Intelligent multi-agent model for energy-efficient communication in wireless sensor networks

Kiran Saleem1, Lei Wang1, Salil Bharany2, Khmaies Ouahada3, Ateeq Ur Rehman4, Habib Hamam5
1School of Software, Dalian University of Technology, Dalian, China
2Independ researcher, Amritsar 143001, India
3School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa
4School of Computing, Gachon University, Seongnam 13120, Republic of Korea
5Faculty of Engineering, University de Moncton, Moncton, E1A3E9, NB, Canada

Tóm tắt

AbstractThe research addresses energy consumption, latency, and network reliability challenges in wireless sensor network communication, especially in military security applications. A multi-agent context-aware model employing the belief-desire-intention (BDI) reasoning mechanism is proposed. This model utilizes a semantic knowledge-based intelligent reasoning network to monitor suspicious activities within a prohibited zone, generating alerts. Additionally, a BDI intelligent multi-level data transmission routing algorithm is proposed to optimize energy consumption constraints and enhance energy-awareness among nodes. The energy optimization analysis involves the Energy Percent Dataset, showcasing the efficiency of four wireless sensor network techniques (E-FEERP, GTEB, HHO-UCRA, EEIMWSN) in maintaining high energy levels. E-FEERP consistently exhibits superior energy efficiency (93 to 98%), emphasizing its effectiveness. The Energy Consumption Dataset provides insights into the joule measurements of energy consumption for each technique, highlighting their diverse energy efficiency characteristics. Latency measurements are presented for four techniques within a fixed transmission range of 5000 m. E-FEERP demonstrates latency ranging from 3.0 to 4.0 s, while multi-hop latency values range from 2.7 to 2.9 s. These values provide valuable insights into the performance characteristics of each technique under specified conditions. The Packet Delivery Ratio (PDR) dataset reveals the consistent performance of the techniques in maintaining successful packet delivery within the specified transmission range. E-FEERP achieves PDR values between 89.5 and 92.3%, demonstrating its reliability. The Packet Received Data further illustrates the efficiency of each technique in receiving transmitted packets. Moreover the network lifetime results show E-FEERP consistently improving from 2550 s to round 925. GTEB and HHO-UCRA exhibit fluctuations around 3100 and 3600 s, indicating variable performance. In contrast, EEIMWSN consistently improves from round 1250 to 4500 s.

Từ khóa


Tài liệu tham khảo

K. Saleem, M. Saleem, R.Z. Ahmad, A.R. Javed, M. Alazab, T.R. Gadekallu, A. Suleman, Situation-aware BDI reasoning to detect early symptoms of COVID 19 using smartwatch. IEEE Sens. J. 23(2), 898–905 (2022). https://doi.org/10.1109/JSEN.2022.3156819. PMID: 36913222; PMCID: PMC9983688

S. Li, W. Qu, C. Liu, T. Qiu, Z. Zhao, Survey on high reliability wireless communication for underwater sensor networks. J. Netw. Comput. Appl. 148, 102446–102446 (2019). https://doi.org/10.1016/j.jnca.2019.102446

Y. Noh et al., DOTS: A propagation delay-aware opportunistic MAC protocol for mobile underwater networks. IEEE Trans. Mob. Comput. 13(4), 766–782 (2014)

S.M. Akhtar, M. Nazir, K. Saleem, H.M.U. Haque, I. Hussain, An ontology-driven IoT based healthcare formalism. Int. J. Adv. Comput. Sci. Appl. 11(2), 479–486 (2020)

H. Mahfooz Ul Haque, K. Saleem, A. Salman Khan, Modeling belief-desire-intention reasoning agents for situation-aware formalisms. Concurr. Comput. Pract. Experience. 35(15), e6417 (2023)

M. Nazir, H. Mahfooz Ul Haque, K. Saleem, A semantic knowledge based context-aware formalism for smart border surveillance system. Mob. Netw. Appl. 27(5), 2036-2048 (2022)

