Work

Economical and efficient big data sharing with i-Cloud

Year: 2014

Type: conference-paper

Abstract: Big data can be hosted on cloud and being shared distributedly through cloud services in an unprecedented volume, variety and velocity. This causes not only cloud network congestions and delayed cloud services but also increases in public cloud data-out charges. Client-side cloud cache alleviates these problems. Furthermore, cloud cache must be aware of nonuniform data-out costs when big data is stored in hybrid clouds built with different public cloud providers. Deploying i-Cloud approach as the core mechanism of cloud cache could save data-out cost up to 14.78% or 4,425 USD saved per annum based on our representative scenario, and delivered 17.24% byte-hit, 17.96% delay-saving and 29.33% cache hit outperforming LRU, GDSF and LFU-DA approaches. A main finding is that i-Cloud, learning uniform cost patterns, could perform well against nonuniform cost environment.

Source: International Conference on Big Data and Smart Computing

DOI: 10.1109/bigcomp.2014.6741417

Authors: Thepparit Banditwattanawong, Masawee Masdisornchote, Putchong Uthayopas

Institutions: Sripatum University, Kasetsart University

Language: English

Topic: Caching and Content Delivery

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: National Science Foundation, Thailand Research Fund, Office of the Higher Education Commission