Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Wireless Personal Communications
Published in: Wireless Personal Communications 3/2022

07-07-2022

Optimal Energy-Delay Scheduling using Improved Beetle Antennae Search (BAS) for Energy-Harvesting WSNs

Authors: Battina Srinuvasu Kumar, S. G. Santhi, S. Narayana

Published in: Wireless Personal Communications | Issue 3/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Optimal energy delay scheduling for capacity allocation problems in interference channel energy harvesting wireless sensor networks (EH-WSN) address of static data streams as well as power surveying. The goal is to diminish the general regression of network. However, the optimization problem is not curved, which makes it difficult to obtain optimal solution. The major goal of this document is to directly address that original non-convex formulation with enhanced Beetle Antennae Search (BAS) algorithm competently gets optimal solution. The simulations in delay, delivery ratio, drop, energy, network life, overload, and throughput are performed; the predictable result shows the improved BAS algorithm performs better convex approximation system. This plan is helpful for other complex optimization problems in WSN.
previous article Hybrid Beamforming in Large-scale Antenna Array for 5G Indoor Communication Network Deployments
next article ERIL: An Algorithm for Emotion Recognition from Indian Languages Using Machine Learning

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Das, I., Shaw, R.N. & Das, S. (2021). Location-based and multipath routing performance analysis for energy consumption in wireless sensor networks. In Innovations in electrical and electronic engineering (pp. 775–782).
2.
Liu, X., Obaidat, M. S., Lin, C., Wang, T., & Liu, A. (2020). Movement-based solutions to energy limitation in wireless sensor networks: State of the art and future trends. IEEE Network., 2, 11478.
3.
Khan, A., Gupta, S., & Gupta, S. K. (2020). Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques. International Journal of Disaster Risk Reduction, 47, 101642.CrossRef
4.
Ammari, H. M. (2021). Connected k-coverage in two-dimensional wireless sensor networks using hexagonal slicing and area stretching. Journal of Parallel and Distributed Computing, 153, 89–109.CrossRef
5.
Chowdary, K. M., & Kuppili, V. (2021). Enhanced clustering and intelligent mobile sink path construction for an efficient data gathering in wireless sensor networks. Arabian Journal for Science and Engineering, 2, 1–16.
6.
Williams, A. J., Torquato, M. F., Cameron, I. M., Fahmy, A. A., & Sienz, J. (2021). Survey of energy harvesting technologies for wireless sensor networks. IEEE Access, 4, 7789.
7.
Liu, L., Guo, X., & Lee, C. (2021). Promoting smart cities into the 5G era with multi-field Internet of Things (IoT) applications powered with advanced mechanical energy harvesters. Nano Energy, 2, 106304.CrossRef
8.
Zhao, B., & Zhao, X. (2021). Deep reinforcement learning resource allocation in wireless sensor networks with energy harvesting and relay. IEEE Internet of Things Journal, 2, 668.
9.
Ma, K., Li, Z., Liu, P., Yang, J., Geng, Y., Yang, B., & Guan, X. (2021). Reliability-constrained throughput optimization of industrial wireless sensor networks with energy harvesting relay. IEEE Internet of Things Journal, 1, 170002.
10.
Mazunga, F., & Nechibvute, A. (2021). Ultra-low power techniques in energy harvesting wireless sensor networks: Recent advances and issues. Scientific African, 4, e000720.
11.
Kanthimathi, N., & Kumar, A. (2020). Novel BOA protocol for optimal energy-delay scheduling in energy harvesting wireless sensor network. Journal of Soft Computing and Engineering Applications, 1(2), 7714.
12.
Sharma, A., & Kakkar, A. (2019). Machine learning based optimal renewable energy allocation in sustained wireless sensor networks. Wireless Networks, 25(7), 3953–3981.CrossRef
13.
Mohanty, S. N., Lydia, E. L., Elhoseny, M., Al Otaibi, M. M. G., & Shankar, K. (2020). Deep learning with LSTM based distributed data mining model for energy efficient wireless sensor networks. Physical Communication, 40, 101097.CrossRef
14.
Mythili, S., Thiyagarajah, K., Rajesh, P., & Shajin, F. H. (2020). Ideal position and size selection of unified power flow controllers (UPFCs) to upgrade the dynamic stability of systems: An antlion optimiser and invasive weed optimisation algorithm. HKIE Transactions, 27(1), 25–37.CrossRef
15.
Rajesh, P., & Shajin, F. (2020). A multi-objective hybrid algorithm for planning electrical distribution system. Sensor, 22(4–5), 224–509.
16.
