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Number of results: 12
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Abstract

In this paper a prototype framework for simulation of wireless sensor network and its protocols are presented. The framework simulates operation of a sensor network with data transmission, which enables simultaneous development of the sensor network software, its hardware and the protocols for wireless data transmission. An advantage of using the framework is converging simulation with the real software. Instead of creating a model of the sensor network node, the same software is used in real sensor network nodes and in the simulation framework. Operation of the framework is illustrated with examples of simulations of selected transactions in the sensor network.
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Authors and Affiliations

Marek Wójcikowski
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Abstract

Disorders of the heart and blood vessels are the leading cause of health problems and death. Early detection of them is extremely valuable as it can prevent serious incidents (e.g. heart attack, stroke) and associated complications. This requires extending the typical mobile monitoring methods (e.g. Holter ECG, tele-ECG) by introduction of integrated, multiparametric solutions for continuous monitoring of the cardiovascular system.

In this paper we propose the wearable system that integrates measurements of cardiac data with actual estimation of the cardiovascular risk level. It consists of two wirelessly connected devices, one designed in the form of a necklace, the another one in the form of a bracelet (wrist watch). These devices enable continuous measurement of electrocardiographic, plethysmographic (impedance-based and optical-based) and accelerometric signals. Collected signals and calculated parameters indicate the electrical and mechanical state of the heart and are processed to estimate a risk level. Depending on the risk level an appropriate alert is triggered and transmitted to predefined users (e.g. emergency departments, the family doctor, etc.).

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Authors and Affiliations

Jerzy Wtorek
Adam Bujnowski
Jacek Rumiński
Artur Poliński
Mariusz Kaczmarek
Antoni Nowakowski
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Abstract

This paper aims at designing, building, and simulating a secured routing protocol to defend against packet dropping attacks in mobile WSNs (MWSNs). This research addresses the gap in the literature by proposing Configurable Secured Adaptive Routing Protocol (CSARP). CSARP has four levels of protection to allow suitability for different types of network applications. The protocol allows the network admin to configure the required protection level and the ratio of cluster heads to all nodes. The protocol has an adaptive feature, which allows for better protection and preventing the spread of the threats in the network. The conducted CSARP simulations with different conditions showed the ability of CSARP to identify all malicious nodes and remove them from the network. CSARP provided more than 99.97% packets delivery rate with 0% data packet loss in the existence of 3 malicious nodes in comparison with 3.17% data packet loss without using CSARP. When compared with LEACH, CSARP showed an improvement in extending the lifetime of the network by up to 39.5%. The proposed protocol has proven to be better than the available security solutions in terms of configurability, adaptability, optimization for MWSNs, energy consumption optimization, and the suitability for different MWSNs applications and conditions.
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Authors and Affiliations

Ahmed Alnaser
1
Hessa Al-Junaid
1
Reham Almesaeed
1

  1. University of Bahrain, College of Information Technology, Kingdom of Bahrain
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Abstract

Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection.
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Authors and Affiliations

Basavaraj M. Angadi
1
Mahabaleshwar S. Kakkasageri
1

  1. Faculty of Electronics and Communication Engineering Department,Basaveshwar Engineering College, Bagalkote, Karnataka, INDIA
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Abstract

The recent decades have seen the growth in the fields of wireless communication technologies, which has made it possible to produce components with a rational cost of a few cubic millimeters of volume, called sensors. The collaboration of many of these wireless sensors with a basic base station gives birth to a network of wireless sensors. The latter faces numerous problems related to application requirements and the inadequate abilities of sensor nodes, particularly in terms of energy. In order to integrate the different models describing the characteristics of the nodes of a WSN, this paper presents the topological organization strategies to structure its communication. For large networks, partitioning into sub-networks (clusters) is a technique used to reduce consumption, improve network stability and facilitate scalability.
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Authors and Affiliations

Sarang Dagajirao Patil
1
Pravin Sahebrao Patil
2

  1. NES Gangamai College of Engineering, Nagaon, Dhule, Maharashta, India
  2. Dept. of E&C Engineering SSVPSBSD College of Engineering Dhule, Maharashtra, India
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Abstract

