Delay-aware heterogeneous cluster-based data acquisition in Internet of Things

Ramachandran, Nandhakumar; Varalakshmi, P.

doi:10.1016/j.compeleceng.2017.03.018

Cited by 17 publications

(14 citation statements)

References 6 publications

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“…The heterogeneous data are aggregated and then transmitted using Bluetooth devices, watches, and tablets for storing, processing, and providing services to the IoT users. Introduction of delay‐aware heterogeneous cluster‐based data acquisition for the formation of clusters ensures the coverage of network field while a multifarious sensor‐based cluster formation algorithm is used for handling of sensors . Energy consumption rate‐based stable election protocol selects the CHs using the weights of election probabilities of sensor nodes.…”

Section: Related Workmentioning

confidence: 99%

“…Introduction of delay-aware heterogeneous cluster-based data acquisition for the formation of clusters ensures the coverage of network field while a multifarious sensor-based cluster formation algorithm is used for handling of sensors. 9 Energy consumption rate-based stable election protocol selects the CHs using the weights of election probabilities of sensor nodes. Network lifetime, stability period, and throughput are more due to balanced energy consumption rate.…”

Section: Validationmentioning

confidence: 99%

“…Here, m and m o are the fractions of the total number of sensor nodes, which are advanced and superadvanced ones. Out of the total nodes, the percentage of forming CHs is depicted by p. In three level hexagonal heterogeneous broad transmission distance protocol (3L-HEXA-HTBTDP), selection criteria for CHs are given by Equations (7), (8), and (9). The new modified thresholds for the selection of normal, advanced, and superadvanced nodes as CHs, respectively, are as follows:…”

Section: L-hexa-htbtdp For Heterogeneous Wsn For Iotsmentioning

confidence: 99%

“…In the flowchart shown, CHs are elected among normal, advanced, and superadvanced nodes. They are selected using thresholds defined in above Equations (7), (8), and (9). Here, r is given as the current round for which the network has been in operation, while r max is the maximum number of rounds.…”

Section: Broad Transmission Distance Of the Fieldmentioning

confidence: 99%

“…Creation of a world in which devices can interact with each other and work according to the instructions of users is the purpose of IoTs. There are mainly three layers in IoT architecture as the application layer, network layer, and physical layer . Battery constraint is a big problem in WSNs.…”

Section: Introductionmentioning

confidence: 99%

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Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

Shrivastav

Kulat

2018

Int J Communication

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Summary Multilevel heterogeneity is the present demand of wireless sensor networks as well as internet‐of‐things for balanced energy consumption of the network systems. In this paper, three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) is introduced for increasing the energy efficiency of the network. Normal, advanced, and superadvanced sensor nodes in a hexagonal field represent three level heterogeneity. These nodes are elected as cluster heads (CHs) on the basis of new thresholds, thus transferring the collected data to the base station. The protocol is beneficial in cellular communication and web‐of‐things applications to fulfill the high energy requirements of the wireless systems. The scalability is done here for perceiving the differences in the application of proposed algorithm 3L‐HEXA‐HTBTDP on different number of sensor nodes with variable values of initial energies. This is a promising approach to achieve reliable communication, coverage, and connectivity among sensor nodes of the hexagonal field. The scheme is evaluated through exhaustive simulation using Matlab. It is compared with the previous approaches of clustering implemented on the hexagonal field. Different performance parameters like alive node metrics, stability period, network lifetime, residual energy, and variance of energy are used for benchmarking the results of 3L‐HEXA‐HTBTDP with three level hexagonal stable election protocol (3L‐HEXA‐SEP) and three level hexagonal energy efficient heterogeneous clustered scheme (3L‐HEXA‐EEHC). In general, it is observed that the proposed 3L‐HEXA‐HTBTDP outperforms other existing protocols.

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Section: Related Workmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

Section: L-hexa-htbtdp For Heterogeneous Wsn For Iotsmentioning

confidence: 99%

Section: Broad Transmission Distance Of the Fieldmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

Shrivastav

Kulat

2018

Int J Communication

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Node placement optimization using particle swarm optimization and iterated local search algorithm in wireless sensor networks

Chelbi

Dhahri

Bouaziz

2021

Int J Communication

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Summary Coverage and connectivity are the two most challenging issues in target‐based wireless sensor networks (WSNs). For that, node placement is one of the fundamental concerns that affect the performance of coverage and connectivity in WSN. This paper introduces a new approach by combining particle swarm optimization and iterated local search (PSO‐ILS) to have an optimum coverage and connectivity rate with the minimum number of nodes. In one side, to maintain the full coverage of targets, the PSO‐ILS is used to deploy the minimum number of sensor nodes. In other side, to achieve the full connectivity, the optimal position determination (OPD) algorithm was conceived to identify the optimal candidate positions which can be used by the PSO‐ILS to place the minimum number of relay nodes. The obtained results considered over a number of runs are compared with canonical PSO, differential evolution (DE), and genetic algorithms (GAs). The outcomes derived from this comprehensive analysis determine that PSO‐ILS provides an effectual improvement in contrary to the methods PSO, DE, and GA in terms of the selected potential positions to ensure full coverage of target points and the number of relay nodes required to achieve full connectivity.

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Virtualization Approach for Machine-Type Communications in Multi-RAT Environment

Gavrilovska

Rakovic

Ichkov

2018

Wireless Pers Commun

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Delay-aware heterogeneous cluster-based data acquisition in Internet of Things

Cited by 17 publications

References 6 publications

Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

Node placement optimization using particle swarm optimization and iterated local search algorithm in wireless sensor networks

Virtualization Approach for Machine-Type Communications in Multi-RAT Environment

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