Energy Efficient Routing in Wireless Sensor Network Based on Composite Fuzzy Methods

Raghavendra, Y M; Mahadevaswamy, U. B.

doi:10.1007/s11277-020-07490-0

Cited by 17 publications

(12 citation statements)

References 13 publications

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“…It is calculated as in eq. (8) [ 28 ].

Where

is the total frames needed to transmit one packet,

is the error probability and

is the number of retransmissions.…”

Section: Methodsmentioning

confidence: 99%

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Multi-factor optimized mobile sink data collection framework for hybrid WSN-LTE assisted IoT network

Mohan,

Panda

2024

Heliyon

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“…It is calculated as in eq. (8) [ 28 ].

Where

is the total frames needed to transmit one packet,

is the error probability and

is the number of retransmissions.…”

Section: Methodsmentioning

confidence: 99%

“…The number of retransmissions is estimated based on the distance between the node to cluster head node (

) and the density of the cluster head node (

) as in eq. (9) [ 28 ]

…”

Section: Methodsmentioning

confidence: 99%

Multi-factor optimized mobile sink data collection framework for hybrid WSN-LTE assisted IoT network

Mohan,

Panda

2024

Heliyon

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“…The composite fuzzy method was proposed by Y. M. Raghavendra and U. B. Mahadevaswamy [22] for energy-efficient routing in WSN. In WSN, energy consumption optimization in SN batteries plays a major role.…”

Section: A Few Recent Work Related To Our Proposal Is Given Belowmentioning

confidence: 99%

Performance Analysis of Deep Learning-Based Routing Protocol for an Efficient Data Transmission in 5G WSN Communication

Arya

Bagwari²,

Chauhan

2022

IEEE Access

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For the past few years, huge interest and dramatic development have been shown for the Internet of Things (IoT) based constrained Wireless sensor network (WSN) to achieve efficient resource utilization and better service delivery. IoT requires a better communication network for data transmission between heterogeneous devices and an optimally deployed energy-efficient WSN. The clustering technique applied for WSN node deployment needs to be efficient; therefore, the entire architecture can obtain a better network lifetime. The entire network is partitioned into various clusters. Moreover, the cluster head (CH) selection process also needs proper attention to achieve efficient data communication towards the sink node via selected CH and increase the node reachability within the Cluster. An energy-efficient deep belief network (DBN) based routing protocol is developed in this proposed framework, which achieves better data transmission through the selected path. Due to this, the packet delivery ratio (PDR) gets improved. In this framework, the nodes in the whole network are initially grouped as clusters using a reinforcement learning (RL) algorithm, which assigns a reward for the nodes belonging to the particular Cluster. Then, the CH required for efficient data communication is selected using a Mantaray Foraging Optimization (MRFO) algorithm. The data is transmitted to the sink node via the selected CH using an efficient deep learning approach. Finally, the performance of the proposed deep network-based routing protocol is evaluated using different evaluation metrics: network lifetime, energy consumption, number of alive nodes, and packet delivery rate. Finally, the evaluated results are compared with a few existing algorithms. The proposed DBN routing protocol has achieved a better network lifetime among all these algorithms.

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“…The data in WMSNs is large, and the proposed network architecture and protocol processing have new challenges. There are some issues discussed here [37][38][39][40]. (1) Reliability: Multimedia data provide a wide range of reliability indicators for audio and scalar images.…”

Section: Challenges In Designing Enhanced Greedy Forwarding With Effi...mentioning

confidence: 99%

An optimal algorithm for better efficiency in WMSN for multimedia applications

Alasadi

2021

IET Wireless Sensor Systems

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The recent trends in wireless network sensor technology are moving towards multimedia applications. Multimedia sensor nodes are difficult to communicate, but communication is necessary. Multimedia service offers both video monitoring and voice over wireless sensor networks. This causes severe problems with usage of data, power, bandwidth, energy usage and wireless sensor network deployment costs. The key restriction for the expansion of a network is the energy conservation. The nodes are distributed in the field to collect audio, video and density information so as to collect the information from sensors. The network of wireless sensors provides different layer nodes depending on their power level. In this work, Enhanced Greedy Forwarding with efficient Multi‐path and Dynamic Routing (EGFMDR) protocol was proposed and the results were compared with existing state‐of‐the‐art protocols like Ad‐hoc On‐demand Distance Vector and DYMO. Depending on how powerful they are, multi‐stage architectures were employed in various areas such as observation, military, media and traffic surveillance. They retain the effectiveness of wireless sensor network in multimedia applications. Service quality protocol parameters were analysed, and from the simulation results attained, the proposed EGFMDR protocol displays reduced end‐to‐end delay, lesser packet loss ratio and increased energy efficiency.

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Energy Efficient Routing in Wireless Sensor Network Based on Composite Fuzzy Methods

Cited by 17 publications

References 13 publications

Multi-factor optimized mobile sink data collection framework for hybrid WSN-LTE assisted IoT network

Multi-factor optimized mobile sink data collection framework for hybrid WSN-LTE assisted IoT network

Performance Analysis of Deep Learning-Based Routing Protocol for an Efficient Data Transmission in 5G WSN Communication

An optimal algorithm for better efficiency in WMSN for multimedia applications

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