Distributed measurement often relies on sensor networks. In this paper, we present the construction of low-coherence fiber-optic Fabry–Pérot sensors connected into a quasi-distributed network. We discuss the mechanism of spectrum modulation in this type of sensor and the constraints of assembly of such sensors in the network. Particular attention was paid to separate the signals from individual sensors which can be achieved by cavity length-based addressing. We designed and built a laboratory model of a temperature sensors network. The employed sensors are low-coherence Fabry–Pérot interferometric sensors in a fiberoptics configuration. The extrinsic sensor cavity utilizes the thermal expansion of ceramics, and the sensors are addressed by the different lengths of the cavities. The obtained test results showthat the signal components from each sensor can be successfully separated, and the number of sensors could be expanded depending on the FWHM of the light source.
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Authors and Affiliations

Katarzyna Karpienko
1
Marcin J. Marzejon
1
Adam Mazikowski
1
Jerzy Plucinski
1

  1. Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics, Department of Metrology and Optoelectronics, 11/12 Gabriela Narutowicza St., 80-233 Gdansk, Poland
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Abstract

The paper presents a circuit structure that can be used for powering an IoT (Internet of Things) sensor node and that can use energy just from its surroundings. The main advantage of the presented solution is its very low cost that allows mass applicability e.g. in the IoT smart grids and ubiquitous sensors. It is intended for energy sources that can provide enough voltage but that can provide only low currents such as piezoelectric transducers or small photovoltaic panels (PV) under indoor light conditions. The circuit is able to accumulate energy in a capacitor until a certain level and then to pass it to the load. The presented circuit exhibits similar functionality to a commercially available EH300 energy harvester (EH). The paper compares electrical properties of the presented circuit and the EH300 device, their form factors and costs. The EH circuit’s performance is tested together with an LTC3531 buck-boost DC/DC converter which can provide constant voltage for the following electronics. The paper provides guidelines for selecting an optimal capacity of the storage capacitor. The functionality of the solution presented is demonstrated in a sensor node that periodically transmits measured data to the base station using just the power from the PV panel or the piezoelectric generator. The presented harvester and powering circuit are compact part of the sensor node’s electronics but they can be also realized as an external powering module to be added to existing solutions.

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Authors and Affiliations

Adam Bouřa
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Abstract

This paper details a hardware implementation of a distributed Θ(1) time algorithm allows to select dynamically the master device in ad-hoc or cluster-based networks in a constant time regardless the number of devices in the same cluster. The algorithm allows each device to automatically detect its own status; master or slave; based on identifier without adding extra overheads or exchanging packets that slow down the network. We propose a baseband design that implements algorithm functions and we detail the hardware implementation using Matlab/Simulink and Ettus B210 USRP. Tests held in laboratory prove that algorithm works as expected.

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Authors and Affiliations

Mohammed El Khattabi
Jelloul Elmesbahi
Ahmed Errami and Omar Bouattane Mohammed Khaldoun
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Abstract

Due to the severe damages of nuclear accidents, there is still an urgent need to develop efficient radiation detection wireless sensor networks (RDWSNs) that precisely monitor irregular radioactivity. It should take actions that mitigate the severe costs of accidental radiation leakage, especially around nuclear sites that are the primary sources of electric power and many health and industrial applications. Recently, leveraging machine learning (ML) algorithms to RDWSNs is a promising solution due to its several pros, such as online learning and self-decision making. This paper addresses novel and efficient ML-based RDWSNs that utilize millimeter waves (mmWaves) to meet future network requirements. Specifically, we leverage an online learning multi-armed bandit (MAB) algorithm called Thomson sampling (TS) to a 5G enabled RDWSN to efficiently forward the measured radiation levels of the distributed radiation sensors within the monitoring area. The utilized sensor nodes are lightweight smart radiation sensors that are mounted on mobile devices and measure radiation levels using software applications installed in these mobiles. Moreover, a battery aware TS (BATS) algorithm is proposed to efficiently forward the sensed radiation levels to the fusion decision center. BA-TS reflects the remaining battery of each mobile device to prolong the network lifetime. Simulation results ensure the proposed BA-TS algorithm’s efficiency regards throughput and network lifetime over TS and exhaustive search method.
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Bibliography

