Processing Geo-Dispersed Big Data in an Advanced MapReduce Framework

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Processing Geo-Dispersed Big Data in an Advanced MapReduce Framework

Big data takes many forms, including messages in social networks, data collected from various sensors, captured videos, and so on. Big data applications aim to collect and analyze large amounts of data, and efficiently extract valuable information from the data. A recent report shows that the amount of data on the Internet is about 500 billion GB. With the fast increase of mobile devices that can perform sensing and access the Internet, large amounts of data are generated daily.

In general, big data has three features: large volume, high velocity and large variety [1]. The International Data Corporation (IDC) predicted that the total amount of data generated in 2020 globally will be about 35 ZB. Facebook needs to process about 1.3 million TB of data each month. Many new data are generated at high velocity. For example, more than 2 million emails are sent over the Internet every second

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