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Node Deployment Techniques for Link Prediction in Heterogeneous Social Networks

MAY ZIN THEIN, Hla Myo Tun

Abstract


Abstract

This research analyses the coverage problem in heterogeneous social network system with two types of sensor nodes having different sensing ranges. The Particle Swarm Optimization (PSO) algorithm is implemented for coverage optimization in heterogeneous network system. This algorithm is used for finding the optimal deployment of the sensor nodes by using specific fitness function. The performance of sensor nodes after running PSO algorithm is evaluated by using Euclidean distances for overlapped coverage of sensor nodes and probability sensing model. The simulations for random sensor node deployment and optimized sensor node deployment are implemented using MATLAB. Simulation results are presented to verify the proposed algorithm and performance evaluation for heterogeneous network system.

Keywords: Node Deployment, Link Prediction, Network Flow, Heterogeneous Social Network, Numerical Analysis.

Cite this Article

Hla Myo Tun, May Zin Thein. Node Deployment Techniques for Link Prediction in Heterogeneous Social Networks. Recent Trends in Sensor Research & Technology. 2020; 7(1): 16–22p.



Keywords


Node Deployment, Link Prediction, Network Flow, Heterogeneous Social Network, Numerical Analysis

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References


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DOI: https://doi.org/10.37591/rtsrt.v7i1.3812

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