2018Unpublished venueRequires access

Deterministic Evolution Through Indexed Leaf Node Based Attachment in Complex Networks

Gautham Suresh, Abhishek Chakraborty, B. S. Manoj

Open publisher page 1 citations

Abstract

Complex networks are abstract graphs where the nodes are real-world entities and their relationships can be imitated as links. The relationships among various real-world entities are neither entirely random nor fully regular, thus, the structures of evolving complex networks are non-trivial in nature. To study the characteristics of such evolving complex networks, efficient network models, that can emulate the realworld networks, are needed. In this paper, a novel network model, deterministic evolution through leaf node attachment (DELNA), that can efficiently emulate many real-world networks, such as technological networks, social networks, and other manmade networks, is proposed. We also compare our DELNA-based network model with a few existing network evolution models, namely Barabási-Ravasz-Vicsck deterministic network model and Barabási-Albert network evolution model. DELNA can find applications in the Internet of things and the satellite communications, where the network resilience is a very crucial parameter.

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What this paper is about

Complex networks are abstract graphs where the nodes are real-world entities and their relationships can be imitated as links. The relationships among various real-world entities are neither entirely random nor fully regular, thus, the structures of evolving complex networks are non-trivial in nature. To study the characteristics of such evolving complex networks, efficient network models, that can emulate the realworld networks, are needed. In this paper, a novel network model, deterministic evolution through leaf node attachment (DELNA), that can efficiently emulate many real-world networks, such as technological networks, social networks, and other manmade networks, is proposed. We also compare our DELNA-based network model with a few existing network evolution models, namely Barabási-Ravasz-Vicsck deterministic network model and Barabási-Albert network evolution model. DELNA can find applications in the Internet of things and the satellite communications, where the network resilience is a very crucial parameter.

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Available abstract

Complex networks are abstract graphs where the nodes are real-world entities and their relationships can be imitated as links. The relationships among various real-world entities are neither entirely random nor fully regular, thus, the structures of evolving complex networks are non-trivial in nature. To study the characteristics of such evolving complex networks, efficient network models, that can emulate the realworld networks, are needed. In this paper, a novel network model, deterministic evolution through leaf node attachment (DELNA), that can efficiently emulate many real-world networks, such as technological networks, social networks, and other manmade networks, is proposed. We also compare our DELNA-based network model with a few existing network evolution models, namely Barabási-Ravasz-Vicsck deterministic network model and Barabási-Albert network evolution model. DELNA can find applications in the Internet of things and the satellite communications, where the network resilience is a very crucial parameter.

Key concepts: Complex network, Computer science, Preferential attachment, Evolving networks, Node (physics), Network formation, Hierarchical network model, Distributed computing

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