Resilient Big Data Monetization
Networking and Internet Architecture
2015-09-16 v1
Abstract
Resilient Big Data monetization is devised as k-dominance and m-connectivity problems, such that common-interests are connected by k-ways to measurement tools, which are tied within each other in m-ways. Consequently, a greedy approximation algorithm Plutus (i.e resembling Greek god of wealth) is proposed, which isolates measurement tools to ac-quire domination over common-interests, establishes synergy from common-interests to measurement tools and then acquires divergence and sustains it within measurement tools
Cite
@article{arxiv.1509.04545,
title = {Resilient Big Data Monetization},
author = {Rossi Kamal and Choong Seon Hong},
journal= {arXiv preprint arXiv:1509.04545},
year = {2015}
}
Comments
8 pages, NOMS 2016