A New Approach to Modeling of Bio-inspired Information Diffusion with Ant Colony Optimization in Complex Networks

Dewi, Reisa Rahmatu; Kim, Tae Hyong

doi:10.1007/978-3-319-07401-6_13

Cited by 2 publications

(1 citation statement)

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“…An important class of information diffusion models are inspired from natural and biological systems. A typical example is provided by Dewi and Kim [61], who propose a bio-inspired model for information diffusion in complex networks using ant colony optimization. The model introduces selfishness in forwarder nodes and unacquainted nodes and employs ant colony optimization to find shortest path and manage the selfish nodes and disjoined nodes.…”

Section: Content Diffusion Models For Social Data Streamsmentioning

confidence: 99%

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

Kilanioti

Fernández-Montes

Fernández-Cerero

et al. 2019

Lecture Notes in Computer Science

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This chapter presents the authors' work for the Case Study entitled "Delivering Social Media with Scalability" within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with

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Section: Content Diffusion Models For Social Data Streamsmentioning

confidence: 99%