Clustered Routing Method in the Internet of Things Using a Moth‐Flame Optimization Algorithm

Sadrishojaei, Mahyar; Navimipour, Nima Jafari; Reshadi, Midia; Hosseinzadeh, Mehdi

doi:10.1002/dac.4964

Cited by 25 publications

(12 citation statements)

References 46 publications

(44 reference statements)

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“…The proposed Energy Aware Cluster-based Routing in IoT was implemented using MATLAB. The proposed Custom Honey Badger and Coot Optimization (CHBCO) model is validated against existing classifiers such as Elephant Herding Optimization (EHO), Harris Hawks Optimization (HHO), COOT, Honey Badger Algorithm (HBA), Moth Flame Optimization (MFO) [29], Delay Constrained Particle Swarm Optimization (DCPSO) [30], Hunger Game Search (HGS), Cyclic Rider Optimization Algorithm (C-ROA) [26], Over taker Assisted Wolf Update (OA-WU) [27] and Sandpiper Optimization with Cycle Crossover Process (SOCCP) [28], respectively. Additionally, the examination was done with respect to Alive Nodes, Distance, Link Quality and Normalization Energy.…”

Section: A Simulation Proceduresmentioning

confidence: 99%

Energy aware Cluster based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks

Gorikapudi¹,

Kondaveeti²

2023

Preprint

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In order to prevent the overloading, the routing algorithm aids in building productive paths both within and between clusters. When sending information from the source IoT device to a base station, not all IoT devices are utilized in the path. We introduced an energy aware cluster-based routing in this paper, in which Improved Fuzzy C-means model plays a major role in clustering initially. Meanwhile, the clustering procedure considers the factors like energy and distance. Subsequent to the clustering process, optimal routing will be takes place by a new hybrid optimization algorithm named Custom Honey Badger and Coot Optimization (CHBCO) that combines the models like Honey badger optimization and Coot optimization model, respectively. For routing, the model considers the constraints like Energy as well as link quality. Also, this model establishes the fault tolerance method, which ensures that the network will continue to operate normally even in the situation of a CH failure. During this, the cluster members switch to another CH. The performance of proposed CHBCO based routing model is compared over existing models with respect to convergence rate, distance evaluation, energy, alive nodes, distance, normalized energy and link quality under five scenarios such as 100, 500, 1000, 1500, and 2000. Moreover, the proposed model obtained 56 alive nodes in the round 1500 for scenario 1(i.e node 100). Also in the round 1500, the CHBCO model obtain a minimum distance as 25 however the existing models achieve higher distance like EHO as 50, HHO as 70, COOT as 40, HBA as 60, MFO as 75, DCPSO as 150, and HGS as 85 for the node setup 1000. The proposed method achieve a better normalized energy as 0.29 in the 2000 round along with node setup 100, while the conventional models reach the lowest normalized energy. Moreover, the CHBCO method fine link quality values such as 0.96, 0.96, 0.95, 0.97, and 0.97 at the node setups of 100, 500, 1000, 1500, 2000 respectively.

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Section: A Simulation Proceduresmentioning

confidence: 99%

Energy aware Cluster based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks

Gorikapudi¹,

Kondaveeti²

2023

Preprint

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“…Clustering is a valuable data collecting technique for the IoT that reduces energy usage selectively by grouping IoT nodes into clusters [30]. The cluster head has complete control over all cluster nodes and is responsible for all intracluster and intercluster communication.…”

Section: Related Workmentioning

confidence: 99%

Optimized Embedded Healthcare Industry Model with Lightweight Computing Using Wireless Body Area Network

Saba

Haseeb

Bahaj

et al. 2022

Wireless Communications and Mobile Computing

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Wireless technology is offering numerous growth to develop communication systems. The Internet of Things (IoT) is combined with the sensing ecosystem to transfer and process the physical environment. Recently, IoT devices have collaborated with wireless devices to improve embedded medical applications. Many solutions are proposed to decrease the power consumption of the sensing ecosystem and support the health industry. However, optimizing the transformation of collected data with lightweight power consumption is still a burning research issue. Moreover, uncontrolled network devices and healthcare professionals are remotely accessed by such embedded systems. Thus, securing sensitive information is also a significant factor for mobile communications. Therefore, this research presents an optimized embedded healthcare industry model with lightweight computing using a wireless body area network (WBAN), aiming to lessen the control overheads and improve the power consumption in mobile e-health services. To begin, it employs an optimal learning algorithm to lower the management costs of embedded systems in order to transform and administer the electronic health record (EHR) more efficiently. Second, with the help of trustworthy gateways, it delivers a safe EHR algorithm as well as lightweight computing resources for embedded systems. The proposed model is tested with a variety of experiments and demonstrates its significant improvement over state-of-the-art techniques.

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“…Also, telecommuting is a process that has found its way into business and will continue to do so as the COVID-19 disappears and become a common model in the near future. Meanwhile, the development of Internet of Things (IoT) technology plays a significant role in the development of telecommuting model and allows employees to proceed without the need for physical presence and with high flexibility and adaptability (Sadrishojaei et al. , 2021a, b).…”

Section: Introductionmentioning

confidence: 99%

Antecedents and consequences of telecommuting on public organizations in Iran: the case of west Azerbaijan province

Khodaparasti

Garbollagh

2022

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PurposeTelecommuting can reduce traffic congestion, energy consumption, prevalence and a death toll of COVID-19 among employees due to less transportation and fewer physical contacts among employees, on the one hand, and efficiently develop their use of information and communications technology, on the other hand. In this regard, the present study aims to explore antecedents and consequences of telecommuting in public organizations.Design/methodology/approachThe study used a descriptive survey method to collect data. The statistical population includes all employees of government organizations in West Azerbaijan province in 2020, which according to the collected information, their number is equal to 63,079 employees. Based on Cochran's formula, a sample size of 686 people was obtained; stratified random sampling was used to select sampling. The process of calculating the sample volume was such that after referring to the preliminary sample and processing the collected data, the variance of the given answers was approximately 0.446. After obtaining the variance of the data, assuming a maximum acceptable error of 5% and a significance level of 0.05, the Cochran's formula calculated the sample size to be 686 people. In order to collect and measure data for the study, a standard questionnaire and the collected data were analyzed using structural equation modeling.FindingsFindings indicate that there is no meaningful relationship between the employees' physical job conditions or the quality of their life with telecommuting and that telecommuting does not have a significant effect on their life. However, job burnout, training and telecommuting experience have a significant positive effect on telecommuting, which in turn has a positive and significant effect on job security, job flexibility, organizational performance and overall productivity of employees.Research limitations/implicationsThis research is a cross-sectional study, and its data have been collected in a certain period of time, while longitudinal research can provide a richer result. Future research can benefit from the impact of employee isolation and telecommuter organizational commitment.Originality/valueThis study hopes to contribute to the increase of the scientific knowledge in the telecommuting field and to allow organizations to rethink the telecommuting strategies to optimize resources and costs and to improve the organization's productivity without harming the quality of life and well-being of their workers.

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Clustered Routing Method in the Internet of Things Using a Moth‐Flame Optimization Algorithm

Cited by 25 publications

References 46 publications

Energy aware Cluster based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks

Energy aware Cluster based Routing Algorithm for Optimal Routing and Fault Tolerance in Wireless Sensor Networks

Optimized Embedded Healthcare Industry Model with Lightweight Computing Using Wireless Body Area Network

Antecedents and consequences of telecommuting on public organizations in Iran: the case of west Azerbaijan province

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