[1] R. Elhabyan, W. Shi and M. St-Hilaire, ”Coverage protocols for wireless sensor networks: Review and future directions,” Journal of Communications and Networks, 21, (1), 45-60, Feb. 2019, DOI: 10.1109/JCN.2019.000005.
[2] X. Ge, Q. Han, X. Zhang, L. Ding and F. Yang, ”Distributed Event-Triggered Estimation Over Sensor Networks: A Survey,” IEEE Transactions on Cybernetics, 50 (3), 1306-1320, March 2020, DOI: 10.1109/TCYB.2019.2917179.
[3] International ATomic Energy Authority (IAEA) accident reports available online, https://www.iaea.org/topics/accident-reports.
[4] R. R. Kumar, L. Macwin and R. Rathna, ”Nuclear radiation detection using Wireless Sensor Network,” 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, 2015, pp. 1-4, DOI: 10.1109/ICIIECS. 2015.7192790.
[5] R. Dersch,Primary and secondary measurements of 222Rn, Journal of Applied Radiation and Isotopes, 60, Issues 2–4, 2004, Pages 387-39, 2004, DOI: 10.1016/j.apradiso.2003.11.046.
[6] Drew, Christina Grace, Deirdre Silbernagel, Susan Hemmings, Erin Smith, Alan Griffith, William Takaro, Tim Faustman, Elaine, ”Nuclear Waste Transportation: Case Studies of Identifying Stakeholder Risk Information Needs”. Environmental Health Perspectives, 111, 263- 72, DOI: 10.1289/ehp.5203.
[7] Manar, M.K., Mohamed, S., Hashima, S., Imbaby, I.M., Amal-Eldin, M., Nesreen, I. “Hardware Implementation for Pileup Correction Algorithms in Gamma Ray Spectroscopy. International Journal of Computer Applications, 176, 43-48, 2017. DOI: 10.5120/ijca2017915634
[8] Bensaleh, Mohammed Saida, Raoudha Hadj kacem, Yessine Abid, Mohamed. ”Wireless Sensor Network Design Methodologies: A Survey”. Journal of Sensors, pp.1-13, 2020. DOI: 10.1155/2020/9592836.
[9] B. Xing, R. Ding and J. Wang, ”Design of Wireless Sensor Network for Protection of X-Ray Detection,” 2013 6th International Conference on Intelligent Networks and Intelligent Systems (ICINIS), Shenyang, 2013, pp. 282-285, DOI: 10.1109/ICINIS.2013.79.
[10] M. Altayeb, M. Mekki, O. Abdallah, A. B. Mustafa and S. Abdalla, ”Automobile and fixed wireless sensor network for radiation detection,” 2015 International Conference on Computing, Control, Networking, Electronics and Embedded Systems Engineering (ICCNEEE), Khartoum, 2015, pp. 199-202, DOI: 10.1109/ICCNEEE.2015.7381361.
[11] C. Liu, P. -. Drouin, G. St-Jean, M. D´eziel and D. Waller, ”Wireless Radiation Sensor Network with directional radiation detectors,” IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Seattle, WA, pp. 1-6, 2014. DOI: 10.1109/NSSMIC.2014.7431111.
[12] Jianxin Sun, ”Radiation detection using mobile sensor networks”, PhD thesis, University of Delaware, Spring 2016.
[13] Ding, Fei Zhang, Deng-yin Wang, Wanping Lei, Zhenzhong. (2018). ”A Low Complexity Active Sensing and Inspection System for Monitoring of Moveable Radiation Environments”. Journal of Sensors, 2018, 1-9. 10.1155/2018/8096012.
[14] M. S. Muktadir, S. Islam and A. R. Alam Chowdhury, ”Development of a Wireless Safety System Based on Multiple Radiation Detector for Nuclear Facilities,” International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, pp. 539- 542, 2019. DOI: 10.1109/ICREST.2019.8644312.
[15] Vasile Buruian˘a, Mihaela Oprea. A Microcontroller-Based Radiation Monitoring and Warning System. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, DOI: 10.1007/978-3-642-33412-2 39.
[16] Barbar´an, Javier D´ıaz, a Esteve, I˜naki Rubio, Bartolom´e. RadMote: a mobile framework for radiation monitoring in nuclear power plants, 2007.
[17] S. Duraisamy, G. K. Pugalendhi and P. Balaji, ”Reducing energy consumption of wireless sensor networks using rules and extreme learning machine algorithm,” The Journal of Engineering, vol. 2019, no. 9, pp. 5443-5448, 2019, DOI: 10.1049/joe.2018.5288.
[18] Thompson, William R. ”On the Likelihood That One Unknown Probability Exceeds Another in View of the Evidence of Two Samples.” Biometrika 25, no. 3/4, 1933. DOI: 10.2307/2332286.
[19] F. Wilhelmi, C. Cano, G. Neu, B. Bellalta, A. Jonsson, and S. Barrachina-Mu˜noz, “Collaborative spatial reuse in wireless networks via selfish multi-armed bandits,” Ad Hoc Networks, vol. 88, pp. 129–141, 10 2017. DOI: 10.1016/j.adhoc.2019.01.006.

