OTP-ER: an ordered transmission paradigm for effective routing in IoT based wireless sensor networks

Kumar, Chandan; Chakravarthy, Vasu; Ramana, Kadiyala; Maddikunta, Praveen Kumar Reddy; Xin, Qin; Narayana, G. Surya

doi:10.1007/s11082-022-03837-y

Cited by 6 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The clustering procedure divides the sensor nodes into smaller groups, or clusters, each of which is headed by a CH. The Cluster Head (CH) combines data from all of the cluster's sensor nodes and sends it to the Base Station (BS) [9,10]. The acquired data from the CH is sent to the BS either immediately or via intermediary CHs and/or sensor nodes; this is known as multi-hop communication.…”

Section: Introductionmentioning

confidence: 99%

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Saritha,

Reddy

2024

JAIT

View full text Add to dashboard Cite

In recent years, Wireless Sensor Network (WSN) has arisen as a practical option for many sectors needing smart technology. Despite its impressive credentials, Wireless Sensor Networks' excessive need for power remains a significant limitation. There is a pressing need to create a trustworthy Wireless Sensor Network with efficient energy and network lifetime due to the proliferation of tiny sensors with incomplete resources. One of the actual ways to deal with these matters is to divide the nodes into clusters. So, it is crucial to use existing energy efficiently to prevent energy waste. In this study, we suggest an Energy-Efficient Hybrid Clustering Algorithm to reduce the high-energy ingesting and increase the network lifetime of Wireless Sensor Networks. The position and speed of a gas molecule, among other Kinetic Gas Molecule Optimization particle characteristics, are initially determined by calculating their kinetic energy. Hybridization of Kinetic Gas Molecule Optimization arises from Kinetic Gas Molecule Optimization's faster convergence in space. Pelican Optimization Algorithm is used to fix the problems with Kinetic Gas Molecule Optimization by changing its inertia weight. Throughput the number of live/dead nodes are all validated against other prominent meta-heuristic methodologies in a MATLAB environment simulation of the proposed Kinetic Gas Molecule Optimization-Pelican Optimization Algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Saritha,

Reddy

2024

JAIT

View full text Add to dashboard Cite

show abstract

“…The information is then analysed by a computer model, which makes precise judgements and perhaps initiates robotic processes. The Internet is used for machine-to-machine communication; however, this exposes MTC systems to a wide variety of security threats, with, but not incomplete to, attacks, network exploitation, injection attacks [4,5]. Furthermore, the MTC system's many devices collect an enormous variety of data (industrial-critical data) that needs regular monitoring to prevent data breaches and tampering.…”

Section: Introductionmentioning

confidence: 99%

Routing Attack Detection Using Ensemble Deep Learning Model for IIoT

Vatambeti¹,

Mamidisetti²

2023

IDA

View full text Add to dashboard Cite

Smart cities, ITS, supply chains, and smart industries may all be developed with minimal human interaction thanks to the increasing prevalence of automation enabled by machine-type communication (MTC). Yet, MTC has substantial security difficulties because of diverse data, public network access, and an insufficient security mechanism. In this study, we develop a novel IIOT attack detection basis by joining the following four main steps: (a) data collection, (b) pre-processing, (c) attack detection, and (d) optimisation for high classification accuracy. At the initial stage of processing, known as "pre-processing," the collected raw data (input) is normalised. Attack detection requires the creation of an intelligent security architecture for IIoT networks. In this work, we present a learning model that can recognise previously unrecognised attacks on an IIoT network without the use of a labelled training set. An IoT network intrusion detection system-generated labelled dataset. The study also introduces a hybrid optimisation algorithm for pinpointing the optimal LSTM weight when it comes to intrusion detection. When trained on the labelled dataset provided by the proposed method, the improved LSTM outperforms the other models with a finding accuracy of 95%, as exposed in the research.

show abstract

“…The significant QoS routing protocol limitations are resource management and energy conservation. As a result of the needs for new procedures, optimization routing methods that depart from conservative choice of paths have been reported to have more energy and QoS performance 22 . This inspired us to do the research.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

Kumar

2023

Int J Communication

View full text Add to dashboard Cite

SummaryInternet of Things (IoT) is a network of smart things that connects people and objects for gathering and exchanging information by means of embedded sensor. IoT‐based wireless sensor network (WSN) nodes are monitored as a resource parameter at the variety of methods, including resource calculation, energy resource, and storage resource, with multipath routing protocols necessary to enable extended network lifespan and achieve high energy utilization. The existing routing protocols did not provide optimal path from the multipath route. Hence, in this manuscript, a Hybrid Marine Predators and Border Collie Optimization algorithm is proposed for multipath routing in IoTs. The main aim of this endeavor is to “increase network lifetime.” IoT is simulated initially and multipath routing initiates in internet of things network. Multipath routing is achieved by proposed Hyb‐MP‐BCOA; this is the combination of Hybrid Marine Predators Algorithm and Border Collie Optimization algorithm. The proposed Hyb‐MP‐BCOA algorithm chooses the optimum path from the multiple path obtainable for routing, depending upon fitness parameter, like context awareness, network lifetime, residual energy, trust, and delay. Based on the fitness parameter, the optimal path is selected by using Hyb‐MP‐BCOA algorithm. Finally, the proposed Hyb‐MP‐BCOA‐MR‐IoT model is applied in MATLAB, and efficacy of proposed technique is estimated by using various performance metrics, like drop, normalized network energy, lifetime of network, delay, throughput, energy consumed, packet delivery ratio, and number of sensor nodes versus aggregation level. The proposed method attains lower delay of 14.285%, 50%, 53.846%, and 57.142%, lower packet drop of 14.285%, 50%, 53.846%, and 57.142%, lower energy consumption compared with existing methods such as multiobjective sun flower optimization with gray wolf optimizer (GWO) for multipath routing in IoT (SFO‐GWO‐MR‐IoT), multiobjective Whale Lion Fireworks optimization algorithm and fitness function for multipath routing in IoT (WLFA‐MR‐IoT), multipath routing in IoT using shuffled frog leaping algorithm (SFLA‐MR‐IoT), and multipath routing in IoT using hybrid Whale Optimization Algorithm‐Moth Flame Optimization (MFO)(hyb‐WOA‐MFO‐MR‐IoT). Finally, the safe communication is attained in the IoT network.

show abstract

OTP-ER: an ordered transmission paradigm for effective routing in IoT based wireless sensor networks

Cited by 6 publications

References 30 publications

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Minimizing the Energy Consumption and Exploiting the NLT by E2HCA Model in WSN

Routing Attack Detection Using Ensemble Deep Learning Model for IIoT

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

Contact Info

Product

Resources

About