Smart City Gnosys

Smart city article details

Title Cfmcrs: Calibration Fuzzy- Metaheuristic Clustering Routing Scheme Simultaneous In On-Demand Wrsns For Sustainable Smart City
ID_Doc 13590
Authors Fanian F.; Kuchaki Rafsanjani M.
Year 2023
Published Expert Systems with Applications, 211
DOI http://dx.doi.org/10.1016/j.eswa.2022.118619
Abstract Achieving a sustainable state in smart cities would require ongoing monitoring and evaluation of all activities in different dimensions. Hence, it is essential to use smart systems and adaptable, reliable, and controllable schemes in all dimensions of smart cities. This paper focuses on the on-demand wireless rechargeable sensor networks (WRSNs) to allow for ongoing and sustainable monitoring and provide application-based services matching goals, conditions, and the environment within in smart cities. Overcoming the challenge of energy limitation, WRSNs are more reliable than wireless sensor networks (WSNs). Hence, the paper proposes a calibration fuzzy-metaheuristic clustering routing scheme (CFMCRS) for on-demand WRSNs. The proposed CFMCRS benefits from resource-saving and energy supplementary techniques in addition to using metaheuristic and fuzzy logic methods to manage roles and energy distribution in nodes and across the network. It also uses a multiobjective function to match and calibrate the network with the nearest-job-next with preemption (NJNP) charging scheduler to meet WRSN requirements in smart cities. The extensive simulation results of the proposed CFMCRS were compared with the state-of-the-art methods in terms of energy efficiency, latency, minimum sustainability rate, dead rate, survival rate, mean energy of network, number of packets received by base station (BS), request rates, and sensitive analysis. Accordingly, the proposed scheme outperformed the other methods by far for application requirements and improved evaluation factors for application. Ultimately, it can prolong the WRSN lifetime. The simulation results were also validated through ANOVA and its subsequent post-hoc analysis.
Author Keywords Charging schedule; Fuzzy inference system; Sustainable smart cities; Whale optimization algorithm (WOA); Wireless rechargeable sensor networks (WRSN)


Similar Articles


Id Similarity Authors Title Published
57351 View0.901Fanian F.; Kuchaki Rafsanjani M.Three-Stage Fuzzy-Metaheuristic Algorithm For Smart Cities: Scheduling Mobile Charging And Automatic Rule Tuning In WrsnsApplied Soft Computing, 145 (2023)
23436 View0.864Chithaluru P.; Al-Turjman F.; Kumar M.; Stephan T.Energy-Balanced Neuro-Fuzzy Dynamic Clustering Scheme For Green & Sustainable Iot Based Smart CitiesSustainable Cities and Society, 90 (2023)
34823 View0.859Mehra P.S.Lbecr: Load Balanced, Efficient Clustering And Routing Protocol For Sustainable Internet Of Things In Smart CitiesJournal of Ambient Intelligence and Humanized Computing, 14, 8 (2023)
676 View0.855Senthamil Selvi M.; Ranjeeth Kumar C.; Jansi Rani S.A Cluster-Based Routing In Wsn For Smart City Applications Using Neural NetworksJournal of Intelligent and Fuzzy Systems, 44, 6 (2023)
40714 View0.852Sambo D.W.; Yenke B.O.; Förster A.; Dayang P.Optimized Clustering Algorithms For Large Wireless Sensor Networks: A ReviewSensors (Switzerland), 19, 2 (2019)
28724 View0.851Saxena P.; Singh Bhadauria S.Hardware Implementation Of Fuzzy Logic-Based Energy-Efficient Routing Protocol For Environment Monitoring Application Of Wireless Sensor NetworksInternational Journal of Communication Systems, 38, 8 (2025)
40832 View0.851Bharany S.; Almogren A.; Altameem A.Optimizing Iot Connectivity: A Quantitative Exploration Of The Comprehensive Adaptive Sensing And Clustering System For Smart Sensor Networks In Smart CitiesWireless Personal Communications, 140, 1 (2025)
39980 View0.851Ijemaru G.K.; Ang K.L.-M.; Seng J.K.P.; Nwajana A.O.; Yeoh P.L.; Oleka E.U.On-Demand Energy Provisioning Scheme In Large-Scale Wrsns: Survey, Opportunities, And ChallengesEnergies, 18, 2 (2025)