A green cluster‐based routing scheme for large‐scale wireless sensor networks

Chanak, Prasenjit; Banerjee, Indrajit; Sherratt, R. Simon

doi:10.1002/dac.4375

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…The DSDV is a proactive routing protocol and having an optimal end-to-end delay in comparison to AODV. The energy responsive green cluster-based routing system [10] is used to avoid the early death of large-scale dense WSNs. In clustered-based networks, clustering forms inadequate load distribution from cluster heads and cluster member nodes.…”

Section: Related Workmentioning

confidence: 99%

“…Decide the size of the WSN Network. In the design the size of the WSN is considered of nodes(5,10,20, 30...100) based on the modular design approach Design Aspects • Select the appropriate routing algorithm to perform the node intercommunication. In the design we have taken AODV routing Algorithm Selection • The design is based on the behavior model in the Xilinx ISE 14.7 software.…”

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confidence: 99%

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Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

Gupta¹,

Vaisla²,

Jain³

et al. 2022

Computer Systems Science and Engineering

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Wireless sensor network (WSN) is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings. The routing of the network is a challenging task. The routing of WSN is classified as proactive, reactive, and hybrid. Adhoc on-demand distance vector (AODV) routing is an example of reactive routing based on the demand route formations among different nodes in the network. The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language (VHDL) programming in Xilinx integrated synthesis environment (ISE) 14.7 software. The performance of the chip is studied based on the field-programmable gate array (FPGA) hardware parameters such as slices, lookup table (LUTs), input/output block (IOB), flipflops, and memory for the different configurations of the network (N = 10, 20 ….100). The delay and frequency are also estimated on the Virtex-5 FPGA. The performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio, throughput, delay, and control overhead. The simulation test cases verified the 8-bit, 64-bit, and 128-bit data communication within the nodes.

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Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

Gupta¹,

Vaisla²,

Jain³

et al. 2022

Computer Systems Science and Engineering

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“…By using either multi‐hop routing or direct connections, the aggregated data are transmitted towards the base station (BS), and the CH receives the data transmitted by the non‐CH nodes. However, with multi‐hop routing energy is very rapidly depleted due to additional CH nodes and high inter‐cluster relay traffic load generated by CHs adjacent to the BS 4 . Since the power is depleted very rapidly from the sensor nodes, it could lead to faulty hardware components and node failure.…”

Section: Introductionmentioning

confidence: 99%

“…However, with multi-hop routing energy is very rapidly depleted due to additional CH nodes and high inter-cluster relay traffic load generated by CHs adjacent to the BS. 4 Since the power is depleted very rapidly from the sensor nodes, it could lead to faulty hardware components and node failure.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Intra‐Cluster Data Aggregation and finding the Best Sink location in WSN using EEC‐MA‐PSOGA approach

Sreedevi

Venkateswarlu

2022

Int J Communication

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Summary Wireless sensor networks (WSNs) consist of nodes. Issues involved with the use of a sensor network are energy‐saving and the effective use of energy. Clustering in WSNs is a proven technique for energy optimization. The relationship between sensor nodes and cluster heads (CHs) has only been considered prior to cluster‐based routing protocols. However, most clustering algorithms have failed to address the routing overhead and the energy consumption rate between CH nodes and SINK. In this paper, a new framework named as EEC‐MA‐PSOGA ‐ an energy‐efficient (EE) intra‐cluster mobile agent (INC‐MA)‐based particle swarm optimization–genetic algorithm (PSO‐GA), has been presented to initiate the distance communication and place the SINK optimally in WSNs. The cluster members send the collected data towards their respective CHs for aggregation. To find the sink's best position, the PSO‐GA‐based location estimation algorithm is initiated based on the network structure. The limited capability of WSNs makes them more vulnerable to attackers. The prevention mechanism must be less complex to ensure the fair operations in the network. Here, the attack detection ability of the proposed solution has been tested against clone attack. With varied communication range, simulation time, and sensor nodes, the tests are conducted extensively on various scenarios of WSNs. When compared with the prior mechanisms, the framework provides better results and better prevention with less overhead by analyzing the experimental results such as energy consumption, network lifetime, and throughput.

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“…Since UCF only relies on energy to elect CHs, the distance within the cluster is likely to be too large. In 2020, Chanak et al proposed a routing scheme based on green clustering for WSNs of different densities [28]. A load-balancing data routing algorithm is proposed in the protocol to balance the network energy cost and extend the network lifespan.…”

mentioning

confidence: 99%

Optimal Relay Angle-Based Clustering Routing Protocol for Wireless Sensor Networks

Guo

Wang

et al. 2022

Journal of Sensors

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In this paper, a novel optimal relay angle-based clustering routing protocol called RACR is proposed to balance nodes’ energy consumption and prolong the network lifespan of wireless sensor networks (WSNs). In RACR, each node considers the parameters residual energy, number of neighbors, and average distance with neighbors as a criteria to determine whether to become a cluster head (CH) which cooperates with its neighbors to form a cluster. Afterward, the optimal relay angle is calculated for each CH to find its best relay node according to a target function considering the least energy consumption, which is applied to reduce the search range for finding routing paths. Consequently, all the CHs can find their best next-hop nodes within the determined field according to their residual energy, distance to the next-hop CH, and loads. Iteratively, the CHs obtain their best routing paths to the BS in the end. Simulation results demonstrate its effectiveness of RACR in terms of energy consumption, standard deviation of residual energy, data communication delay, network throughput, and lifespan.

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A green cluster‐based routing scheme for large‐scale wireless sensor networks

Cited by 13 publications

References 30 publications

Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware

An Efficient Intra‐Cluster Data Aggregation and finding the Best Sink location in WSN using EEC‐MA‐PSOGA approach

Optimal Relay Angle-Based Clustering Routing Protocol for Wireless Sensor Networks

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