A Cluster-Based Routing Strategy Using Gravitational Search Algorithm for WSN

Kavitha, A.; Guravaiah, Koppala; Velusamy, R. Leela

doi:10.5626/jcse.2020.14.1.26

Cited by 14 publications

(7 citation statements)

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“…In the literature, many load balanced cluster-based routing approaches [30][31][32][33][34][35] have been proposed for efficient routing. These approaches improve the network lifetime by achieving load balance among the CHs.…”

Section: Related Workmentioning

confidence: 99%

“…CH selection phase is performed as in CS-CGMP based routing strategy. 31 The precise number of CHs are selected based on the total number of alive nodes in a zone. The required number of CHs is decided by the node density of the zone.…”

Section: Ch Selection Phasementioning

confidence: 99%

“…It is important to select the number of CHs needed for communication. CH selection phase is performed as in CS‐CGMP based routing strategy 31 . The precise number of CHs are selected based on the total number of alive nodes in a zone.…”

Section: Proposed Approachmentioning

confidence: 99%

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DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Kavitha

Guravaiah²,

Velusamy

et al. 2023

Int J Communication

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Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or timeseries/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.

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Section: Related Workmentioning

confidence: 99%

Section: Ch Selection Phasementioning

confidence: 99%

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DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Kavitha

Guravaiah²,

Velusamy

et al. 2023

Int J Communication

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“…However, this approach also incurs clustering overhead for selecting the optimal set of CHs. Later, Kavitha et al [62] used GSA for assigning sensor nodes to an appropriate cluster head (CH) in a load-balanced way such that it reduces the energy consumption and hence enhances the lifetime of a network.…”

Section: Existing Routing Techniquesmentioning

confidence: 99%

Data Collection Protocols in Wireless Sensor Networks

Guravaiah¹,

Kavitha²,

Velusamy³

2021

Wireless Sensor Networks - Design, Deployment and Applications

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In recent years, wireless sensor networks have became the effective solutions for a wide range of IoT applications. The major task of this network is data collection, which is the process of sensing the environment, collecting relevant data, and sending them to the server or BS. In this chapter, classification of data collection protocols are presented with the help of different parameters such as network lifetime, energy, fault tolerance, and latency. To achieve these parameters, different techniques such as multi-hop, clustering, duty cycling, network coding, aggregation, sink mobility, directional antennas, and cross-layer solutions have been analyzed. The drawbacks of these techniques are discussed. Finally, the future work for routing protocols in wireless sensor networks is discussed.

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“…CH selection is extremely important in cluster-based routing methods. Most clustering algorithms focus solely on CH selection and cluster formation [13], rather than data routing after cluster creation. Data about data compactness and separateness can be obtained from clustering outcomes.…”

Section: Introductionmentioning

confidence: 99%

SSE Path Routing Protocol for WSN IOT Using Fuzzy Mean Weighted Code and Enthalpy ANN-GOA

Rani

Sharma

2021

Preprint

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Wireless Sensor Networks (WSNs) play a key role in the Internet of Things (IoT) by delivering cost-effective solutions for specific IoT applications. The amount of energy used to transport data from a sensor node to its destination is a significant consideration when developing wireless sensor network routing strategies. A variety of routing protocols are utilised in WSN to improve network performance. When a node's mode transitions from active to sleep, the efficiency declines because data packets must wait at the starting point where they were transmitted, which increases packets' waiting time and end-to-end latency, resulting in an increase in energy consumption. This study proposes the SSE Path routing protocol as a Scalable, Secure, and Energy Efficient Routing Protocol for WSN IoT. Our proposed protocol, first selecting the nodes using a single-hop clustering algorithm. Second, FMWC (Fuzzy Mean Weighted Code) based packet coded operation for the security of packet. Finally, Scalable Enthalpy Artificial Neural-Network Based Grasshopper Optimization Algorithm (EANN-GOA) algorithm for selecting the congestion-free path for transit the data packets. The experimental results revelations the dominance of presented protocol comparing with the existing protocols.

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A Cluster-Based Routing Strategy Using Gravitational Search Algorithm for WSN

Cited by 14 publications

References 0 publications

DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

DR‐NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Data Collection Protocols in Wireless Sensor Networks

SSE Path Routing Protocol for WSN IOT Using Fuzzy Mean Weighted Code and Enthalpy ANN-GOA

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