Tutorial: Resilient Big Data Measurement

You are here

Resilient Big Data Measurement

Rossi Kamal

Kyung Hee University & IROBIX INC

Choong Seon Hong

Kyung Hee University



Big Data Monetization is resembled by the domination of service provider's measurement tools over Smart-device user's common-interests (e.g. environmental information, emotion,etc.). However, adaptation to usage-dynamics necessitates stronger binding between common-interests and measurement tools.Hence, 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 acquire domination over common-interests, establishes synergy from common-interests to measurement tools and then acquires divergence and sustains it within measurement tools. In this tutorial, we have presented our Big Data Measurement Software.