A Survey of Secured Cluster Head: SCH Based Routing Scheme for IOT Based Mobile Wireless Sensor Network

Kiruba, D. Giji; Benita, J.

doi:10.1149/10701.16725ecst

Cited by 9 publications

(5 citation statements)

References 38 publications

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“…The disadvantage is that it misses the network's vigour in each cycle. The cutoff value was expressed by EDDEEC using three segments: an enhanced node, a standard node, and a superior node [19][20].…”

Section: Related Workmentioning

confidence: 99%

Blue Brain Based Clustering Protocol for Mobile Wireless Sensor Networks

Rajesh

2023

Preprint

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Blue Brain based clustering have emerged as one of the most popular methodologies in a variety of applications, like farming, smoke alarms, medical, and industrial surveillance e.t.c. Blue Brain based mobile wireless sensor networks offers a variety of advantages, like affordability, portability, versatility, self-organization, and the capacity to route traffic using Blue Brain algorithms. Increasingly practical applications than it's ever been utilize Blue Brain. However, among the most serious issues is the lack of energy. It prevents the full use of Blue Brain technology. Normally, battery packs have a limited life are used to power sensors. Wireless sensor networks always have opportunity for efficient energy usage even when renewable resources (like solar or electromechanical technologies) are being used as supplemental energy. In this research work point out the flaws in the existing approaches, offer a fresh technique that strengthens it, and contrast it with ICRA strategy. This investigation largely relies on the constraints of an ICRA as well as its associated algorithms in order to enhance network longevity by minimizing energy usage.

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Section: Related Workmentioning

confidence: 99%

Blue Brain Based Clustering Protocol for Mobile Wireless Sensor Networks

Rajesh

2023

Preprint

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“…Though, M-LEACH does not think mobility in basestation. Energy-Efficient and Reliable-Routing (E 2 R 2 ) for MWSNs think about the mobility of basestation and smart dust nodes while routing resolution are made, but less security while routing resolution [10,11]. B92 utilizes non-orthogonal bases to transmit qubits to delivery side [12].…”

Section: Related Workmentioning

confidence: 99%

CSCRT Protocol with Energy Efficient Secured CH Clustering for Smart Dust Network Using Quantum Key Distribution

Rajesh¹,

Rajanna²

2022

IJSSE

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Energy efficient protocols for Mobile wireless smart dust networks are getting prominence in the present scenario. This paper describes a novel scheme for intrusion detection framework for secured clustered mobile smart dust networks which better suits the periodical data gathering. The essential objective of a battery equipped mobile wireless smart dust nodes is to upgrade the transmission energy. The proposed protocol has the favourable position that the communication and computational overheads get reduced and gives improved energy efficient routing protocol as far as energy efficient and intrusion detection system. The intrusion and interruption are fundamentally same as that it is difficult to recognize. The design becomes more complex, any security protection algorithms utilize more energy. This can be achieved by using IDS based clustering tactic, Specific Encryption algorithm with Quantum Key Distribution and Chance Succession Comparison Ratio Test protocol. Particular encryption for data based communication is carried out to low utilization of energy and also to discover attacks, when it occurs in mobile nodes. Data transmission rate is a factor for energy utilization. Simulation is done in NS2, results show that better energy efficient routing scheme for mobile wireless smart dust network.

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“…The Blue Brain not only oversees the products but also monitors the behavior of its owners. Blue Brain is being used more and more in a variety of applications, such as smart home design, health analysis, and environmental observation [5][6][7][8]. As such, increasing the effectiveness of real information gathering and communication is a challenging undertaking.…”

Section: Introductionmentioning

confidence: 99%

Energy capable protocol for heterogeneous blue brain network

DENNİSON,

DASEBENEZER,

DENNİSON

2024

Turkish Journal of Engineering

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The Blue Brain has a wide range of applications, which raises a number of challenging issues. Electronics may continuously monitor their surroundings depending on the real data that their Blue Brain nodes are acquiring by employing situational intelligence based on the Blue Brain environment. The Blue Brain does more than only monitor user behavior when utilizing this technology. Blue Brain is linked to a critical prerequisite for energy-efficient communication methodologies. Through the Blue Brain network, it utilizes the heterogeneity and variety of the interconnected components. Blue Brain nodes that are outsourced and have limited energy resources must utilize less energy. IoT nodes with differing energy levels are frequently dispersed across different geographic regions. The main goal of this work is to provide an energy-efficient Blue Brain framework capable of managing cluster head (CH) selection and Blue Brain node clustering. The appropriate CHs are selected, and an energetic cutoff concept is developed to guarantee that energy is shared equally among the CHs and participating Blue Brain nodes. The proposed concept envisions three different kinds of Blue Brain nodes for a Blue Brain infrastructure: expert, intermediary, and normal Blue Brain nodes. Level 1 Blue Brain nodes are regarded as normal nodes; level 2 nodes are regarded as intermediate Blue Brain nodes; and level 3 nodes are regarded as expert Blue Brain nodes. Level 1 Blue Brain nodes use the least amount of energy. The outcomes of the simulation demonstrate that the recommended strategy outperforms other existing methods.

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A Survey of Secured Cluster Head: SCH Based Routing Scheme for IOT Based Mobile Wireless Sensor Network

Cited by 9 publications

References 38 publications

Blue Brain Based Clustering Protocol for Mobile Wireless Sensor Networks

Blue Brain Based Clustering Protocol for Mobile Wireless Sensor Networks

CSCRT Protocol with Energy Efficient Secured CH Clustering for Smart Dust Network Using Quantum Key Distribution

Energy capable protocol for heterogeneous blue brain network

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