A novel energy consumption model using Residual Energy Based Mobile Agent selection scheme (REMA) in MANETs

Valikannu, R.; George, Adrian V.; Srivatsa, S. K.

doi:10.1109/spin.2015.7095410

Cited by 11 publications

(5 citation statements)

References 9 publications

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“…A few work had been done on the development of models to obtain these parameters in mobile network. Example is the work of Valikannu et al where an energy consumption model using residual energy‐based mobile agent selection scheme for MANETs is proposed. Due to the random mobility of nodes in MANET, there are chances that route failure may occur during the data transmission.…”

Section: Related Workmentioning

confidence: 99%

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

Olakanmi

Odeyemi

Abbas

2020

Engineering Reports

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Mobile wireless sensor network (MWSN), as a backbone of most communication and embedded systems, is characterized by low data delivery as a result of the energy constraint and in‐deterministic movement of the nodes. To select optimal route path for a reliable data routing, protocols need to select neighbouring nodes with low mobility and residual energy parameters along the route. However, obtaining these parameters from the targeted nodes may encourage mischievous nodes to manipulate their energy and mobility parameters in their favor, leading to the selection of non‐optimal route path and/or exposing the network to other attacks. Rather than depending on the targeted nodes for these parameters, they can be accurately and securely obtained by sink node or base station using effective predictive models. However, most of the existing predictive models engaged by MWSN routing protocols either provide only the energy level or mobility factor of the nodes for optimal route path selection. This, therefore, reduces the reliability of the obtained optimal route paths in terms of data delivery. In this article, we propose predictive models for an accurate prediction of mobility and residual energy parameters of nodes in MWSN for efficient route management. The models are simulated on an existing MWSN protocol to determine their performance. The simulation results show that the adoption of these models in the development of routing protocol will not only lead to optimal route paths' selection but also enhance data delivery rate in MWSN.

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Section: Related Workmentioning

confidence: 99%

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

Olakanmi

Odeyemi

Abbas

2020

Engineering Reports

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“…The network lifetime can be increased by implementing energy efficient algorithms for routing [25]. Hierarchical approach of mobile agent based layers to optimize load balancing was developed for a large scale network, which plays a momentous role in reduced energy [26].…”

Section: B2 Networkmentioning

confidence: 99%

The Internet of Things Model Architectures for Customized Applications: A Review

Kavitha

Vallikannu

2019

International Journal of Simulation: Systems, Science &Amp; Technology

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The world is moving towards autonomous systems and hence all systems need an intelligent feedback control mechanism to achieve their potential for various applications. IoT is one of the leading technologies that can transform the current trends which will shape the future of industry and business in the coming years. As seen since 2017 IoT has converged with Block-chain technology which is used to track and coordinate billions of smart objects, facilitating transparency of transactions and providing better security and privacy by using efficient cryptographic algorithms. Different technologies are utilized to connect the different parts of IoT to the sensors which includes: Ethernet, Bluetooth, Wi-Fi, Wi-Max, Long Term Evolution (LTE) and the latest technology of Li-Fi. Interoperability and standardization of IoT devices and protocols are key challenging issues which deter the end users to select consumables of their choice and choose service providers based on their area and requirements. However, numerous problems and challenges raised by IoT need more attention in order for impending benefits to be comprehended. IoT has the potential to enhance customer relationships and boost the growth of business by improving quality, productivity and reliability while reducing costs, risk and accidents. This paper provides an overview of IoT and its architecture and applications, such as fully automated smart industries, smart cars and home security.

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“…In [18] authors proposed a novel energy consumption model using Residual Energy based Mobile Agent selection scheme (REMA). In this by sharing topology information among the nodes, mobile agent dynamically select appropriate upper layer agents for reliable data transmission.…”

Section: Related Workmentioning

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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A novel energy consumption model using Residual Energy Based Mobile Agent selection scheme (REMA) in MANETs

Cited by 11 publications

References 9 publications

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

The Internet of Things Model Architectures for Customized Applications: A Review

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

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