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http://dx.doi.org/10.6109/jkiice.2016.20.4.721

Performance Analysis of User Clustering Algorithms against User Density and Maximum Number of Relays for D2D Advertisement Dissemination  

Han, Seho (Department of Electrical, Electronic and Control Engineering & IITC, Hankyong National University)
Kim, Junseon (School of Electrical & Computer Engineering, UNIST)
Lee, Howon (Department of Electrical, Electronic and Control Engineering & IITC, Hankyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.4, 2016 , pp. 721-727 More about this Journal
Abstract
In this paper, in order to resolve the problem of reduction for D2D (device to device) advertisement dissemination efficiency of conventional dissemination algorithms, we here propose several clustering algorithms (modified single linkage algorithm (MSL), K-means algorithm, and expectation maximization algorithm with Gaussian mixture model (EM)) based advertisement dissemination algorithms to improve advertisement dissemination efficiency in D2D communication networks. Target areas are clustered in several target groups by the proposed clustering algorithms. Then, D2D advertisements are consecutively distributed by using a routing algorithm based on the geographical distribution of the target areas and a relay selection algorithm based on the distance between D2D sender and D2D receiver. Via intensive MATLAB simulations, we analyze the performance excellency of the proposed algorithms with respect to maximum number of relay transmissions and D2D user density ratio in a target area and a non-target area.
Keywords
User clustering Algorithm; D2D Advertisement Dissemination; User Density; Social Commerce Service;
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