sensor network (WSN), Internet of Things (IoT), intrusion detection, cloud computing, fog computing, edge computing, security.

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“…However, machine-learning models have recently been included to improve localization accuracy [25]. These integrated techniques include k-means clustering [26], artificial neural networks (ANNs) [27,28], fuzzy logic (FL) [18,[29][30], support vector machines (SVMs) [15,31], Bayesian optimization [20], principle component analysis (PCA) [21], and semi-supervised [32] or deep learning [33].…”

Section: The Related Workmentioning

confidence: 99%

“…Li et al [21] introduced a nonconvex robust PCA algorithm to eliminate outliers. Kumar et al [32] presented a localization technique that used a semisupervised hidden Markov model (HMM) for mobile WSN nodes. The algorithm worked well in both indoor and outdoor environments, while requiring fewer training data than some models.…”

Section: The Related Workmentioning

confidence: 99%

A Hybrid Approach Using Multistage Collaborative Calibration for Wireless Sensor Network Localization in 3D Environments

Liang

2020

IEEE Access

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Accurate localization is critical in the internet of things (IOT), especially for wireless sensor networks (WSNs). Location estimation can be affected by factors such as node density, topological diversity, and sensor coverage. As such, we propose a hybrid approach using multistage collaborative calibration for wireless sensor network localization, specifically in 3D environments. This technique integrates a Modified version of Light Gradient Boosting Model (MLGB), which is based on a regression scheme, a cooperative methodology, and a fine calibration model for collaborative fusion. These techniques were combined with quadrilateral shrunk centroid (QSC) and distance vector hop algorithms, using a multi-communication radius and an improved frog-leaping algorithm (DVMFL). In the first step, MLGB was used to correct for inhomogeneous localization estimation errors and RSSI data sparsity. As a result, the model is capable of adapting to high topological diversity (i.e., C-shape, H-shape, Sshape, and O-shape).Successive steps further improved prediction accuracy by using a screening cooperative anchor node strategy to increase node density and enhance the QSC-DVMFL fusion framework for fine position estimation. The proposed methodology was assessed in a series of validation, comparing it to other techniques. The results demonstrated a clear effectiveness and adaptability across a variety of factors that typically affect WSN localization. INDEX TERMS Wireless sensor network; Localization; Multistage collaborative calibration technique; Modified version of light GBM; Quadrilateral shrunk centroid;

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Sensor node tracking using semi-supervised Hidden Markov Models

Cited by 12 publications

References 22 publications

Antnet Pheromone-Based Stochastic Multipath Routing Protocols using Hidden Markov Models for Energy Enhancement in Wireless Sensor Networks

Antnet Pheromone-Based Stochastic Multipath Routing Protocols using Hidden Markov Models for Energy Enhancement in Wireless Sensor Networks

Intrusion Detection Protocols in Wireless Sensor Networks Integrated to Internet of Things Deployment: Survey and Future Challenges

A Hybrid Approach Using Multistage Collaborative Calibration for Wireless Sensor Network Localization in 3D Environments

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