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Authors and Affiliations

Sherief Hashima
1
Imbaby Mahmoud
2

  1. Engineering Dept., Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 13759, Egypt
  2. Radiation Engineering Dept., National Center of Radiation Research and Technology (NCRRT) Egyptian Atomic Energy Authority, Cairo, Egypt
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Abstract

Wireless Sensor Network (WSN) technology has grown in importance in recent years. All WSN implementations need secure data transmission between sensor nodes and base stations. Sensor node attacks introduce new threats to the WSN. As a result, an appropriate Intrusion Detection System (IDS) is required in WSN for defending against security attacks and detecting attacks on sensor nodes. In this study, we use the Routing Protocol for Low Power and Lossy Networks (RPL) for addressing security services in WSN by identifying IDS with a network size of more or less 20 nodes and introducing 10% malicious nodes. The method described above is used on Cooja in the VMware virtual machine Workstation with the InstantContiki2.7 operating system. To track the movement of nodes, find network attacks, and spot dropped packets during IDS in WSN, an algorithm is implemented in the Network Simulator (NS2) using the Ad-hoc On-Demand Distance Vector (AODV) protocol in the Linux operating system.
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Authors and Affiliations

Joseph Kipongo
1
Theo G. Swart
1
Ebenezer Esenogho
1 2

  1. Center for Telecommunications, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South Africa
  2. Department of Electrical and Electronic Engineering, University of Botswana, Gaborone, Botswana
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Abstract

Wireless sensor network is a dynamic field of networking and communication because of its increasing demand in critical Industrial and Robotics applications. Clustering is the technique mainly used in the WSN to deal with large load density for efficient energy conservation. Formation of number of duplicate clusters in the clustering algorithm decreases the throughput and network lifetime of WSN. To deal with this problem, advance distributive energy-efficient adaptive clustering protocol with sleep/wake scheduling algorithm (DEACP-S/W) for the selection of optimal cluster head is presented in this paper. The presented sleep/wake cluster head scheduling along with distributive adaptive clustering protocol helps in reducing the transmission delay by properly balancing of load among nodes. The performance of algorithm is evaluated on the basis of network lifetime, throughput, average residual energy, packet delivered to the base station (BS) and CH of nodes. The results are compared with standard LEACH and DEACP protocols and it is observed that the proposed protocol performs better than existing algorithms. Throughput is improved by 8.1% over LEACH and by 2.7% over DEACP. Average residual energy is increased by 6.4% over LEACH and by 4% over DEACP. Also, the network is operable for nearly 33% more rounds compared to these reference algorithms which ultimately results in increasing lifetime of the Wireless Sensor Network.
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Bibliography