Shajin, F. H., & Rajesh, P. (2020). Trusted secure geographic routing protocol: Outsider attack detection in mobile ad hoc networks by adopting trusted secure geographic routing protocol. International Journal of Pervasive Computing and Communications, 1, 776.
17.
Thota, M. K., Shajin, F. H., & Rajesh, P. (2020). Survey on software defect prediction techniques. International Journal of Applied Science and Engineering, 17(4), 331–344.
18.
Zhao, F., Chen, Y., Zhang, Y., Liu, Z., & Chen, X. (2021). Dynamic offloading and resource scheduling for mobile edge computing with energy harvesting devices. IEEE Transactions on Network and Service Management, 7, 550.
19.
Kumar, A., Singh, R. K., & Vijay, S. (2021). Performance analysis of energy efficient infrastructure-less wireless sensor networks optimize by Bio-inspired optimization. Materials Today Proceedings, 3, 7702.
20.
Deng, X., Guan, P., Hei, C., Li, F., Liu, J., & Xiong, N. (2021). An intelligent resource allocation scheme in energy harvesting cognitive wireless sensor networks. IEEE Transactions on Network Science and Engineering., 4, 1147.MathSciNet
21.
Nobar, S. K., Mansourkiaie, F., & Ahmed, M. H. (2020). Packet dropping minimization in energy harvesting-based wireless sensor network with linear topology. IEEE Access, 8, 38682–38691.CrossRef
22.
Liu, F., Jiang, C., & Xiao, W. (2020). Multistep prediction-based adaptive dynamic programming sensor scheduling approach for collaborative target tracking in energy harvesting wireless sensor networks. IEEE Transactions on Automation Science and Engineering, 18(2), 693–704.CrossRef
23.
Raja, J., & Mookhambika, N. (2021). A novel energy harvesting with middle-order weighted probability (EHMoWP) for performance improvement in wireless sensor network (WSN). Journal of Ambient Intelligence and Humanized Computing, 3, 1–12.
24.
Jiao, D., Yang, P., Fu, L., Ke, L., & Tang, K. (2019). Optimal energy-delay scheduling for energy-harvesting WSNs with interference channel via negatively correlated search. IEEE Internet of Things Journal, 7(3), 1690–1703.CrossRef
25.
Lee, K., & Hong, J. P. (2015). Energy-efficient resource allocation for simultaneous information and energy transfer with imperfect channel estimation. IEEE Transactions on Vehicular Technology, 65(4), 2775–2780.CrossRef
26.
Aoudia, F. A., Gautier, M., & Berder, O. (2017). Distributed computation of fair packet rates in energy harvesting wireless sensor networks. IEEE Wireless Communications Letters, 6(5), 626–629.CrossRef
27.
Zhang, D., Chen, Z., Awad, M. K., Zhang, N., Zhou, H., & Shen, X. S. (2016). Utility-optimal resource management and allocation algorithm for energy harvesting cognitive radio sensor networks. IEEE Journal on Selected Areas in Communications, 34(12), 3552–3565.CrossRef
28.
Fawaz, I., Sarkiss, M., & Ciblat, P. (2019). Delay-optimal resource scheduling of energy harvesting-based devices. IEEE Transactions on Green Communications and Networking, 3(4), 1023–1034.CrossRef
29.
Masood, Z., Jung, S. P., & Choi, Y. (2018). Energy-efficiency performance analysis and maximization using wireless energy harvesting in wireless sensor networks. Energies, 11(11), 2917.CrossRef
30.
Jiao, D., Yang, P., Fu, L., Ke, L., & Tang, K. (2019). Optimal energy-delay scheduling for energy harvesting wsns via negatively correlated search. In ICC 2019–2019 IEEE international conference on communications (ICC) (pp. 1–7). IEEE.
31.
Guleria, K., & Verma, A. K. (2019). Meta-heuristic ant colony optimization based unequal clustering for wireless sensor network. Wireless Personal Communications, 105(3), 891–911.CrossRef
32.
Mittal, N. (2019). Moth flame optimization based energy efficient stable clustered routing approach for wireless sensor networks. Wireless Personal Communications, 104(2), 677–694.CrossRef
Metadata
Title
Optimal Energy-Delay Scheduling using Improved Beetle Antennae Search (BAS) for Energy-Harvesting WSNs
Authors
Battina Srinuvasu Kumar
S. G. Santhi
S. Narayana
Publication date
07-07-2022
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 3/2022
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09828-2

Other articles of this Issue 3/2022

Wireless Personal Communications 3/2022 Go to the issue

OriginalPaper

Performance Evaluation of Data-driven Intelligent Algorithms for Big data Ecosystem

OriginalPaper

ACOLBR: ACO Based Load Balancing Routing in MANET

OriginalPaper

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing

OriginalPaper

An Optimized Fuzzy Clustering Algorithm for Wireless Sensor Networks

OriginalPaper

Compressive Sensing Node Localization Method Using Autonomous Underwater Vehicle Network

OriginalPaper

GAPSO-SVM: An IDSS-based Energy-Aware Clustering Routing Algorithm for IoT Perception Layer