Distributed Data Analysis with Docker Swarm Using R

Aruna, P.; Kannammal, A.; Aishwarya, .; Surya,

doi:10.1145/3293475.3293492

Cited by 2 publications

(2 citation statements)

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“…EATMAR [20] failed to examine the more objective function for achieving the efficient routing. Taylor-SHO [21] failed to determine an analysis of computation overhead. TBEBR [22] had minimum resource accessibility, partial communication as well as minimum energy constraints.…”

Section: Discussionmentioning

confidence: 99%

“…However, the EATMR approach was failed to examine the more objective function for achieving the efficient routing. Shivaraj Sharanabasappa Kalburgi and M. Manimozhi [21] implemented the integration of Taylor series and Spotted Hyena Optimization called (Taylor-SHO) for CH selection and network lifetime enhancement in WSN. Initially, the suggested approach was utilized for the efficient CH selection by the utilization of fitness estimation based on energy, distance as well as delay.…”

Section: Iiliterature Surveymentioning

confidence: 99%

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Multi-objective Trust-aware Dynamic Weight Pelican Optimization Algorithm for Secure Cluster Head and Routing Selection in WSN

Srinivasan R.

2024

jes

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Wireless Sensor Networks (WSN) is a group of Sensor Nodes (SNs) which are performed to intellect a normal singularity from an environment. The minimum resources and computational power of WSN creates vulnerable to number of security attacks. To addresses this problem, this paper proposes a Multi-objective Trust-aware Dynamic Weight Pelican Optimization Algorithm (M-TDWPOA)-based secure and energy aware multi-hop routing in WSN with the Base Station (BS). The proposed method comprises of two significant steps: Initially, dynamic energy-efficient Cluster Head (CH) selection by utilizing the multi-objective functions such as Distance between neighbor nodes, Distance between BS to CH, Energy, Centrality and Trust Threshold. Then, dynamic secure multi-hop routing is selected by the multi-objective functions such as Distance between BS to CH, Energy, Trust Threshold which is dynamically reducing the network overhead. Furthermore, a security aware multi-hop routing is employed through the different trust classes like direct, indirect, recent and authentication. The proposed M-TDWPOA approach is estimated with various performance metrics like alive nodes, dead nodes, energy consumption, Throughput and so on. The proposed M-TDWPOA achieves the minimum energy consumption of 0.4927J, 0.4851J, 0.4771J, 0.4693J and 0.4617J when compared to the existing methods like Fractional Artificial Lion (FAL).

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Section: Discussionmentioning

confidence: 99%

Section: Iiliterature Surveymentioning

confidence: 99%