An Enhanced GEAR Protocol for Wireless Sensor Networks

Priyadarshi, Rahul; Soni, Surender Kumar; Sharma, Prashant

doi:10.1007/978-981-13-0776-8_27

Cited by 29 publications

(5 citation statements)

References 11 publications

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“…The performance assessment criteria used in the study are as follows: PDF/PDR overhead, delay, transmission and routing. The authors of [21][22][23][24] described the M-GEAR protocol, which uses a gateway node to lower the consumption of energy of a sensor network. This method led to better Cluster Head distribution across the WSN.…”

Section: Related Workmentioning

confidence: 99%

Impact of Network Size on Routing Protocols Performance in Wireless Sensor Network: A Simulation

Kanojia Sindhuben Babulal, Bobby Sharma, Vikas Rathi

2024

jes

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Wireless sensor networks (WSNs) are a decentralized kind of network which is equipped with sensor nodes and is rapidly being utilized to intelligently monitor different environmental conditions at a minimal cost. Sensor nodes are often battery-powered and the essential issue to address is how to decrease node energy consumption so that the network lifetime may be prolonged to realistic lengths. Routing is one of the primary operations performed within the network which consumes a sufficient amount of energy. Therefore, it is very much essential to consider the finest routing protocol so that it consumes less energy. In this article, we look at several routing protocols used in WSNs, including AODV, DSDV, DSR, OSLR and M-GEAR. Furthermore, we studied the execution of selected protocols based on network factors such as network latency, packet delivery ratio, and network throughput against multiple network sizes. The simulation findings show that protocol performance varies depending on network size and that selecting the optimum protocol based on network parameters is also crucial.

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Section: Related Workmentioning

confidence: 99%

Impact of Network Size on Routing Protocols Performance in Wireless Sensor Network: A Simulation

Kanojia Sindhuben Babulal, Bobby Sharma, Vikas Rathi

2024

jes

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“…While this data might eventually lead to considerable improvements in healthcare delivery, it also has the potential to overwhelm healthcare systems. It may seem like searching for a needle in a haystack among all this information [132,133]. To solve this problem, we need to use machine learning and other types of high-level data analysis.…”

Section: Data Overloadmentioning

confidence: 99%

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Priyadarshi,

Gheisari

2024

Preprint

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The emergence of Internet of Things (IoT) devices is revolutionizing healthcare. This dynamic healthcare environment relies on Internet of Healthcare Things (IoHT) and Internet of Medical Things (IoMT) technologies. Economic, social, and technological opportunities from the IoHT are transforming healthcare systems. This article covers the history, present condition, and future prospects of IoHT, as well as its topologies, platforms, services, applications, market trends, and solution types. It examines security issues, requirements, and a threat taxonomy, studying smart healthcare privacy and security. It explores future research and the challenges IoHT-based solutions face. International health rules and regulations based on the IoT and their social and economic effects on long-term development are also examined. Integrating IoMT into healthcare infrastructures enhances scalability, efficiency, reliability, and accuracy. Through communication networks and data-processing algorithms, IoMT creates smart hardware and software platforms that enhance decision-making. IoMT devices' low resources raise privacy and security concerns. Security and privacy issues are organised by healthcare IoMT adoption in this study. We give an extensive attack taxonomy against the IoMT infrastructure, encompassing devices, security mechanisms, and their pros and cons. Furthermore, it describes the privacy and security requirements for any unique security solutions against IoMT's multiple attack vectors. This article explains the complicated difficulties, security concerns, and future research pathways needed to safeguard and ensure the long-term expansion of these game-changing technologies in the healthcare ecosystem.

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“…Hence lifetime of those sensor nodes is less which further reduces the lifetime of the over-all network. This singularity of irregular energy consumption degrees is named as energy hole issue [11] [12][13]that may outcome quick dysfunction of the whole network, although other portions of the system still have loads of energy [14]. Figure 1 reflects that nodes in the blue region have died because they are nearer to the sink and discharging their energy in rapid fashion.…”

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confidence: 99%

Reduction of Energy Hole in WSN

2019

IJEAT

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Energy hole problem in the wireless sensor network (WSN) is a critical issue due to the energy discharge of the sensor nodes in a rapid manner which lies closer to the sink. This is because of the fact that nearer sensor nodes send their own information as well as the information received from other regions to the sink. After sometime these sensor nodes start losing their power levels and become incapable to transfer data to sink and perform other activities despite the fact the energy of nodes in other regions are still unused which further disturbs the network performance. In this article, we have proposed a Concentric Layered Hexagonal Network Division Approach (CLHND) for solving energy hole issue. Initially, the network is divided into concentric hexagons and each hexagon act as a different layer. After that, each hexagon is divided into six equal portions. In the subsequent stage, the larger layer will be selected from all other layers. Now to decrease additional energy discharging from this layer, numerous sensor nodes positioned. In the final phase to prevent the energy hole issue, a suitable directing and ordering have been done which further improves network lifetime. The simulation results showed that the proposed CLHND approach has resolved the energy hole issue as compared to the existing techniques such as HRTBR and SEHP.

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An Enhanced GEAR Protocol for Wireless Sensor Networks

Cited by 29 publications

References 11 publications

Impact of Network Size on Routing Protocols Performance in Wireless Sensor Network: A Simulation

Impact of Network Size on Routing Protocols Performance in Wireless Sensor Network: A Simulation

Security and Privacy in Machine Learning for IoHT and IoMT: A Review

Reduction of Energy Hole in WSN

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