Compartmental Modeling of Opportunistic Signals for Energy Efficient Optimal Clustering in WSN

Kumar, Sudhir

doi:10.1109/lcomm.2017.2763948

Cited by 26 publications

(14 citation statements)

References 9 publications

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“…Therefore, their sustenance to continue with maximum operational rounds of data aggregation can never be guaranteed by such approaches. Approaches such as in previous studies 25,28,[30][31][32][33][34][35]38,39 have claimed of optimizing clustering performance by introducing a cluster head selection process; however, such selection process does not prove the longevity of cluster head operation in case of random dispersal of cluster head. • Few studies towards topology control: Any new and unique process introduced in clustering also affects the topology.…”

Section: Research Problemmentioning

confidence: 99%

“…Study considering the case of the underwater network is carried out by Yadav and Kumar where clustering is optimized based on wave‐based factors (electrical and optical). Comprehensive modeling toward clustering operation has been presented by Kumar that uses an attenuation framework towards investigating the opportunistic power of signal with respect to the spatial distance of the node. The model presented an energy minimization solution by computing an optimal number of clusters.…”

Section: Related Workmentioning

confidence: 99%

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Interstellar‐based topology control scheme for optimal clustering performance in WSN

Jyothi

Usha

2020

Int J Communication

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Summary Clustering is one of the essential operations in wireless sensor network (WSN) to ensure organized data aggregation followed by energy efficiency. However, obtaining optimal clustering performance is yet an unsolved problem in WSN. Review of existing approaches towards cluster optimization shows that effective balance between energy efficiency and topology control is still missing. Therefore, the proposed system presents a unique topology control mechanism using a novel concept of interstellar orientation toward optimizing the clustering performance in WSN. Adopting an analytical research methodology, the proposed system introduces two interstellar‐based topology control system, which targets the maximum saving of resource consumption of the cluster head. The simulated outcome of the study shows that the proposed topology control system offers significant energy conservation performance in comparison to the existing hierarchical clustering scheme in WSN.

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Section: Research Problemmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Interstellar‐based topology control scheme for optimal clustering performance in WSN

Jyothi

Usha

2020

Int J Communication

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“…The cooperative integration and strategy satisfy certain independent concurrent users request that control energy efficiency and minimize the WSN service problem. Compartmental clustering model of an opportunistic signal in WSN for nodes energy efficiency has been proved by [11]. The opportunistic signal of the optimal cluster partition is obtained through the compartmental model rather than the state-of-the-art attenuation models.…”

Section: Energy Efficiency In Wsn Nodesmentioning

confidence: 99%

Resourceful Residual Energy Consumption in TDMA Scheduling for IoT-based Wireless Sensor Network

Rahiman¹,

Islam²,

Derahman³

2019

Adv. sci. technol. eng. syst. j.

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Recently, wireless sensor network (WSN) gets more concern due to the robustness in the latest communication technology iteration such as big data, IoT and 5G. Such daily usage of these technologies includes smart home, smart farming, smart traffic control etc. Moreover, WSN becomes the best preference for mobile objects in data accumulating in a wild range area. Routing distance, signal interference and routing computational cost give a significant impact to the WSN nodes lifetime. Unsynchronized node time allocation slot and neighbor discovery are the main factors in the energy consumption issue faced by the WSN. Higher energy consumption reduces the network lifetime and WSN nodes performance. This paper discusses the optimization of energy-topology (E-T) factors for distributed time division multiplexing algorithm (TDMA) slot scheduling for high-speed data link capacity. The E-T factor is based on the influence of residual energy and topology on the time slot allocation. Both node residual energy and topology information have shown a respectable impact on the TDMA node slot allocation. Moreover, the numbers of neighbors and the network residual energy have been proved both nodes execution time and energy utilization can be reduced in the algorithm. The algorithm performance has been evaluated based on the previous experiment parameters with new high-speed data link. The experimental results have shown a significant improvement in residual energy consumption for the proposed optimized TDMA slot allocation

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“…The second one involes a backup non-renewable energy source, such as the on-grid energy that will guarantee the smooth operation of the system in case the harvested energy is insufficient [12], [13]. The third one is radio resource exchange among neighboring nodes, such as the energy cooperation scheme that can share one system's excessive energy with the other [14].To minimize the impact of dynamics of green energy sources on the network performance, the modernized electricity grid has allowed the distributed harvested green energy to be contributed back to the smart grid in exchange for on-grid energy credit [17], [18]. Consequently, in the green energy powered wireless access networks, the smart grid is an "unlimited energy storage device" with back up ongrid power supply.…”

Section: Elements Of Resource Allocationmentioning

confidence: 99%

Energy Consummation in cognitive radio network using Different Methods

Gunjal¹,

Sharama²,

Todmal³

2019

IJEAT

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The cognitive radio and resource allocation techniques have been proposed for efficiently utilizing the radio resources. Cognitive radio is an emerging technology intended to enhance the utilization of the radio frequency spectrum and allocate the available resources correctly. The cooperative communication system, with the same total power and bandwidth of legacy wireless communication systems, can increase the data rate of the future wireless communication system. A combination of cognitive radio with resource allocation can further improve the future wireless network performance and reduces the energy consummation. Efficient resource allocation in cognitive radio network (CRN) is essential in order to meet the challenges of future wireless networks. In this Paper, we are going to discuss the different Localization Techniques, objectives and protocols used in the literature for resource allocation in CRN. This paper also highlights the use of power control, cooperation types, network configurations, and Energy consummation used in CRN. Finally, directions for future research are outlined of proposed algorithms for energy minimization.

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Compartmental Modeling of Opportunistic Signals for Energy Efficient Optimal Clustering in WSN

Cited by 26 publications

References 9 publications

Interstellar‐based topology control scheme for optimal clustering performance in WSN

Interstellar‐based topology control scheme for optimal clustering performance in WSN

Resourceful Residual Energy Consumption in TDMA Scheduling for IoT-based Wireless Sensor Network

Energy Consummation in cognitive radio network using Different Methods

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