Wireless sensor networks (WSN) have become a hot research areaowing to the unique characteristics and applicability in diverse application areas.Clustering and routing techniques can be considered as an NP hard optimi...Wireless sensor networks (WSN) have become a hot research areaowing to the unique characteristics and applicability in diverse application areas.Clustering and routing techniques can be considered as an NP hard optimizationproblem, which can be addressed by metaheuristic optimization algorithms. Withthis motivation, this study presents a chaotic sandpiper optimization algorithmbased clustering with groundwater flow optimization based routing technique(CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensornodes in WSN and elect an optimal set of routes with an intention of achievingenergy efficiency and maximizing network lifetime. The CSPOC algorithm isderived by incorporating the concepts of chaos theory to boost the global optimization capability of the SPOC algorithm. The CSPOC technique elects an optimum set of cluster heads (CH) whereas the other sensors are allocated to thenearer CH. Extensive experimentation portrayed the promising performance ofthe CSPOC-GFLR technique by achieving reduced energy utilization, improvedlifetime, and prolonged stability over the existing techniques.展开更多
Wireless Sensor Networks(WSN)started gaining attention due to its wide application in the fields of data collection and information processing.The recent advancements in multimedia sensors demand the Quality of Servic...Wireless Sensor Networks(WSN)started gaining attention due to its wide application in the fields of data collection and information processing.The recent advancements in multimedia sensors demand the Quality of Service(QoS)be maintained up to certain standards.The restrictions and requirements in QoS management completely depend upon the nature of target application.Some of the major QoS parameters in WSN are energy efficiency,network lifetime,delay and throughput.In this scenario,clustering and routing are considered as the most effective techniques to meet the demands of QoS.Since they are treated as NP(Non-deterministic Polynomial-time)hard problem,Swarm Intelligence(SI)techniques can be implemented.The current research work introduces a new QoS aware Clustering and Routing-based technique using Swarm Intelligence(QoSCRSI)algorithm.The proposed QoSCRSI technique performs two-level clustering and proficient routing.Initially,the fuzzy is hybridized with Glowworm Swarm Optimization(GSO)-based clustering(HFGSOC)technique for optimal selection of Cluster Heads(CHs).Here,Quantum Salp Swarm optimization Algorithm(QSSA)-based routing technique(QSSAR)is utilized to select the possible routes in the network.In order to evaluate the performance of the proposed QoSCRSI technique,the authors conducted extensive simulation analysis with varying node counts.The experimental outcomes,obtained from the proposed QoSCRSI technique,apparently proved that the technique is better compared to other state-of-the-art techniques in terms of energy efficiency,network lifetime,overhead,throughput,and delay.展开更多
文摘Wireless sensor networks (WSN) have become a hot research areaowing to the unique characteristics and applicability in diverse application areas.Clustering and routing techniques can be considered as an NP hard optimizationproblem, which can be addressed by metaheuristic optimization algorithms. Withthis motivation, this study presents a chaotic sandpiper optimization algorithmbased clustering with groundwater flow optimization based routing technique(CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensornodes in WSN and elect an optimal set of routes with an intention of achievingenergy efficiency and maximizing network lifetime. The CSPOC algorithm isderived by incorporating the concepts of chaos theory to boost the global optimization capability of the SPOC algorithm. The CSPOC technique elects an optimum set of cluster heads (CH) whereas the other sensors are allocated to thenearer CH. Extensive experimentation portrayed the promising performance ofthe CSPOC-GFLR technique by achieving reduced energy utilization, improvedlifetime, and prolonged stability over the existing techniques.
文摘Wireless Sensor Networks(WSN)started gaining attention due to its wide application in the fields of data collection and information processing.The recent advancements in multimedia sensors demand the Quality of Service(QoS)be maintained up to certain standards.The restrictions and requirements in QoS management completely depend upon the nature of target application.Some of the major QoS parameters in WSN are energy efficiency,network lifetime,delay and throughput.In this scenario,clustering and routing are considered as the most effective techniques to meet the demands of QoS.Since they are treated as NP(Non-deterministic Polynomial-time)hard problem,Swarm Intelligence(SI)techniques can be implemented.The current research work introduces a new QoS aware Clustering and Routing-based technique using Swarm Intelligence(QoSCRSI)algorithm.The proposed QoSCRSI technique performs two-level clustering and proficient routing.Initially,the fuzzy is hybridized with Glowworm Swarm Optimization(GSO)-based clustering(HFGSOC)technique for optimal selection of Cluster Heads(CHs).Here,Quantum Salp Swarm optimization Algorithm(QSSA)-based routing technique(QSSAR)is utilized to select the possible routes in the network.In order to evaluate the performance of the proposed QoSCRSI technique,the authors conducted extensive simulation analysis with varying node counts.The experimental outcomes,obtained from the proposed QoSCRSI technique,apparently proved that the technique is better compared to other state-of-the-art techniques in terms of energy efficiency,network lifetime,overhead,throughput,and delay.
