Social element of big data analytics
Awais Ahmad · 2016
As we delve deeper into the Internet of Things (IoT), we are observing the intensive interaction and heterogeneous communication among different social objects over the Internet. Such knowledge gives us the concept of Social Internet of Things (SIoT). SIoT comprises billions of interconnected objects that generate massive volume of heterogeneous, multisource, dynamic, and sparse data, which lead a system towards a major computational challenges, such as processing, analyzing, and storing data in an efficient manner. To address this problem, we propose a system architecture for processing a stream of Big Data with the enhanced features of parallel processing techniques. The proposed architecture consists of three functional domains, i.e., object domain, SIoT server domain, and application domain. The performance of the system architecture is tested on Hadoop using UBUNTU 14.04 LTS core™i5 machine with 3.2 GHz processor and 4 GB memory. The analysis and discussion show that the performance of the proposed system architecture fulfills the required desires if we increase the size of the datasets.