NEMA: Node Energy Monitoring Algorithm for Zone Head Selection in mobile ad-hoc network using residual battery power of node

Ghode, Sushma D.; Bhoyar, Kishor K.

doi:10.1109/wispnet.2016.7566492

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…Node Energy Monitoring Algorithm for Zone Head Selection (NEMA) improves ZRP by adding energy constraints to hence the lifetime of MANET [15]. NEMA consists of two parts.…”

Section: Hybrid Routing Protocolsmentioning

confidence: 99%

QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks

Liu

Wang

et al. 2020

Computer Communications

121

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“…Node Energy Monitoring Algorithm for Zone Head Selection (NEMA) improves ZRP by adding energy constraints to hence the lifetime of MANET [15]. NEMA consists of two parts.…”

Section: Hybrid Routing Protocolsmentioning

confidence: 99%

QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks

Liu

Wang

et al. 2020

Computer Communications

121

View full text Add to dashboard Cite

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“…Ghode and Bhoyar proposed an ahead selection process based on residential node energy in the zone. Ghode and Bhoyar [110] proposed the Node Energy Monitoring Algorithm (NEMA) to monitor changes in the energy level of nodes and select the cluster head node based on their energy.…”

Section: Geographic Routing Protocolsmentioning

confidence: 99%

Mobile Ad Hoc Network in Disaster Area Network Scenario: A Review on Routing Protocols

et al. 2021

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Disasters could cause communication systems partially or completely down. In such a case, relief operations need a rapidly deployed communication system to save lives. Exchanging information among the rescue team is a vital factor to make important decisions. Communication system required to be robust to failures, rapidly deployable, easily maintainable to provide better services. Wireless ad-hoc networks could be the choice of establishing communication with the aid of existing infrastructure in a post-disaster case. In order to optimize mobile ad-hoc network performance, address the challenges that could lead to unreliable performance is required. One and most crucial key challenge is routing information from a sender to receiver. Due to the characteristics of a disaster environment such as signal attenuation, communication links exist between rescue crew is short-lived, suffer from frequent route breakage, and may result in unreliable end-to-end services. Many routing protocols have been proposed and evaluated in different network environments. This paper presents the basic taxonomy of Mobile Ad Hoc Networks and the state of the art in routing categorizes (Proactive, Reactive, Geographic-aware and Delay tolerant Networks (DTN)). The comparison of existing routing protocols in Mobile Ad-Hoc Networks indicates that overhead in Proactive and Geographic is competitive with delay in Reactive and DTN routing.

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“…In this we use our previously designed algorithms namely Zone Head Selection Algorithm (ZHSA) which select maximum residual energy node as zone head using max-heap tree algorithm and Node Energy Monitoring Algorithm (NEMA) which monitors individual nodes energy level and assign various roles to nodes based on remaining battery power of node. These two algorithms are mentioned in [28]. The working of EE-HRP explained below:  Every node is capable of changing its transmission power level depending on the distance to the receiver.…”

Section: Proposed Optimized Ee-hrp Protocolmentioning

confidence: 99%

Optimized Energy Efficient Hybrid Routing Protocol (EE-HRP) for Minimum Battery Power Consumption in MANET

Ghode¹,

Bhoyar²

2018

IJIES

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Mobile Ad-hoc networks (MANET) are being installed in a wide range of applications like military scenarios, rescue operations, data and device networks etc. Many of these networks uses battery operated nodes. A major requirement of these networks is to wisely utilize the battery power of nodes, so that the nodes can actively participate in process of communication for maximum time span without partitioning the network. This will result into maximum network lifetime which is again main goal in ad hoc routing algorithms. To achieve this we proposed an optimized Energy Efficient Hybrid Routing Protocol (EE-HRP) which uses routing strategy that seeks to find the best balance between minimizing the power consumption and evenly using all nodes within the network to avoid early exhaustion of individual node. In EE-HRP we use multiple threshold values for remaining battery power of nodes and assign different role of each node depending on remaining battery power of the node using our Node Energy Monitoring Algorithm (NEMA). Here we also make use of our previously designed algorithm Zone Head Selection Algorithm (ZHSA) which is used to select maximum energy node as Zone Head (ZH). By doing so we prevent nodes from early battery exhaustion which results to increase network lifetime to some extent. The key factor governing the performance of optimized EE-HRP are theoretically analyzed and evaluated. The simulation results are compared with some MANET routing protocols in different network scales, taking into consideration the power consumption. The theoretical analysis and simulation results shows that our proposed optimized EE-HRP reduces total power consumption, reduces end-to-end delay, increases packet delivery ratio and achieves maximum network lifetime.

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NEMA: Node Energy Monitoring Algorithm for Zone Head Selection in mobile ad-hoc network using residual battery power of node

Cited by 8 publications

References 19 publications

QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks

QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks

Mobile Ad Hoc Network in Disaster Area Network Scenario: A Review on Routing Protocols

Optimized Energy Efficient Hybrid Routing Protocol (EE-HRP) for Minimum Battery Power Consumption in MANET

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