Designing Energy-Efficient Topologies for Wireless Sensor Network: Neural Approach

Patra, Chiranjib; Roy, Anjan Guha; Chattopadhyay, Samiran; Bhaumik, Parama

doi:10.1155/2010/216716

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…In [13], the author proposed an SOFM topology building (SOFMTB) algorithm to optimise energy in WSNs. Unlike LSTM, the SOFM model is a spatial technique that provides a suitable network configuration for a given problem.…”

Section: Related Workmentioning

confidence: 99%

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory

Al-Nader,

Lasebae,

Raheem

et al. 2023

Electronics

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The multiple objective optimisation (MOO) challenges encountered in the context of wireless sensor networks (WSNs) present a formidable NP-hard problem. These issues primarily arise from the constraints imposed by critical factors such as connectivity, coverage, and, most notably, energy consumption. Simultaneously fulfilling these three requirements is no longer considered the standard approach for enhancing system dependability. To illustrate, a prospective solution may optimise one or two of these requirements while bolstering overall network energy efficiency. Nonetheless, prior endeavours documented in the extant literature reveal unexplored avenues for enhancement. Hence, this paper introduces a new methodology aimed at alleviating MOO concerns and thereby enhancing the quality of service (QoS) in WSNs. A long short-term memory (LSTM) model is proposed as an analytical tool to deliver an energy-efficient scheduling solution that aligns and optimises WSN parameters, striving to attain the most favourable system performance. The LSTM algorithm’s effectiveness is assessed through the iterative application of periods, confirming the desired QoS levels. The unique feature of LSTM lies in its capability to observe specific event sequences and subsequently establish them as the system’s default configuration for its entire operational lifespan. Once these favourable parameters are identified, LSTM automatically ensures consistent service availability and reliability throughout the network’s lifespan. The results obtained demonstrate the superiority of the proposed LSTM-based scheduling algorithm in comparison to the self-organising map (SOFM)-based node scheduling algorithm. The LSTM-based approach outperforms the SOFM-based alternative by a remarkable 75% in terms of coverage and exhibits a 20% enhancement in network lifetime, all while maintaining equivalent levels of connectivity (i.e., 99%) in both algorithms.

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Section: Related Workmentioning

confidence: 99%

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory

Al-Nader,

Lasebae,

Raheem

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

“…In ref. [21], the author proposed the SOFM topology building (SOFMTB) algorithm to optimize energy in WSNs. The work utilized the SOFM technique to adjust the clusters based on energy levels for efficient dissemination of data over the network.…”

Section: Related Workmentioning

confidence: 99%

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical WSN Using Spatial Self-Organizing Feature Map

Al-Nader,

Lasebae,

Raheem

2023

Electronics

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Technological advances in the internet of things (IoT) allowed a low-cost, yet small sensor device to operate with limited power in a dynamic harsh environment where human intervention is impossible. The wireless sensor network (WSN) is an example of the IoT in which physical devices’ software and sensors can interconnect to provide application services. It is important that such applications be dependable to meet the required quality of service (QoS) and function as expected. Consequently, the multi-objective optimization (MOO) problem in WSNs aims to address the trade-off among coverage, connectivity, and network lifetime requirements. Node scheduling is one approach of many used to optimize energy in WSNs. The contribution of this work is the proposal of a self-organizing feature map (SOFM) to enhance the node scheduling in WSNs. The proposed SOFM node-scheduling algorithm aims to spatially explore the state space domain and obtain an optimal solution. In our experiment, the proposed SOFM node-scheduling algorithm is evaluated against a comparable algorithm, namely the BAT node-scheduling algorithm, via MATLAB simulator. The results showed that the SOFM node-scheduling algorithm outperformed the latter by 27% and 28% for the maximum and minimum coverage, respectively, with similar performance of 99% of connectivity and network lifetime.

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“…When the connection is shared between the various nodes at this time at a time only one node has the permission to send the data to the other node for that it must be made sure that the channel or link is free or not. This should be possible with the assistance of sending the request to send signal referred as rts to the receiver node and get back clear to send denoted as cts from the receiver side to the sender [14]. For this kind trading the signs between two nodes, both the nodes has to communicate with each other.…”

Section: Mobilitymentioning

confidence: 99%

Introducing Energy Efficient Strategies of Virtual Backbone Nodes in Wireless Sensor Network

Kumar¹,

Sharma²

2016

IJCA

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Wireless Sensor Network is a Research issue in which construction of Virtual Backbone schemes over multi-hop wireless sensor networks. This paper investigates the problem of connectivity for random placement of nodes by minimizing active sensor nodes. Several backbone construction techniques have been reported in recent years regarding the routing problem of the ad hoc wireless sensor networks. As the network size is growing in the physical world, redundancy in nodes also increased because of this the redundancy it affects the WSN performance. Hence the classification of all these backbone construction techniques is done, which are based on the connected dominating set (CDS) and other techniques. A generalized scheme to be more robust, having lesser number of Backbone nodes with higher mobility is proposed.

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Designing Energy-Efficient Topologies for Wireless Sensor Network: Neural Approach

Cited by 8 publications

References 10 publications

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical Wireless Sensor Networks Using Long Short-Term Memory

A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical WSN Using Spatial Self-Organizing Feature Map

Introducing Energy Efficient Strategies of Virtual Backbone Nodes in Wireless Sensor Network

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