A. Irfan, R. Taj, K. Inayat, J. Salman, M. Shahrulniza, U.M. Irfan, RACE-SM: Reliability and adaptive cooperation for efficient UWSNs using sink mobility. Front. Mar. Sci. 9, 2296-7745 (2022). https://www.frontiersin.org/articles/10.3389/fmars.2022.1030113

S.M. Akhtar, M. Nazir, K. Saleem, R.Z. Ahmad, A.R. Javed, S.S. Band, A. Mosavi, A multi-agent formalism based on contextual defeasible logic for healthcare systems. Front. Public Health. 10, 849185 (2022)

N. Bhadwal, V. Madaan, P. Agrawal, A. Shukla, A. Kakran, in 2019 international conference on Automation, Computational and Technology Management (ICACTM), Smart border surveillance system using wireless sensor network and computer vision (IEEE, 2019), pp. 183-190

N. Srivastava, N. Gupta, B. Verma, P. Tiwari, L. Verma, M. Kaur, Border security system. IJRITCC. 5(5), 283–285 (2017)

H. Aloulou, R. Endelin, M. Mokhtari, B. Abdulrazak, F. Kaddachi, J. Bellmunt, in 2016 21st International Conference on Engineering of Complex Computer Systems (ICECCS), Detecting inconsistencies in rule-based reasoning for ambient intelligence (IEEE, 2016), pp. 235-240

H. Haiouni, R. Maamri, in 2016 International Conference on Advanced Aspects of Software Engineering (ICAASE), Context-aware planning for intelligent environments (IEEE, 2016) pp. 1-5

T. Mazhar, et al., The role of ML, AI and 5G technology in smart energy and smart buildings management. Electronics. 11(23), 3960 (2022)

S.K. Haider, et al., Energy efficient UAV flight path model for cluster head selection in next-generation wireless sensor networks. Sensors. https://doi.org/10.3390/s21248445

B.S. Halakarnimath, A.V. Sutagundar, Multi-agent-based acoustic sensor node deployment in underwater acoustic wireless sensor networks. J. Inf. Technol. Res. 13(4), 136–155 (2020)

E. Gladkauskas, Development of a water activity control and reaction monitoring system for acidolysis and transesterification reactions using immobilized lipases in a rotating bed reactor, MS Thesis, Lund University, Sweden (2019)

A.A.H. Mohamad, N.K. Jumaa, S.H. Majeed, ThingSpeak cloud computing platform based ECG diagnose system. Int. J. Comput. Digit. Syst. 8(01), 11–18 (2019)

A. Muqeet, Real-time monitoring of electromyography (EMG) using IoT and ThingSpeak. Sci. Technol. Dev. 8, 9–13 (2019)

A.H. Miry, G.A. Aramice, Water monitoring and analytic based ThingSpeak. Int. J. Electr. Comput. Eng. 10(4), 3588 (2020)

J.I.V. Luna, F.J. Sánchez-Rangel, J.F. Cosme-Aceves, Monitoring system for doors and windows of a data center with IoT. Ingenius. 22, 72 (2019)

S. Balouch, et al., Optimal scheduling of demand side load management of smart grid considering energy efficiency. Energy Res. https://doi.org/10.3389/fenrg.2022.861571

S. Balouch, et al., Feasibility of solar grid-based industrial virtual power plant for optimal energy scheduling: a case of Indian power sector. Energies. https://doi.org/10.3390/en15030752

D. Jain, P.K. Shukla, S. Varma, Energy efficient architecture for mitigating the hot-spot problem in wireless sensor networks. J. Ambient. Intell. Human. Comput. 14, 10587–10604 (2023). https://doi.org/10.1007/s12652-022-03711-5

V. Narayan, A.K. Daniel, P. Chaturvedi, E-FEERP: Enhanced fuzzy based energy efficient routing protocol for wireless sensor network. Wirel. Pers. Commun. 131, 371–398 (2023). https://doi.org/10.1007/s11277-023-10434-z

H.V. Chaitra, G. Manjula, M. Shabaz, A.B. Martinez-Valencia, K.B. Vikhyath, S. Verma, J.L. Arias-Gonzáles, Delay optimization and energy balancing algorithm for improving network lifetime in fixed wireless sensor networks. Phys. Commun. 58, 102038 (2023)