A Green Data Collection &amp; Transmission Method for IoT-Based WSN in Disaster Management

Nandan, Aridaman Singh; Singh, Samayveer; Malik, Arun; Kumar, Rajeev

doi:10.1109/jsen.2021.3117995

Cited by 38 publications

(12 citation statements)

References 22 publications

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“…Due to their significant impact in efficiently solving a complex problem, metaheuristic schemes like GA, DE, EP, ES, PSO, TLBO, and ant colony optimization (ACO) are being used in almost every field of engineering. These schemes have also proved their significance in the domain of IoT‐based WSNs, and hence, numerous contributions based on these techniques can be easily found in the literature like in previous studies 13–19 …”

Section: Literature Reviewmentioning

confidence: 96%

DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

Chaurasiya

Biswas

Nayyar

et al. 2023

Int J Communication

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With the evolution of technology, many modern applications like habitat monitoring, environmental monitoring, disaster prediction and management, and telehealth care have been proposed on wireless sensor networks (WSNs) with Internet of Things (IoT) integration. However, the performance of these networks is restricted because of the various constraints imposed due to the participating sensor nodes, such as nonreplaceable limited power units, constrained computation, and limited storage. Power limitation is the most severe among these restrictions. Hence, the researchers have sought schemes enabling energy-efficient network operations as the most crucial issue. A metaheuristic clustering scheme is proposed here to address this problem, which employs the differential evolution (DE) technique as a tool. The proposed scheme achieves improved network performance via the formulation of loadbalanced clusters, resulting in a more scalable and adaptable network. The proposed scheme considers multiple parameters such as nodes' energy level, degree, proximity, and population for suitable network partitioning. Through various simulation results and experimentation, it establishes its efficacy over state-of-the-art schemes in respect of load-balanced cluster formation, improved network lifetime, network resource utilization, and network throughput. The proposed scheme ensures up to 57.69%, 33.16%, and 57.74% gains in network lifetime, energy utilization, and data packet delivery under varying network configurations. Besides providing the quantitative analysis, a detailed statistical analysis has also been performed that describes the acceptability of the proposed scheme under different network configurations.

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Section: Literature Reviewmentioning

confidence: 96%

DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

Chaurasiya

Biswas

Nayyar

et al. 2023

Int J Communication

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“…Having a few more nodes with extra power is helpful in such applications to extend the network's lifespan. Similarly, various clustering-oriented approaches for enhancing network efficiency, lifetime, and stability have been proposed by several academics [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] . The most important objective in these types of protocols is to choose the cluster head (CH) with precision.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other researchers have also discussed various data collection techniques using IoT-based WSNs [23] , [24] , [25] . Singh et al.…”

Section: Literature Reviewmentioning

confidence: 99%

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A secure energy-efficient routing protocol for disease data transmission using IoMT

Singh

Nandan²,

Sikka³

et al. 2022

Computers and Electrical Engineering

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“…In disaster scenarios, a cluster-based network is proposed to bridge the possibly lengthy distance between source and destination devices. Even in the absence of a communication infrastructure, we use relay selection and D2D communication architecture to keep devices connected [11]. If the communication infrastructure issues occur during the disaster, a better way to find alternative nodes for shortest path identification and route management are predicted.…”

Section: Introductionmentioning

confidence: 99%

OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management

Raja

Logeshwaran²,

Srinivasan³

et al. 2022

Scientific Programming

131

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As an underlayment to cellular 5G communication network, device-to-device (D2D) communications will not only boost capacity utilization and power efficiency but also provide public health and public safety services. One of the most important requirements for these businesses is to have alternate access to cellular networks in the event that they are partially or completely disrupted as a result of a natural disaster. Despite limited communication coverage and bandwidth scarcity, the 3rd Generation Partnership Project (3GPP) must have developed a new device-to-device (D2D) communication method fundamental enhanced mobile that can strengthen spectral efficiencies besides allowing direct communication of gadgets in close propinquity devoid of transitory by elevated-node B (eNB). Unfortunately, enabling data transmission on a cellular connection offers a challenge in terms of two-way radio source administration, because D2D associates recycle cellular users’ uplink radio resources, which might create interference to D2D user equipment’s (DUE) receiving channels. In this study, we concentrate on optimal cluster head selection using the binary flower pollination optimization algorithm by designing an energy-efficient lifetime-aware leisure degree adaptive routing protocol named OptCH_L-LDAR. This topology is constructed with a multi-hop obliging communication system, instructed on the way to wrap an extensive remoteness connecting source and destination. The proposed OptCH_L-LDAR is compared with three state-of-art methods such as binary flower pollination (BFP) algorithm, time division multiple access (TDMA), and data-driven technique (DDT). As a result, the proposed OptCH_L-LDAR achieves 96% of energy efficiency, 89% of lifetime, 97% of outage probability, and 98% of spectral efficiency.

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A Green Data Collection & Transmission Method for IoT-Based WSN in Disaster Management

Cited by 38 publications

References 22 publications

DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks

A secure energy-efficient routing protocol for disease data transmission using IoMT

OCHSA: Designing Energy-Efficient Lifetime-Aware Leisure Degree Adaptive Routing Protocol with Optimal Cluster Head Selection for 5G Communication Network Disaster Management

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