[1] K. Sohraby, D. Minoli, T. Znati, “Wireless sensor networks: technology, protocols, and applications,” John Wiley & Sons, 2007.
[2] K. Pavai, A. Sivagami and D. Sridharan, "Study of Routing Protocols in Wireless Sensor Networks,” 2009 International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, Kerala, 2009, pp. 522-525.
[3] D. Goyal and M. R. Tripathy, "Routing Protocols in Wireless Sensor Networks: A Survey,"2012 Second International Conference on Advanced Computing & Communication Technologies, Rohtak, Haryana, 2012, pp. 474-480.
[4] NasirSaeed, Ahmed Bader, T.Y. Al-Naffouri, Mohamed-slim Alouini, “When Wireless Communication Faces COVID-19: Combating the Pandemic and Saving the Economy,” Research Gate Journal, May 2020.
[5] Jitendra Singh, Rakesh Kumar, “Clustering algorithms for wireless sensor networks: A review,” 2nd International Conference on Computing for Sustainable Global Development, May 2015.
[6] S. Misra and R. Kumar, "A literature survey on various clustering approaches in wireless sensor network," IEEE 2nd International Conference on Communication Control and Intelligent Systems (CCIS), Mathura, 2016, pp. 18-22.
[7] S. Mishra, R. Bano, S. Kumar and V. Dixit, "A literature survey on routing protocol in wireless sensor network," IEEE International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, 2017, pp. 1-4.
[8] Kalyani Wankhede, Sumedha Sirsikar, “Review of Clustering Algorithms in Wireless Sensor Networks,” International Journal of Advance Foundation and Research in Computer (IJAFRC), Volume 1, Issue 11, November 2014, pp.126-133.
[9] Sangho Yi, Junyoung Heo, Yookun Cho and Jiman Hong b, “PEACH: Power-efficient and adaptive clustering hierarch protocol for wireless sensor networks,” Computer Communications, ELSEVIER, 23 June 2007, pp. 2842–2852.
[10] K. T. Kim and H. Y. Youn, “Energy-Driven Adaptive Clustering Hierarchy (EDACH) for Wireless Sensor Networks,” International Federation of Info. Processing, vol. 3823, Dec. 2005, pp. 1098–1107.
[11] V. Loscri, G. Morabito and S. Marano, “A Two-Level Hierarchy for Low-Energy Adaptive Clustering Hierarchy(TL-LEACH),” IEEE Proceedings of Vehicular Technology Conference, vol. 3, 2005, pp. 1809-1813.
[12] S. Nasr, M. Quwaider, “LEACH Protocol Enhancement for Increasing WSN Lifetime,” 2020 11th International Conference on Information and Communication Systems (ICICS), April 2020, pp. 102-107.
[13] M. Kaddi, Z. Khalili, M. Bruchra, “A Differential Evolution Based Clustering and Routing Protocol for WSN,” 2020 International Conference on Mathematics and Information Technology, March 2020, pp. 190-195.
[14] G. Malshetty, B. Mathapati, “Efficient Clustering in WSN-Cloud using LBSO (Load Based Self Organised) technique,” Third International Conference on Trends in Electronics and Informatics(ICOEI), October 2019, pp. 1243-1247.
[15] K. Dubey, A. Yadav, P. Kumar, P. Shekar, P. Rajput, S. Kumar, “Power Optimization Algorithm for Heterogeneous WSN using Multiple Attributes,” Proceedings of Third International Conference on Computing Methodologies and Communication (ICCMC), August 2019, pp. 294-299.
[16] O. Younis, S. Fahmy, “HEED: A Hybrid Energy-Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on mobile computing, vol. 3(4) , 2004, pp. 1-36
[17] A. Manjeshwar, D. P. Agrawal, “TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks,” 15th International Workshop on Parallel and Distributed Processing Symposium (IPDPS), 23–27 April 2001, pp. 2009–2015.
[18] A. Manjeshwar, D. P. Agrawal, “APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks,” 2nd International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing,” April 2002, pp. 195–202.
[19] Chirihane Gherbi, Zibouda Aliouat, Mohamed Benmohammed, “A Novel Load Balancing Scheduling Algorithm For Wireless Sensor Networks,” Journal of Network And Systems Management (2019) 27, pp. 430–462.
[20] Heinzelman W,Chandrakasan A and Balakrishnan H, "Energy-Efficient Communication Protocols for Wireless Microsensor Networks," Proceedings of the 33rd Hawaaian International Conference on Systems Science (HICSS), January 2000.
[21] JiuqiangXu, Wei Liu, Fenggao Lang, Yuanyuan Zhang, Chenglong Wang, “Distance Measurement Model Based on RSSI in WSN,” Scientific Research Journal on Wireless Sensor Network, August 2010, pp. 606-611
[22] Nazir Babar, Hasbullah Halabi & Madani Sajjad, “Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks,” EURASIP Journal on Wireless Communications and Networking, 2011, art. no 92. doi: 10.1186/1687-1499-2011-92.

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Authors and Affiliations

Shankar D. Chavan
1
Shahaji R. Jagdale
1
Dhanashree A. Kulkarni
1
Sneha R. Jadhav
1

  1. Dr. D. Y. Patil Institute of Technology, Pimpri, Pune
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Abstract

The 6TiSCH communication stack enables IPv6 networking over the TSCH (Time Slotted Channel Hopping) mode of operation defined in IEEE 802.15.4. Lately it became an attractive solution for Low power and Lossy Networks (LLNs), suitable for Industrial Internet of Things (IIoT) applications. This article introduces a credible energy consumption model for the 6TiSCH network nodes, operating in the 863-870 MHz band. It presents the analysis leading to the construction of the model as well as verification through experimental measurements which showed 98% accuracy in determining power consumption for two different network topologies. The article includes reliable battery lifetime predictions for transit and leaf nodes along with other parametric study results.

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Authors and Affiliations

Mateusz Kubaszek
Jan Macheta
Łukasz Krzak
Cezary Worek

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